Generative ai tools

Abstract

Disclosed are a variety of AI tools, including for example: an AI system configured to receive text and / or an image as a prompt and to tokenize the received image; an AI system configured to receive multiple prompts at once and to process these prompts as a group, optionally using commands included with the prompts; an AI system configured to take on a role having specific characteristics; an AI system configured to participate in a conversation with another AI; an AI system configured to participate in a conversation including more that two participants; an AI system configured to generate results based on a user's personal writing style; a prompt marketplace; an AI system configure for automatic generation of alternative search terms; an AI system configured for voice cloning; and various associated methods.

Description

Generative Al ToolsCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority and benefit of US provisional patent applications Ser. Nos. 63 / 441,833, filed January 29, 2023; 63 / 444,870, filed February 10, 2023; 63 / 446,893, filed February 19, 2023; 63 / 451,605, filed March 12, 2023; 63 / 459,640, filed April 15, 2023; 63 / 468,239 filed May 22, 2023; and 63 / 470,802, filed June 14, 2023; the disclosures of which are hereby incorporated herein by reference in their entirety.BACKGROUND

[0002] Artificial intelligence systems based on Generative Pretrained Transformer (GPT) models such as ChatGPT from Open Al are useful but can be difficult to use in an optimum manner.SUMMARY

[0003] Various embodiments of the invention include a user interface configured to facilitate the use of generative Al systems. These Al systems are typically configured to provide responses to prompts. The responses and prompts can include a wide range of media / content types, including text, audio, images, video, 3D metaverse content, and / or any combination thereof. The user interface may be configured for presentation on a computer, an AR / VR system, a mobile device a 3D display, and / or the like. The user interface may be visual, tactile, and / or audio.

[0004] In some embodiments the user interface is configured for a user to selectively generate content according to customized settings. For example, a user may select a desired "tone," "sentence structure," "format," and / or other "style" attributes. A style may be based on a set of defined attributes, e.g., attributes of text meant to be read by a child, or may be based on existing content. Style logic may be configured to modify responses received from an Al system to match a particular document, to modify a prompt to achieve the desired style, and / or may be trained to match a style found in a plurality of documents. In some embodiments, a style may include a specific output format. For example, style logic maybe configured to produce a response in a Word document, an Excel spreadsheet or a PowerPoint presentation. In such examples the style logic may further be configured to perform operations on the output. For example, to sort data or perform a standard excel operation on the data in a spreadsheet, or to use a specific PowerPoint presentation format or Word style. Style logic is optionally configured as an add-on or integrated into commonly used computerapplications such as those discussed herein.

[0005] Various embodiments of the invention include personalization logic configured to personalize output from an Al. For example, output may be personalized based on an individual style such as a desired formality or writing type. This personalization logic may function as a middle layer between a user interface and the Al. In one example, the personalization logic may be trained to produce output that reads like a patent specification. In another example, the logic may be trained to read like a particular person's e-mail correspondence. In this case, the logic may be trained using the person's past emails. In another example, the logic may be trained to produce output that reads like it was written by Hemingway. The logic may operate by modifying prompts sent to the Al and / or by modifying responses received from the Al. The logic may also be integral to an Al which is configured to receive a prompt plus a style designation. Various embodiments of the invention include an ability to buy / import customized styles. Such styles are optionally registered as an NFT and / or on a blockchain.

[0006] Various embodiments of the invention include a content authoring tool. This tool is optionally an addon for a word processing, image editing, video editing or metaverse editing application. In one example, the content authoring tool is configured generating or receiving an outline, optionally modifying and / or editing the outline, generating content based on the outline, selecting and / or modifying a style of the generated content. In an illustrative example, a tool for writing an essay may include: 1) logic configured to help choose an essay topic, 2) logic configured to create and / or manage an outline of the essay, 3) logic configured to conduct research on the essay subject, 4) logic configured to generate the essay based on the outline, and 5) logic configured to edit and revise the essay. The content authoring tool is optionally configured to develop content through an interactive process with a user. The amount of user control over and / or input to the interactive process is optionally user selectable. In some embodiments, the content authoring tool is configured to suggest prompts to a user, e.g., to suggest a set of alternative prompts to generate a paragraph corresponding to a particular outline element.

[0007] Various embodiments of the invention include a system configured for generating responses to an outline, the system comprising: outline management logic configured for the generation and manipulation of the outline; outline parsing logic configured to parse the outline based on nested levels of the outline and to generate a set of two or more promptstherefrom; Al interface logic configured to provide each of the two or more prompts (optionally) separately to an artificial intelligence system; answer (response) logic configured to receive an (optionally) separate response from the artificial intelligence system for each of the two or more prompts; and response display logic configured to display the separate responses to a user.

[0008] Various embodiments of the invention include a system configured to generate a response; the system comprising: an input configured to receive data including a set of prompts; parser logic configured to identify two or more prompts within the received set of prompts; Al interface logic configured to provide each of the two or more prompts separately to an artificial intelligence system; answer logic configured to receive response from the artificial intelligence system for in response to the two or more prompts; response display logic configured to display the separate responses to a user.

[0009] Various embodiments of the invention include an Al system 100 configured for generating a response to an image, the system comprising: an image input 110 configured to receive an image; image processing logic 115 configured to generate tokens representing contents of the image, the tokens including words representing a scene in the image and / or a selected object within the image; Al interface logic 130 configured to provide the tokens to an artificial intelligence system based on a GPT model; answer logic 140 configured to receive a response to the tokens from the artificial intelligence system, wherein the tokens optionally include less than 10 words and the response includes more than 20 words; response display logic 145 configured to display the response to a user; and a digital processor 195 configured to execute at least the image processing logic or the answer display logic.

[0010] Various embodiments of the invention include a question answering tool. The question is optionally provided as an image. For example, the question may be a math problem or a multiple choice question and the question answering tool is configured to receive a picture of the question, parse the picture to determine the question and use a generative Al to provide an answer to the question. The types of questions that can be answered include, but are not limited to: yes / no questions, multiple-choice questions, math equations, mathematical proofs, math word problems, word insertion (fill in the blank) questions, questions requiring a narrative answer, logic questions, riddles, and / or the like. In some embodiments, a user my provide an image or other content and request a standard question be applied to the content. For example, "what is this," "when is this," "how doesthis work / ' "where is this" or "who is this," etc.

[0011] Various embodiments of the invention include an Al system 100 for automated answering of questions comprising: an input 110 configured to receive an image and / or text, the image or text including a question; optional image processing logic 115 configured to generate tokens representing the question; Al interface logic 130 configured to provide the tokens or the text to an artificial intelligence system; answer logic 140 configured to receive an answer to the question from the artificial intelligence system; answer display logic 145 configured to display the answer to a user; and a digital processor 195 configure to execute at least the image processing logic or the answer display logic.

[0012] Various embodiments of the invention include Al systems configured for multiparty interactions including three or more entities. Such interactions may be text based, verbal, between avatars, etc. For example, a text or audio conversation may take place between 3, 4, 5 or more entities. These entities may include any combination of humans or Als. For example, two humans may have a 3-way conversation with an Al, or two Als may have a 3- way conversation with one human. The type (human or Al) of some entities may be unknown. In some embodiments, the contributions of more than one Al to an interaction is managed by a supervisor layer configured to determine which responses from the two or more Als should be added to the interaction. In some embodiments, an Al in the conversation may include logic configured to determine where in the interaction to provide a response and where not to provide a response. Such an Al may be able to participate in the interaction without need of a supervisor layer. Al systems used for multi-party (3+) interactions may also include logic configured to identify which entities contributes each content to the interaction. For example, to identify who said what and to generate responses based not only on what was said but who said it.

[0013] Various embodiments of the invention include logic configured to recognize and execute commands within or between prompts. As used herein, the term "commands" is intended to refer to executable instructions that may be executed by logic, e.g., software or hardware instructions. The commands can include, for example, conditional statements, arithmetic operations, input\output operations, and\or other types of commands typically found in scripting or computer languages. In some embodiments, a conditional statement may be used to select among a set of alternative prompts based on the contents of prior responses and / or based on an additional input by a user. For example, an input / outputcommand may be used to ask a user if a previous response was satisfactory. If it was, then the system moves on to a subsequent prompt. If it was not, then the system may retry a variation of a previous prompt. In another example a script may be used to generate a document from an outline, wherein the script is used to maintain continuity between generated part of the document. In this case, the script may be configured to identify which part of the outline is to be expanded on (within each step which is associated with a different prompt) and which parts of the outline are to be considered in order to maintain continuity.

[0014] Various embodiments of the invention include an analysis system configured to analyze text, audio, video or a virtual environment, the system including: an trained artificial intelligence system or an input / output configured to communicate with a trained artificial intelligence system; an input configured to receive an input sequence including the text, audio, video and / or virtual environment; assignment logic configured to assign elements of the input sequence to one or more entities (e.g., sources) within the input sequence; (for example, which avatar said that or performed the action, etc.); prompt logic configured to provided the input sequence and the assignment of elements to the artificial intelligence system; output configured to provide an output of the artificial intelligence to a user, the output being based on the input sequence and the assignment; and a microprocessor configured to execute at least the assignment logic.

[0015] Various embodiments of the invention include a supervised Al system 100 configured to generate a response; the system comprising: an input configured to receive data including a set of prompts; an optional parser configured to identify prompts within the received data; Al interface logic configured to provide each of the prompts to two or more artificial intelligence system (Al systems); Answer logic configured to receive a separate response from the two or more artificial intelligence system for each of the two or more prompts; Al supervision logic configured to determine which of the separate responses to include in an interaction between two or more parties; optional script logic 150 configured to identify commands within the data and to execute the identified commands; and optional response display logic configured to display the determined separate responses to a user and / or the one or more of the Al systems. Optionally, the system is optionally configured to manage an interaction between a person and an Al and a party which may or may not be an Al. Where the system is optionally configured to manage an interaction between two or more humans and at least one Al. Optionally, the system is configured to manage an interactionbetween at least one person and at least two or more Al.

[0016] Various embodiments of the invention include a conversational Al system 100 configured to generate a response; the system comprising: an input configured to receive data including a set of prompts, the data may include an image, audio and / or text; an optional parser configured to identify prompts within the received data, wherein the identified prompts are optionally from two or more sources and identification of the prompts includes assigning each prompt to one of the two or more sources; (the prompts are optionally part of a conversation between the two or more sources. The two or more sources could be humans, Ais or any combination thereof. Their form (human or Al) may not be known.); an artificial intelligence system (Al system) configured to provide a response based on a received prompt; Answer logic configured to determine whether or not to provide the response to the sources based on a value of the response to the conversation; Optional Al supervision logic configured to determine which of more than one alternative responses to include in an interaction between two or more parties; optional script logic 150 configured to identify commands within the data and to execute the identified commands; and optional response display logic configured to display the determined separate responses to a user and / or the one or more of the Al systems. Optionally, the system is optionally configured to manage an interaction between a person and a an Al and a party which may or may not be an Al. Where the system is optionally configured to manage an interaction between two or more humans and at least one Al. Optionally, the system is configured to manage an interaction between at least one person and at least two or more Al.

[0017] Various embodiments of the invention include a Al system 100 for automated generating of text comprising: a text input 120 configured to receive text, the text including a series (one or more) of prompts (e.g., an outline); text processing logic 125 configured to identify each of the prompts within the text; Al interface logic 130 configured to provide the each of the prompts to an artificial intelligence system; answer logic 140 configured to receive a plurality of responses to the prompts an from the artificial intelligence system; and answer display logic 145 configured to display the responses to a user or storage; optional script logic 150 configured to identify commands within the text and to execute the identified commands; an optionally command input configured for user to provide command for execution on the plurality of responses; and optionally wherein at least the image processing logic or the answer display logic are configured to be executed by a digital processor 195.

[0018] Al System 100 typically further includes one or more Digital Processor 195 configured to execute at least Image Processing Logic 115, Answer Display Logic 140, Outline Management Logic 155, and / or any of the other logic included in Al System 100. Digital Processor 195 may include an integrated circuit, an optical circuit or a quantum computing device.

[0019] Various embodiments of the invention include a method of generating a conversation using two or more generative Als, the method comprising: optionally assigning characteristics to a first Al; optionally assigning characteristics to a second Al; optionally assigning a scope of the conversation; receiving an initial prompt from a user; modifying the initial prompt to include optionally the characteristics assigned to the first Al and the assigned scope; providing the modified initial prompt to the first Al; receiving a first response to the modified initial prompt from the first Al; modifying the first response to include characteristics assigned to the second Al and the assigned scope; providing the modified first response to the second Al; receiving a second response to the modified first response from the second Al; and repeating the steps of receiving a response, modifying the response and providing the modified response to the first or second Al to create a conversation between the first or second AL

[0020] Various embodiments of the invention include a methos of providing prompt confidentiality, the method including: a first user writes a first prompt; the first user uploads the first prompt to a prompt marketplace; the first user optionally provides one or more search terms to be associated with the first prompt, search terms optionally include the source of the first prompt, e.g., that the first prompt is from the account of a well-known influencer or that the first prompt is meant to be humors; the first user optionally provides distribution terms to be associated with the first prompt, distribution terms may include permission to see and / or modify, purchase price, rental price, rental duration, number of available instances of the first prompt for sale or rental, pay-per-use, and / or the like. Optionally, the first prompt may be free to use. Optionally, the first user can designate that the prompt not be confidential and / or may be used on an unlimited basis. Optionally, the first user may designate that the price of using the first prompt increase or decrease with time and / or popularity. Optionally, the first user may lock distribution terms for the first prompt such that they cannot be changed, thus, assuring a purchaser that the prompt they paid for will not later become free or available at a lower cost from the creator. A second useraccesses the first prompt marketplace and identifies the first prompt as one the second user would like to purchase / rent or otherwise use. The identification is optionally based on a search term, such as a source / author name, on a user rating of the first prompt, on a recommendation of the first prompt, on sample responses generated using the first prompt, and / or the like. The second user may be one of a plurality of second users who access and make use of the first prompt, optionally according to the distribution terms. An identifier of the first prompt and the distribution terms are optionally recorded on a blockchain associated with a smart contract configured to enforce the distribution terms. The second user purchases or rents permission to use the first prompt, optional for monitory or other consideration. Rental may be for a per use basis, for a fixed time, for a specified number of uses, etc. Note that obtaining permission to use the first prompt may be exchanged separately on the prompt marketplace relative to ownership of the first prompt. In some instances, the marketplace is further configured for transfer of full ownership of the first prompt, optionally including rights to any revenue / consideration received from use of the first prompt. Optionally, ownership and / or usage rights with respect to the first prompt may be transferred and retransferred on the prompt marketplace. For example, a user with rented rights to use a prompt may sublet those rights to another user within their rental period. As is described elsewhere herein, such rights and transfers are optionally recorded on a blockchain. As such, a user that has sublet their rental rights to another may not use the first prompt during the term of the sublet. The prompt is associated with an account of the second user based on the permission purchased or rented. Such association may be time limited based on a rental of the first prompt. The time limit is optionally enforce using data recorded on a blockchain. To use the prompt, the second user first selects the first prompt from among what may be a plurality of prompts associated with their account. The prompts associated with their account may be prompts authored by the second user (and optionally saved) and / or prompts (or permissions / rights thereto) purchased or rented from the marketplace. The selection being for use in a next exchange and or for use in a series of exchanges, with an GPT engine. The selection of the first prompt by the second user is communicated to a prompt server. The second user (purchaser / renter) then provides a second prompt via their client device. The second prompt is communicated from the client device to the prompt server. Optionally the selection of the first prompt and the second prompt are communicated to the prompt server together. Optionally the second prompt isfiltered at the prompt server to remove content that would expose details of the first prompt. For example, a second prompt that included "repeat all of this prompt back to me" may be modified to prevent a response that includes the first prompt verbatim. Optionally, according to the distribution terms, details of the first prompt are hidden from the second user. At the prompt server, the first prompt and the second prompt are combined to create a combined prompt. For example, the first prompt may be added as a prefix and / or suffix to the second prompt. In alternative embodiments, the first prompt may be used to modify the second prompt according to a script or a set of rules. For example, the first prompt may include a rule "replace all references to male gender with references to female gender" or "randomly mix up order of words." Optionally, an account of the second user is charged for use of the first prompt, all or part of this charge may be provided to an account of the first user. The combined prompt is sent to a GPT engine configured to provide a response to the combined prompt. A response to the combined prompt is received at the prompt server. The response is optionally filtered / altered to remove any instance of the first prompt included therein. The response is communicated from the prompt server to the client device of the second user. In alternative embodiments, the response is communicated directly from the GPT engine to the client device without passing through the prompt server. The response received at the client device is displayed to the second user.

[0021] Various embodiments of the invention include a method of exchanging prompts, the method comprising: receiving a first prompt from a first user; optionally receiving a description of the first prompt from the first user, the description including a characterization and / or purpose of the first prompt; optionally receiving distribution terms for the first prompt; optionally recording the distribution terms on a blockchain; offering the first prompt to a second user; receiving a request for permission to use the first prompt from the second user; associating the first prompt with an account of the second user; optionally recording the association of the first prompt with the account of the second user on the blockchain according to a smart contract; optionally receiving consideration from the second user for use of the prompt; receiving a second prompt from the second user; (optionally filtering the second prompt to avoid giving the second user details (e.g., the actual text) of the first prompt.); combining the first prompt and the second prompt to generate a combined prompt; (optionally at a server such that the second user does not see details of the first prompt.); providing the combined prompt to a GPT and / or LLM based Al system; receiving aresponse to the combined prompt from the Al system; optionally filtering the response to avoid providing details of the first prompt to the second user; and providing the (optionally filtered) response to the second user.BRIEF DESCRIPTION OF THE DRAWING

[0022] FIG. 1 illustrates an Artificial Intelligence (Al) system, according to various embodiments of the invention.

[0023] FIG. 2 illustrates a multi-chat system according to various embodiments of the invention.DETAILED DESCRIPTION

[0024] As used herein, the term "Al" is used to refer to artificial intelligence. An artificial intelligence is a machine-based system configured for perceiving, synthesizing, and / or referring information. Artificial intelligence systems may be based on neural networks, large language models (LLM), knowledge graphs, and or the like. One class of artificial intelligence systems is based on GPT.

[0025] As used herein, the term "GPT" is used to refer to a generative pre-trained transformer. A generative pre-trained transformer is a family of language models generally trained on a large corpus of text data to generate human-like text. They may be built using several blocks of a transformer architecture. They can be fine-tuned for various natural language processing tasks such as text generation, language translation, and text classification. The "pre-training" in its name refers to the initial training process on a large text corpus where the model learns to predict the next word in a passage, which provides a solid foundation for the model to perform well on downstream tasks with limited amounts of task-specific data. As used herein, it is not intended that GPT be restricted to text based systems. Rather, GPT may be applied to other types of content.

[0026] As used herein, the term "prompt" is used to refer to the input provided to an artificial intelligence system, and / or other logic. Typically, a prompt is expected to initiate the generation of a "response." A response is the output of the artificial intelligence system or logic that results from the prompt. Prompts and responses may include a wide variety of content types including text, images, audio, 3D environments, actions, commands, and / or any of the other types of content discussed herein. Prompts and responses are optionally passed through a middle layer of logic between a user interface (or other interface) and an artificial intelligence. This logic may be configured to modify, edit or supplement theprompts and / or responses.

[0027] As used herein, the term "style" is used to refer to characteristics of generated output. In the case of text these characteristics can include factors such as writing style, grammar, word choice, sentence structure, narrative tone, spelling, language, dialogue v. narrative, question v. statement, punctuation, font, headings, layout, paragraph structure, and / orthe like. For example, one style of output may include a nested outline while another style of output includes a narrative description, while a third style of output includes a dialogue between two or more parties. A style may refer to an output type. For example, whether the output is in excel, text or audio format. With regard to audio, style may refer to volume voice type, speaking rate, background noise, data file type, and / or any other characteristics of audio. With regard to images or video, style may include brush strokes, photograph versus drawing, color scheme, action speed, and / or any other type of image or video characteristics. Additional examples of "style" are discussed elsewhere herein.

[0028] As used herein, a "question" is typically content that requests a response. Although, in some embodiments, logic is configured to distinguish between actual questions and rhetorical questions. Example of a question include: "what time is it?" or "who were the winners of the last 10 Super Bowls?" As noted herein there are a wide variety of possible questions including, for example, multiple choice questions, math questions, narrative questions, yes / no questions, etc. Some embodiments are specifically configured to answer questions such as those that may be found in homework or a quiz. Further, some embodiments are specifically configured to generate questions for these and other purposes.

[0029] As used herein, the terms "multiparty" or "multi-chat" are used to refer to interactions, e.g., conversations, including two, three, four or more parties. Unless specifically noted, the use is specifically meant to include interactions including three or more parties. The parties may include any combination of humans, Al entities, and / or other entities. For example, a conversation may include a human and two Als, a conversation may include three Als, or a conversation may include two Als and one human. Other entities can include, for example, a data source, a sensor, the Internet, a computing system and / or the like. For example, an "other entity" might include a machine control system configured to provide sensor data to a conversation and to receive commands from the conversation. Theparties to the conversation may be represented by avatars come by a unique identifier such a phone number, an e-mail address, a username, and / orthe like. For example, an Al configure to participate in a text conversation may be assigned a unique phone number or extension. In some embodiments, the parties may include just two Als. For example, one embodiment of a multi-party interaction includes two Als configured to communicate with each other so as to generate a conversation that may then be presented to human readers or listeners. In this case, after an initial prompt, only the Als may contribute further to the conversation.

[0030] A variety of inventions and embodiments thereof are described herein. These include, for example, an adaptable interface that allows a user to personalize prompts sent to an artificial intelligence system, authoring tools, question answering tools, use of images as prompts, and multi-prompt systems. Any of the embodiments described herein may include the Al that generates responses to prompts and / or may include an interface (e.g., API) to an Al managed by a third party. Optionally, both internal and external Al systems are employed in any of the described systems and methods.

[0031] In some embodiments an interface is configured to provide a user with customization options. For example, to set a desired "tone," "sentence structure," "style" or format of a desired response. Some embodiments include authoring tools configured for a user to generate a document. For example, to turn an outline into an essay, to improve transitions between paragraphs or other sections, to check antecedent basis, to check logical flow throughout document, etc. In some embodiments tools are configured to provide answers to questions, which may be provided as an image, for example multiple choice questions or mathematical questions. In some embodiments, multiple prompts may be provided by a user in a single document, for example, as a document outline including multiple outline levels.

[0032] FIG. 1 illustrates an Artificial Intelligence (Al) system 100, according to various embodiments of the invention. Al system 100 is configured for generating a response to one or more prompts. The prompts may include any combination of text, an image, data, and / or command. In some embodiments, Al System 100 includes an Image Input 110 configured to receive an image. The image may be part of an image sequence, e.g., a video. The image may be a virtual image or environment. For example, the image may include a 3D environment including textured surfaces as seen from a specific point of view.

[0033] Al System 100 optionally further includes Image Processing Logic 115 configured to generate tokens representing contents of the image. The tokens can include, for example, words representing an action with the image, a subject matter of the image, a scene in the image, and / or a selected object within the image. An output of Image Processing Logic 115 can include a description of any characteristic of the image. Image Input 110 and / or Image Processing Logic 115 may be configured to audio data as well as or alternatively to image data. For example, Image Processing Logic 115 may be configured to convert audio data to text.

[0034] Image Processing Logic 115 is optionally configured to extract from an image or a sequence of images: the outline, a question, the two or more prompts, a prompt, image tags, and / or a source of an image. Image Processing Logic 115, Text Processing Logic 125, and or Script Logic 150 are optionally configured to identify received commands within the data and to execute the identified commands, the commands being received along with the prompts or within the prompts, the commands optionally including conditional logic.

[0035] Al System 100 typically further includes a Text Input 120. Text Input 120 may be part of a graphical user interface (GUI) and / or an application program interface (API). Image Input 110 and Text Input 120 are optionally part of a same interface. In one embodiment, this interface includes a text input field into which a user can enter text and an image input into which a user can provide images.

[0036] Al System 100 typically includes Text Processing Logic 125. Text Processing Logic 125 is configured to process received text to, for example, identify prompt text, identify different prompts, identify commands, and / or identify data within the received text. For example, Text Processing Logic 125 may be configured to identify more than one prompt within received text and to identify commands or Boolean operators configured to be applied to the more than one prompt. Text Processing Logic 125 is optionally further configured to identify a source of text. For example, in a chat session involving more than two sources of text, Text Processing Logic 125 may be configured to assign a particular part of a received text to a specific source. Where the text includes a conversation between an Al and more than one additional entity, Text Processing Logic 125 may assign parts of the text to specific members of the additional entities.

[0037] Any of Image Input 110 through Text Processing Logic 125 are optionally parts of a chat environment in which entities can chat with each other. A chat environment is theenvironment in which a chat or other multi-party interaction takes place and typically includes supporting logic. For example, a Chat Environment 220 may include a browser window, a texting service, a social media application, a user interface, a virtual environment (e.g., a metaverse), a game, a communication application, etc. The chat environment may be configured for specific types of interactions. For example, one chat environment may be configured for interactions between an Al, a human and a traffic control system. One chat environment may be configured to support interactions between family in the real world, avatars in the metaverse or in a computer game and / or a non-player character as represented by an Al.

[0038] Al System 100 further includes Al interface logic 130 configured to provide the tokens, data, commands, and / or text to Al Logic 135. Al Logic 135 can be included as part of Al System 100 or may be an external system, such as ChatGPT by OpenAL Al Logic 135 is optionally a trained artificial intelligence system (e.g., machine learning system) based on a GPT model. Al Logic 135 is configured to provide an answer (e.g., a response) to a prompt.

[0039] Al System 100 further includes Answer Logic 140 configured to receive a response to the tokens and / or text from the artificial intelligence system. In some embodiments, the tokens optionally include less than 10 words and the response includes more than 20 words. In embodiments of Al System 100 that include Al Logic 135, Answer Logic 140 may include merely a memory storage internal to Al System 100.

[0040] Answer Logic 140 is optionally configured to merge two separate responses received in response to a same outline element or a subset thereof. Answer Logic 140 is optionally configured to check consistency between a received response and one or more previously received responses based on the same outline. Image Processing Logic 115 and / or Text Processing Logi 125 may be configured to recognize organization of the outline, e.g., by identifying nesting levels of the outline.

[0041] Al System 100 response further includes Answer Display Logic 145 configured to present (e.g., display) the response to a user. The presentation can include an image, video, audio, text, a virtual environment, and / or other content. Answer Display Logic 145 may be configured to display the response within a user interface, e.g., a GUI.

[0042] Answer Display Logic 145 is optionally configured to display received responses to the user in combination with previously received responses and optionally in combination with elements of the outline. Answer Display Logic 145 is optionally configured to allow theuser to edit a response prior to providing a subsequent response, the response and subsequent response both being based on elements of the outline. Answer Display Logic 145 is optionally configured to allow the user to adjust a style of a response. Answer Display Logic 145 is optionally configured to allow the user to adjust conformity between two responses. Answer Display Logic 145 is optionally configured to allow the user to adjust the order of two responses within generated content.

[0043] In various embodiments Al System 100 is configured to generate answers (e.g., responses) based on an outline. These answers may be textual and / or any of the other types of content discussed herein (e.g., audio, images, video, 3D virtual environment, etc.). These embodiments include Outline Management Logic 155 configured for the generation, use, and / or manipulation of the outline; and Outline Parsing Logic 160 configured to parse the outline based on nested levels of the outline and to generate a set of two or more prompts therefrom. The set of prompts may be provided to Al Logic 135 by Al Interface Logic 130 as individual prompts or as subsets (parts) of the outline. For example, an outline having 20 points may be provided to Al Logic 135 as a separate prompt for each outline element, as a prompt representing multiple elements, and / or in sets of more than one prompts each prompt representing an element.

[0044] Outline Management Logic 155 is optionally configured for importing the outline from an external source. Outline Management Logic 155 is optionally configure to use a first element of the outline and the artificial intelligence system to generate sub elements of the first element of the outline. Outline Management Logic 155 is optionally configured to display the outline in a user interface, the user interface being for a user to review and / or edit the outline. Outline Management Logic 155 is optionally configured to generate the outline from preexisting content.

[0045] Outline Parsing Logic 160 is optionally configured to generate the two or more prompts such that the responses from the two or more prompts are consistent with each other. Outline Parsing Logic 160 is optionally configured to generate the two or more prompts such that a response generated using a sub-element of the outline is consistent with the parent of the sub element, within a nested outline.

[0046] In embodiments of Al System 100 configured to use an outline, Answer Logic 140 (elsewhere referred to as response logic) may be configured to receive an (optionally) separate response from the artificial intelligence system for each of the two or moreprompts. Likewise, Image Input 110 and Text Input 120 may be configured to receive data including a set elements of an outline, which may represent a set of prompts. Image Processing Logic 115 and / or Text Processing Logi 125 (functioning as "parsing logic") may be configured to recognize organization of the outline, e.g., by identifying nesting levels of the outline. Use of Image Processing Logic 115 and / or Text Processing Logi 125 as parsing logic to identify two or more prompts within the received set of prompts is not necessarily limited to operations on outlines. For example, the parsing logic may be configured to identify prompts to use as a part of a script, and / or to be used to generate an answer and then subsequently modify the answer. Separate prompts identified using Text Processing Logic 125 and / or Image Processing Logic 115 may be separately provided to Al Logic 135 or may be provided to Al Logic 135 as a set.

[0047] As an illustrative example, Al System 100 may be used to generate a document, e.g., an essay, using the following process. The elements of Al System 100 are optionally configured to perform these steps: a. Choose a Topic: The first step in writing an essay is to choose a topic. With the help of Al Logic 135 (or an alternative GPT Al system), one can brainstorm ideas by typing in keywords related to your topic. Al Logic 135 will then provide you with a list of related topics and questions to help you narrow down your ideas. Once you've chosen a topic, you can proceed to the next step. b. Title: An optional next step is to provide the selected topic to Al Logic 135 and request a title for the essay. In response, Al Logic 135 will provide one or more alternative titles for the user to select from. c. Create an Outline: Before you start writing, it's important to create an outline for your essay. An outline will help you organize your ideas and ensure that your essay is coherent and well-structured. With the help of Al Logic 135, you can generate a basic outline by providing, via Text Input 120, a topic and a few keywords. Al Logic 135 will then provide you with a structured outline that you can use as a guide for your essay. In a typical example, Al Logic 135 may be used to generate a top-level outline based on the topic and / or selected title. The user may also provide a set of "main points" that they wish to include in the outline. In response, Al Logic 135 will provide a top-level outline having a set of outline elements in order. d. Edit outline: Optionally, the user is given a chance to modify the outline elements, this modification can include editing the text of the outline elements, altering the order of the outline elements (e.g., by drag-and-drop), and / or expanding outline elements. Expansion of outline elements can include selection of a particular outline element and requesting the selected element be expanded into an ordered set of outline elements at the next (lower) level of the outlines. Two, three or more outline levels may thus be generated. Optionally, an outline element may be dragged to a different outline level. Editing may be performed by Text input 120. Outline Management Logic 155 is optionally configured to edit the outline. e. Conduct Research: After creating an outline, it's time to conduct research on your chosen topic. You can use Al Logic 135 to help you find relevant sources of information. Simply provide Al Logic 135 with a few keywords related to your topic, and it will provide you with a list of articles, books, and other sources that you can use to support your arguments. f. Write the Essay With the help of Al Logic 135 and Outline Management Logic 155, writing an essay is easier than ever. Simply provide Al Logic 135 (using outline Management Logic 155) with your outline and the relevant sources of information, and it will provide you with suggestions for how to structure your essay, as well as provide you with sentences and phrases that you can use in your writing. You can also ask Al Logic 135 to provide you with examples of essays on similar topics, which can be a great way to get inspiration and ideas for your own essay. The essay may be written one outline element at a time, or all at once. When generating text for a particular outline element, an optional feature of Al Logic 135 is to provide other outline elements in the prompt sent to the GPT engine for the particular outline element. For example, if text for a third level outline element is being generated, then all the outline elements of the second and first level may be included in the prompt. This causes the text to be generated with consideration of other relevant elements within the outline. Optionally, one, two or more of the immediately preceding paragraphs arealso included in the prompt. These paragraphs may or may not have been edited by the user. Specifically, if a user edits a paragraph and then uses the outline and Al to generate a next paragraph the edited version of the paragraph is used rather than merely the unedited (Al generated) version of the paragraph. g. Edit and Revise Once you've finished writing your essay, it's useful to edit and revise your work to ensure that it is clear, concise, and well-written. Al Logic 135 can help you with this by providing suggestions for grammar and spelling errors, as well as offering suggestions for how to improve your writing. You can also ask Al Logic 135 to provide you with feedback on your writing, which can be a great way to improve your writing skills over time. In conclusion, writing an essay with the help of Al Logic 135 can be a great way to make the process easier and more efficient. By using Al Logic 135 to brainstorm ideas, create an outline, conduct research, write an essay, and edit and revise your work, you can create a well-structured, well-researched, and well-written essay in no time.

[0048] Example: (Any of the steps below may be done automatically, and / or prompted by the AL)Human: Give me some ideas for a high school essayAl (Al System 100): A great essay topic for a high school student is to explore the importance of family. They could research different types of family structures, highlighting how each type of family impacts the lives of its members. They could discuss how values and traditions help define family and how a family's love and support help each individual reach their goals. Students could incorporate personal stories to illustrate the positive effects a loving family can have on a person's development. Finally, they could talk about the importance of respecting and celebrating family diversity.Human: Suggest titles for an essay about the importance of family, with emphasis on non-traditional family structures.Al: (offers several alternative titles for the user to select from.) - User selects using outline Management Logic 155, Text Input 120, and / or Image Input 110. Human: Create an outline for an essay about the importance of family (This isbased on the selected title and the stated emphasis.)Al: Outline for an Essay About the Importance of Family:I. IntroductionA. Definition of familyB. Overview of different types of family structuresII. BodyA. Discuss how values and traditions shape each family.B. Describe how family members support and love each other.C. Share personal stories to illustrate the positive impact of family.D. Explain the importance of respecting and celebrating family diversity.III. ConclusionA. Summarize the role of family in a person's life.B. Emphasize the importance of respecting and valuing all families.Human: (reorders elements of the outline using drag and drop; manually adds two elements, and edits one of the elements suggested by the Al)Human: Name several books and websites that can be reliable sources of information for the essay about the importance of the family.Al: Books that can provide valuable information for an essay about the importance of the family include "The Meaning of Marriage: Facing the Complexities of Commitment with the Wisdom of God" by Timothy Keller, and "Strong Families, Strong World: Building Our Future From the Inside Out" by Jean Twenge. Additionally, websites such as the National Council on Family Relations (https: / / www.ncfr.org / ) and the Child Trends Data Bank (https: / / www.childtrends.org) can provide invaluable resources and up-to-date data on the issue.Human: Write a 500-word introduction for the essay about the importance of the family. Include citations by Timothy Keller and Jean Twenge.Al: The family is an essential part of human society. It plays an important role in the development and well-being of individuals, the community, and society as a whole. It is helpful to explore the importance of the family through the lenses of culture, history, and technology. Cultural significance lies at the heart of understanding theimportance of the family. The family is seen as a source of stability and continuity, providing emotional, physical, and social support. This makes it an important building block for both individuals and society in general. As Timothy Keller notes in "The Meaning of Marriage: Facing the Complexities of Commitment with the Wisdom of God" "a strong family is the foundation of any flourishing society" (pg.60). Historically, the family has also been viewed as an important economic unit. As noted by Jean Twenge in "Strong Families, Strong World: Building Our Future From the Inside Out", families were often "the producers of most goods and services" (pg. 12). They provided support for each other's needs, from the provision of food, clothing, and shelter, to the sharing of skills, knowledge, and resources. This helped ensure that everyone had access to basic needs and enabled them to thrive. The importance of the family is also seen in how technology has impacted its role in society. Technology can benefit the family by making communication with relatives easier, as connections can now be maintained through online chat services, video calling, and messaging apps. Technology can also help with day-to-day tasks, such as managing schedules, shopping, and banking, allowing more time to be available for family activities. To summarize, the importance of the family cannot be underestimated. It provides a source of stability, continuity, and support. It has historically been an essential economic unit and remains as relevant today as ever. Technology has made it easier than ever before to keep in touch and manage family activities, but technology should never take the place of direct interpersonal contact, which is essential for family relationships. Through understanding the cultural, historical, and technological contexts of the family and its role in society, it is possible to appreciate the immense importance it holds for individuals, the community, and society as a whole.

[0049] The user and Al may then step through each element of the essay to generate corresponding text using outline Management Logic 155 and / or Outline Parsing Logic 160. For each element, the preceding and / or following essay elements are optionally considered for text generation. Thus, the Al is provided knowledge of the essay organization and content as it generates each paragraph. Specifically, Al Logic 135 may use outline elements at a lower level of nesting and / or at a same level of nesting when converting an outline element to text. The user may be given opportunities to edit each paragraph as it isproduced. Repeat the same for each point and edit everything into one piece. Optionally, those parts of the essay generated by the Al v generated by the human are marked as such, e.g., using font or meta data.

[0050] In some embodiments, Al System 100 includes user interface logic (e.g., Image Input 110 and Text Input 120) configured for a user to provide one or more images and a specific question regarding the one or more images. For example the question may include "who is this," "what is this," "where is this," "how is this," "who made this," "How old is this," "Is this real," 'when is this," "where can I buy this," "how much does this cost," "how to make this," and / or any other question concerning the images. In a specific example, the user interface logic may be configured for a user to provide a video and audio and a question "Is the audio authentically from the person in the video?"

[0051] In some embodiments, Al System 100 is configured for automated answering of questions. These embodiments can include Answer Logic 140 configured to receive an answer to a user provided question, from Al Logic 135. Text Processing Logic 125 is optionally configured to determine if a prompt includes a question.

[0052] A question answering tool can be configured to start with a photograph of a question, the question can be a math problem including an equation, can be a multiplechoice problem, can be a question requesting a written answer. The photograph may process to tokenize the question; The question is converted to a format suitable for analysis using a GPT trained AL Receiving an answer to the question from the Al. Providing the answer to the question.

[0053] In various embodiments: the question includes a math equation or a chemical formula; the question includes a math, physics, chemistry, legal, medical, language, graphical, geographical, spelling, history, music, and / or game question; the question is a multiple-choice question; the question calls for a narrative answer, and / or the question calls for a written answer.

[0054] In various embodiments, Al System 110 is configured to facilitate "multi-chat" interactions. These interactions can include, for example, just two or more Als, an Al and two or more other entities, an Al and two or more humans, multiple Als and multiple humans, a human and two or more AIS, or any combination thereof. Human participants are optionally represented by avatars (e.g., in a virtual environment) and may use Text Input 115 to provide input to the conversation. The conversation is optionally managed using AlSupervision Logic 165 as described elsewhere herein.

[0055] In a conversation, not everything said (or otherwise contributed) need be treated as a prompt. For example, in an interaction involving three or more entities, an Al need not respond to every contribution to the conversation made by one of the other parties. In fact, it may be inappropriate for the Al to treat every statement (or other contribution) made by the other parties as a prompt. A conventional system, such as ChatGPT from OpenAI, would be inappropriate in a multi-party interaction. The Al system (e.g., Al System 100) must decide when to respond or not respond to a particular prompt. There are two approaches to adapting an Al to a multi-party interaction. A first approach is to train the Al on multiparty conversations specifically. In this case, the decision of whether or not to respond to a particular contribution to the conversation is built into the Al. In this case, Al Logic 135 may be configured to provide an empty "NUL" response. A second approach is to use a supervisory layer (e.g., Al Supervisor Logic 210) between Al Loic 135 and the conversation. In this case, the Al might generate a response for each statement contributed to the conversation by other parties, but Al Supervisor Logic 310 is used to determine whether or not the generated response should be added to the conversation. Systems configured for multi chat optionally include assignment logic configured to assign contributions to the interaction (e.g., conversation) to specific entities. For example, assignment logic may be used to determine who made a particular statement. This assignment logic may be included in Image Processing Logic 115 and / or Text Processing Logic 125.

[0056] More than one participant in a multi-party interchange may be an Al. for example, one or more one participant may be an Al in a multi-party text, verbal, video, and / or audio interaction. Use cases include having a debate between two different Al as moderated by a person. Having Ais represent fans of two different sports teams or other competitors during a competition, an Al moderated discussion, logic configured to moderate an interaction including one or more Al, and / or the like. In a specific example, a multi chat conversation can occur between two Als while one or more humans observe or monitor the conversation.

[0057] FIG. 2 illustrates a Multichat System 200 according to various embodiments of the invention. Multi-chat System 200 is typically integrated with Al system 100. Multi-chat System 200 is configured to contribute to a Chat Environment 220 that may also be connected to one or more human participants and / or any othertype of participant (e.g., human, Al, supervised Al, or other entity). Multi-chat System 200 includes Al supervisorlogic 210 configured to supervise the contribution of Als to Chat Environment 220. Al Supervisor Logic 210 is optionally integrated within one or more of the Als (e.g., Al System 110 or Al Logic 135) and / or the Chat Environment 220. Chat Environment 220 and / or Supervisor Logic 210 optionally include assignment logic (not shown) configured to assign elements of the conversation as having been contributed by specific entities. The assignment logic may be included in Image Processing Logic 115 and / or Text Processing Logic 125. Chat Environment 220 and / or Supervisor Logic 210 are optionally included in Al System 100.

[0058] Supervisor Logic 210 may include logic configured to access two (or more) different Al APIs at the same time, and to present responses from these Ais as part of a serialized interaction. In some embodiments, Supervisor Logic 210 is further configured to supervise contributions from one or more human sources (e.g., users or avatars). For example, Supervisor Logic 210 may be configured to allow a contribution from a human entity only when that contribution is appropriate, useful, constructive and or otherwise beneficial to the conversation. Supervisor Logic 210 is optionally configured to prevent a particular person from dominating a conversation. Supervisor Logic 210 is optionally configured to supervise contributions from a source of unknown type. For example, from a source that may be human or Al or some other device (e.g., a sensor, a vehicle or loT system). The Chat Environment 220 can include a messaging system, communication features in a virtual environment (e.g., a video game or a metaverse), a social network, and / or the like.Multichat System 200 can include multiple instances of Al System 100 and / or Al Logic 135.

[0059] One example of the use of multi chat system 200 includes a virtual environment, such as a video game or a metaverse, that includes multiple human avatars within a social Chat Environment 220. The social chat environment could include a club, a bar, a restaurant, a school, a meeting room, a store, a meeting place, etcetera. In a specific example a metaverse may include a bar that avatars can visit. The bar includes a bartender and a waitress each represented by an AL The avatars can interact with each other and / or the characters represented by the Al's. Supervisor Logic 210 is configured to control contributions from the Als to this interaction. For example, the Al represented by the bartender may contribute when one of the avatars orders a drink but let the avatars talk between themselves when interaction or contribution from the bartender is not necessary. The contribution by the bartender may be text, audio, and / or some action, e.g., making theordered drink and giving to the requestor. This is an example of a contribution to an interaction being something other than video, audio or text. Examples of elements of the interaction that the bartender may respond to include: "what kind of beers do you have?," " I would like a glass of wine", do you know what time the game is on," or "has Judy stopped by today?." The Al Supervisor Logic 210 that controls the contributions of the waitress and bartenders may be configured to manage occasional background conversations between the waitress and bartender and / or to spontaneously contribute to conversations of other entities within the Chat Environment 220.

[0060] A special case of multi chat includes two or more Al's having a conversation with each other. This conversation may be initiated by a human provided prompt and the Als may be configured with particular characteristics. For example, one Al may be configured to represent George Washington and another Al may be configured to represent Genghis Khan. These "personalities" may be designated by a human user using an interface to a chat environment including logic configured to support such an interaction. The human user may also designate initial prompts and / or the subject of the conversation between the two or more Als. In a specific example, the human may instruct the two Als, having the above personalities, to take opposing sides in a debate about World Trade. The resulting conversation between the Als may then take place without further human intervention or may take place under further control of the human. The resulting conversation may be saved and / or streamed to the human and / or third parties. Optionally, once the conversation between the two A's has begun the chat environment is configured for the human to alter or rewind contributions contributed by each of the Als. For example, if the human notices an inappropriate or improper statement contributed by one of the AIS, the human may step the conversation back to a previous state and allow it to restart from that point. The human may also, in some environments, add their own prompts to the interaction after it has begun.

[0061] In some embodiments Multichat System 200 is configured to generate a conversation between Als, the system comprising a Chat Environment 220 within a virtual environment or a video game. The Chat Environment 220 and / or Al Supervisor Logic 310 include a first interface configured to communicate between the chat environment and a first Al; a second interface configured to communicate between the chat environment and a second Al, wherein the first Al and the second Al are each generative Als configured toprovide a response to a prompt and the chat environment is configured to combine the prompts and responses into a conversation between the first Al and the second Al; and a user interface configured to provide the conversation to one or more human user. The first and second interfaces may include Image Inpu61 110 and / or Text Input 120. The user interface is optionally configured for the human user to initiate the conversation between the first Al and the second Al by providing one or more prompts. For example, the human user may provide an initial conversation to start a conversation. Optionally, the user interface is further configured for the human user to provide personality characteristics to the first they are and the second Al, the personality characteristics optionally including an audio voice, a writing style, characteristics of a living or historical person, a specific point of view, an aggressive or passive personality type, etc. The first Al and the second Al are optionally different instances of the same Al accessed through separate sessions. The conversation may be presented a text, audio, and / or video format. Multichat System 200 is optionally configured to support a conversation between three or more Al's, and / or between two Als and one or more human participants.

[0062] Furthermore, Chat Environment 220 and / or Supervisor Logic 210 are optionally configured to receive serial inputs from two different sources and to respond to these inputs based on their source. Specifically, in a three (or more)-way conversation one participant is drawn from a first Al via a first API and a second participant is drawn from a second Al via a second API. Optionally, one or more of the Al's may specifically be configured to receive a series of inputs and decern which or two sources each element in the series comes from, and to generate a response based on the decerned sources. For example, the Al may receive a conversation:Harry: My wand is broken.Ron: I like chocolate.Harry: this is important, we are going to die.Ron: chocolate is important too.

[0063] The source of each statement (Ron or Harry) is important to understanding the meaning of the conversation. The Al is optionally placed in a "conversation mode" in which it is configured to look for sources of specific inputs. These sources may be labeled by a name (as shown in the above example), by an IP address, by a MAC address, by a computer / network address, by an in-text label, by a font, by a voice print, by recognition ofa character / person in a video, by an avatar / user name, and / or the like.

[0064] In a specific example, an Al is configured to receive one or more different video streams, to identify characters in each of these video streams and to assign audio / actions of the identified characters as coming from different participants in an interaction. For example, the Al may be configured to receive a video / audio track in which two characters are speaking and based on the actions of the characters, facial movements, or voice identification, to assign the audio (and / or text generated therefrom) to the specific characters. A response from the Al can then be based, in part, on these assignments. The response optionally includes an avatar / avatar command that may be added to the video, optionally in real-time.

[0065] In some embodiments, the tracking of characters, the conversion of audio / video to text, and / or the assignment of audio / actions to a specific character is permitted by logic external to the Al. In this case, Al may only need to be configured to receive the interaction in a text form with different participants being assigned to different text within the text sequence.

[0066] In a conversation including 3 or more entities, each entity may take turns contributing or may the entities, may randomly contribute or one entity may contribute more than another entity. The Al system needs to know when and when not to contribute a response to the conversation. For example, the Al system need not respond to every prompt (e.g., conversation statement) by the other entities. In various embodiments, the Al may is configured to respond to questions directed at the Al, not to respond to questions directed at other entities / parties to the conversation, to score its available responses responsive to the flow of the conversation, to provide (or not) a response based on this score; the Al may be set to aggressive or less aggressive (passive) modes (e.g., set the Al to talk a lot or less); measure a time delay in which the conversation is quite and increase the likelihood that the Al will respond as time goes on; detect pauses in the conversation; and / or the like. In some embodiments the Al may be configured to detect the sources of each statement in a conversation. For example, in a 3D virtual environment or in a video or in a game, different sources may make statements (e.g., a person or avatar may speak), the response (contribution to the conversation) from the Al is optionally dependent on the sources of prior statements. It matters who says something, not just what was said.

[0067] Assuming a three-way text conversation between Bria, Sabrina and Simone. Bria isan Al system, and Sabrina and Simone may be Al and / or human. Example conversation: Simone: Good morning Sabrina, how are you?(here Bria will choose not to respond because the answer logic determines that it is more appropriate for Sabrina to respond)Sabrina: Good, what would you like for breakfast?(Again, at this point in the conversation the answer logic will conclude that it is best for Simone to respond, even though Bria may have a potential response, it is give low value to this point in the conversation. However, Bria may be configured to provide a response after a delay if Simone does not answer. Such a response may include, for example, the avocado should be eaten soon.)Simone: I would like fried eggs.Bria: the refrigerator inventory shows that there are no more eggs left.(Here the answer logic has determined that it has a high value response and this is a good time to add it to the conversation.)

[0068] Al systems can be programmed to participate in group conversations by having their algorithms observe the subtle nuances of human language, such as detecting the topic of the conversation and responding accordingly. Depending on the type of Al system, the machine can use natural language processing (NLP) to detect the context of a conversation, identify keywords, and provide relevant responses. Some Al systems are even able to learn from conversations and recognize patterns in order to give more appropriate answers. Furthermore, Al can use sentiment analysis to gauge the tone of a conversation and automatically adjust its responses based on the speaker's emotion. Finally, Al can employ techniques from machine learning to generate better and more natural-sounding conversations.

[0069] Some embodiments include multi-AI contribution need not be restricted to conversations. For example, two or more independent Als may be configured to contribute to a work of art, a mathematical / engineering / scientific problem, a business problem. In a specific example, a first Al may be configured to generate an outline for a novel while a second Al may be configured to fill in the outline, a fist Al may be configured to compose a work of art while a second Al may be configured to sculpt brush strokes or chisel strokes; a first Al may be configured to design a software / hardware application while a second Al may be configured to compose code specific to the designed application, a first Al may beconfigured to generate dialog, while a second Al is configured to generate a plot or description within which the dialog occurs, an Al may be configured go generate an image of one or more person while a second Al is configured to generate facial expressions, of the one or more person, One Al may be configured to control interactions between avatars in a meta space, one avatar may be configured to control actions of an specific Avatar (of the avatars), and / or while a third Al is configured to generate 3D motions of that avatar, etc.

[0070] Some embodiments include a user / application specific grammar checker based on a type of document, for example a patent application may have a different grammar than a romance novel, (or not.)

[0071] Some embodiments of the current invention include an "environment processing system" that processes an entire 3D / metaverse system.

[0072] Some things done differently by a multi-chat Al (e.g. embodiments of the systems illustrated in FIG. 1 and 2.) relative to a conventual system include:1. Considers when to respond or not to respond to a prompt, may not respond to a prompt.2. Considers the source of prompts. E.g., did entity A or B provide the prompt?3. Recognize a rhetorical question.4. May generate a response but then decide not to deliver it.5. Rank and or generate responses based on contribution to a conversation not just the latest prompt.6. Rank possible responses differently if in a conversation mode.7. Switch between a conversation mode and a non-conversation mode.8. Have logic configured to detect the subject and our topic of a conversation.9. Change the subject and / or topic of a conversation intentionally.10. Mediate between other parties in the conversation.11. Train specifically for any one or a combination of the above capabilities.12. Multichat Al Considerations as to when to respond:13. Value of a response to the conversation, may be measured by rank, score, conversational balance, etc.14. Time delay since the last contribution to the conversation.15. Request for response directed to a party other than the generative Al. For example, the question "where did you buy those shoes" is less likely to be directed at the Althan a human in the conversation.16. Information or knowledge specifically available to particular parties in the conversation, e.g., the Al main know the exact time or may know the score of a football came two years ago. In contrast another party may have more knowledge about what is for dinner or "what game would you like to play."17. Entry of a new entity into the conversation, for example a new entity entering a metaverse space, a new participant in a text chat, or the detection of a new voice in audio.18. Distance between entities. For example, a statement is more likely to be directed at a nearby entity relative to an entity that is a far distance away in a virtual or real- world space.19. Taking turns among entities to provide input to the conversation, e.g., to achieve conversational balance.20. The type of prompt, for example, was the prompt in the form of text, audio, or an event?

[0073] An interaction / conversation can include two, three, four or more entities, and can include entities that are human, and artificial intelligence, and or a non-intelligent signal source. The following is an example of a conversation including a human, a generative Al, and a signal source:Signal source: (provides an image)Al: "Lincoln, I have analyzed this image and am concerned about the temperature of the pipe in the lower left corner. I have highlighted it with a circle."Abraham Lincoln: "is that the coolant return height?"Al: "yes, it should be at approximately 110 degrees centigrade. It appears to be approximately 200 degrees centigrade according to the infrared image provided by the local security camera.Abraham Lincoln: "Please provide a set of additional images from different angles." Signal source: (provide the requested set of images)Al: "Based on the additional images, it appears that the only image that indicates the pipe is too hot is taken with the sun directly behind the pipe."Abraham Lincoln: "store incident, record additional images on next security sweep." Al: "confirmed incident stored. Additional image request transmitted."Note that contributions from the signal source entity may be triggered by a request generated by the Al and sent to the signal source without inclusion in the conversation.

[0074] Various embodiments of the systems illustrated in FIGs 1 and 2 are configured to generate personalized chatbots. Specifically, various embodiments of the invention include Personalization Logic 170 configured for a user to upload their own content and to train the Al on that content. For example, one could upload all of one's e-mail to create a chatbot specifically trained to mimic a person's e-mail. Personalization Logic 170 may be configured to train Answer Logic 130 to modify an answer, or to train a supervisor layer between Al Logic 135 and other parts of Al System 100, and / or to train Al Logic directly. In another example, one could upload all USPTO patents to train a chatbot as a patent drafter.

[0075] Personalization of just style is optionally achieved in various embodiments. These embodiments typically include a style layer (e.g., Al Supervisor Logic 210 or Personalization Logic 170) on top of a generalized chatbot. Again, one could train the style layer based on one's own writings. One could train more than one style. One for e-mail, one for general writing, one for patent drafting, one for Office Action Responses. For example, an embodiment of Answer Logic 140 trained thus would receive responses from the generalized chatbot (Al Logic 135) and modify the responses to match a selected style.Elements of style that may be customized include sentence length and structure, vocabular, words used, punctuation, paragraph length, spelling, numbering, fonts, use of emojis, grammar, writing formality, humor, use of headings, outline style, bullet and numbering formatting, and / or the like.

[0076] Personalization can include: a "tone" selection input, a "sentence structure" selection input; a "style matching" selection input, and / or a "format" selection input.

[0077] An authoring tools can include a word processing addon and may be configured to Automate processes of: generating or receiving an outline, manipulating the outline, generating first text from the outline using GTP, and providing a set of tools configured to automate refinement of the outline and resulting document.

[0078] A content drafting system configured for personalization of Al output may comprise: user interface logic configured generate a user interface, the user interface (e.g., Text Input 120) being configured for a user to provide prompts; a trained Al based on a GPT model and configured to provide responses to the prompts or an interface to said trained Al; style logicconfigured to modify the provided responses to match a desired style and to provide the modified responses to the user; and optional style training logic configured to train the style logic based on training data provided by the user. Style logic and style training logic are optionally included in Personalization Logic 170.

[0079] In various embodiments, Text Input 120 is optionally configured for the user to select the desired style from among a plurality of alternative styles. These embodiments may further comprising data selection logic configured to determine which of the training data provided by the user should be used by the training logic to train the style logic. The style logic is optionally trained using text provided by the user, the training data optionally including text messages, documents, e-mail, websites, poetry, lyrics, audio a voice, images, a virtual environment, and / or presentation slides. The style logic is optionally configured to modify the responses with respect to any combination of: sentence length and structure, vocabular, words used, punctuation, paragraph length, spelling, numbering, fonts, use of emojis, grammar, writing formality, humor, use of headings, outline style, and / or bullet and numbering formatting. The style logic may be configured to modify the responses with respect to any combination of: image style, color content, background environment, avatar characteristics, motion type, voice sound, background sound, volume, and / or music style. The provided responses include text, audio, images, and / or video.

[0080] The style logic is configured to modify the provided responses to match a style of an existing document, audio, image and / or video.

[0081] The style logic is optionally configured to modify a response by modifying a prompt used to generate the response, configured to Modify a file type of a response you can, and / orthe file type optionally including PowerPoint presentation, Word document or excel file, HTML or other presentation word processing or spreadsheet types.

[0082] The style logic is optionally configured to modify a style of a first response received from the trained Al to match a style of a second response received from the drained AL

[0083] The system of any one of the preceding claims, wherein the style logic is configured to select a sentence structure, grammatical structure, paragraph style, and / or language. The style logic is optionally configured to modify style of a response in order to achieve stylistic conformity between two parts of a content of a document. The style logic is optionally configured to modify a response to match a specific person's voice or a voice having specific characteristics. The s style logic is optionally configured to modify a responseto imitate a style of a specific author.

[0084] The style training logic is configured to receive a set of emails from the user and to train the style logic based on the received emails and / or the style training logic is configured to determine which of the training data to use to train the style logic based on criteria selected by the user.

[0085] Various embodiments of the systems illustrated in FIGs 1 and 2 are configured to provide an Al Supervised Search optionally configured to be used in combination with an indexed search system. Generative systems based on large language models are typically configured for generating text based on a prompt. While these systems may be trained on very large datasets, such training does not necessarily lead to a good search system. However, generative Al does have a place in search systems. This place is in the development of search queries and / or the processing of search results.

[0086] Va rious embodiments of the invention include a search system that makes use of both an Al model and an indexed search model. For example, an Al based on a generative large language model, e.g., GPT, may be used in conjunction with a search system comprising and indexing of Internet content, e.g., Google's current search system. The Al acts as an interface or middle layer between a user and the indexed search system.

[0087] The Al (e.g., Al Logic 135) may be configured to 1) generate, modify or filter queries sent to the index system, and / or 2) to sort, filter or moderate responses received from the index system. The Al supervises communication between the user and the indexed search system.

[0088] Specific examples of what the Al may be configured to do include:A) Modifying a query received from the user in order to generate one or more alternative queries configured to retrieve different and perhaps improved results. For example, if a user provides the search terms "mermaid swimsuit," then the Al may suggest one or more of Mermaid tail swimsuit, Mermaid bikini, Mermaid swimwear, Fish tail swimsuit, Fantasy swimsuit, Mythical creature swimsuit, etc. These search terms may then automatically be provided to the indexed search system in addition to or as an alternative to the search terms provided by the user. The expansion or modification of search terms may provide a variety of advantages. For example, the Al may be configured to substitute terms that will lead to a better result.Example, the Al learns that results generated using "mermaid tails swimsuit" are more likely to be clicked on then results generated using just "mermaid swimsuit." The Al can learn this by using both search terms in two separate queries, then combining the results to present to the user, and then seeing which results are more likely to be clicked on.B) Modifying and / or combining results received from the indexed search system. For example, the Al may remove results that are to the most part duplicates of other results from the same query or from a prior query. (Removal of results meaning that these results are not presented to the user, even if received from the indexed search system.)Example, if a first search is made on an indexed system using "mermaid tail swimsuit" and a second search is made on the indexed system using "fishtail swimsuit", then two different search results are returned. A trained generative Al may be used to combine, sort, filter, or otherwise manipulate these results to produce a preferred set of results for presentation to a user.

[0089] In either the manipulation of queries or their management of search results, a generative Al is also capable of memory capabilities. For example, the Al may detect a theme in a series of queries provided by a user and use the entire series as an input to generate suggested improved queries. Likewise, the Al may detect duplicates in multiple sets of search results and reorganize these sets to remove duplicates, to prioritize results that arise in more than one of the sets, to prioritize results based on not just one but several of the queries, allow further searches within a previously generated search result, and / or the like.

[0090] Va rious embodiments of the embodiments illustrated in FIG.s 1 and 2 are configured to combine both generative Al and an indexed search system that is not limited to use of the Al in a layer between a user and the indexed search system. Specifically, the Al may be used at various layers within the index search system. In an illustrative example, the index search system may receive a query "mermaid tails swimsuit." The first token in this string, "mermaid," may then be used in an initial query on the indexed data. At this point, the Al can be used to seek alternatives for "tails" and "swimsuit". For example, the Al may suggest search terms "tails" and "costume." More generally, the combination of generative Al and searching an index may be applied in a wide variety of approaches, including use of the Albetween various levels of indexing, use of the Al to select optimum index and or search terms, and or use of the Al to process index search results at one or more levels of a search index.

[0091] Various embodiments of the embodiments illustrated in FIG.s 1 and 2 are configured to perform a method of generating a conversation, the method comprising: Establishing a connection to a first Al and establishing a connection to a second Al using, for example using Al Interface Logic 130; optionally assigning personal characteristics to the first Al and the second Al; providing a first prompt to the first Al, optionally using Image Processing Logic 115 and / or Text Processing Logic 125; receiving a first response to the first prompt from the first Al, optionally using Answer Logic 140; providing the first response to the second Al as a second prompt; receiving a second response to the second prompt from the second Al; providing the second response 2 the first Al has a third prompt; repeating the process of providing a response from one of the first and second Al to the other of the first and second Al as a new prompt to generate a conversation between the first Al and the second Al; and providing the generated conversation to a human user.

[0092] Various embodiments of the embodiments illustrated in FIG.s 1 and 2 are configured to perform a method of generating a conversation between three entities, the method comprising: establishing communication channels from a chat environment to the three entities, wherein at least a first of the three entities is an Al; receiving contributions to the conversation from a first and second of the three entities; determining whether or not to contribute an Al response from the first of the three entities to the conversation, the response from the first of the three entities being a response to the contributions from the third and / or the second of the three entities; and adding the Al response to the conversation.

[0093] The method of any one of the above claims, further comprising rewinding the conversation to a selected prompt and restarting the conversation from the selected prompt. The first Al and the second Al are optionally different instances of the same AL

[0094] The above methods optionally include one or more of: editing one of the responses received from the first Al or the second Al; generating the conversation in a chat environment including a messaging application or a virtual environment; determining (e.g., using Al Supervisor Logic 210) whether or not to contribute and a response is performed within the Al (e.g., Al System 100 and / or Al Supervisor Logic 210); and streaming theconversation to one or more third parties.

[0095] The chat environment optionally includes a messaging application, and audio application, a virtual environment, a social network, a point-of-sale system, an ordering system, a transportation device (e.g., vehicle), a game environment, a classroom, a meeting place, and / or the like.

[0096] Al Supervisor Logic 210 is optionally configured to score a candidate response from the Al, the score being based on a predicted value of the response to the conversation.

[0097] The method of any one of the above claims, wherein the Al Logic 135 and / or Al Supervisor Logic 210 is configured to recognize a rhetorical question, is configured to recognize a question directed toward one of the other entities in the conversation, and / or is configured to recognize a question directed at the AL The Al is optionally represented by a non-player character in a game or virtual environment.

[0098] In various embodiments Al System 100 is configured to analyze text, audio, video or a virtual environment to determine a source of an input (e.g., an input sequence of audio and / ortext) received by Image Input 110 and / or Text Input 120, the system including: an trained artificial intelligence system or an input / output configured to communicate with a trained artificial intelligence system; an input configured to receive an input sequence including the text, audio, video and / or virtual environment; assignment logic configured to assign elements of the input sequence to one or more entities (e.g., sources) within the input sequence; (for example, which avatar said that or performed the action, etc.); prompt logic configured to provide the input sequence and the assignment of elements to the artificial intelligence system; output configured to provide an output of the artificial intelligence to a user, the output being based on the input sequence and the assignment; and a microprocessor configured to execute at least the assignment logic. Optionally the input sequence includes a series of text messages, and the assignment logic is configured to assign each of the text messages to corresponding a member of priority of entities who contributed the text messages to the input sequence.

[0099] The i nput sequence may include a series of audio segments and the assignment logic is configured to assign each of the audio segments to a corresponding member of a priority of entities who contributed the audio segments to the input sequence. The assignment of audio segments is optionally performed based on source location and / or the characteristics of an entity's (e.g., person's) voice. The input sequence may include a video and theassignment logic is configured to assign each audio segment within the video to a corresponding entity, wherein the corresponding entity may or may not be visible within the video at a time the audio segment is produced, wherein the assignment may be based on characteristics of an entity's voice, a location of the entity within the video, and / or movement of an entities (e.g., movement of their mouth, gesture or other action). The input sequence may include text and / or audio from a virtual environment and the assignment logic is configured to assign each element of the input sequence to a corresponding source within the virtual environment, wherein sources within the virtual environment optionally include avatars or background sources. Background sources can include, for example, a virtual radio within the virtual environment or a sound coming from a virtual audio speaker.)

[0100] In some embodiment assignment logic is configured to assign text messages or elements within an interaction to entities based on a metadata tag, the metadata tag optionally including a username, a telephone number, an avatar name, and / or a face recognition result. In some embodiments, the assignments are made to objects (e.g., virtual devices, NPCs or Avatars) in a virtual environment.

[0101] Various embodiments of Al system 100 are configured to generate a response; the system comprising: an input configured to receive data including a set of prompts; an optional parser configured to identify prompts within the received data; Al interface logic configured to provide each of the prompts to two or more artificial intelligence system (Al systems); Answer logic configured to receive a separate response from the two or more artificial intelligence system for each of the two or more prompts; Al supervision logic configured to determine which of the separate responses to include in an interaction between two or more parties; optional script logic 150 configured to identify commands within the data and to execute the identified commands; and optional response display logic configured to display the determined separate responses to a user and / or the one or more of the Al systems. The system is optionally configured to manage an interaction between a person and an Al and a party which may or may not be an Al. Where the system is optionally configured to manage an interaction between two or more humans and at least one Al. Wherein the system is configured to manage an interaction between at least one person and at least two or more Al.

[0102] Various embodiments of Al system 100 are configured to generate aresponse the system comprising: an input configured to receive data including a set of prompts, the data may include an image, audio and / or text; an optional parser configured to identify prompts within the received data, wherein the identified prompts are optionally from two or more sources and identification of the prompts includes assigning each prompt to one of the two or more sources; (the prompts are optionally part of a conversation between the two or more sources. The two or more sources could be humans, Ais or any combination thereof. Their form (human or Al) may not be known.) an artificial intelligence system (Al system) configured to provide a response based on a received prompt; Answer logic configured to determine whether or not to provide the response to the sources based on a value of the response to the conversation; Optional Al supervision logic configured to determine which of more than one alternative responses to include in an interaction between two or more parties; optional script logic 150 configured to identify commands within the data and to execute the identified commands; and optional response display logic configured to display the determined separate responses to a user and / or the one or more of the Al systems. The system is optionally configured to manage an interaction between a person and an Al and a party which may or may not be an Al. Where the system is optionally configured to manage an interaction between two or more humans and at least one Al. The system is optionally configured to manage an interaction between at least one person and at least two or more Al.

[0103] Various embodiments of Al system 100 are configured for automated generating of text comprising: a text input 120 configured to receive text, the text including a series (one or more) of prompts, (e.g., an outline); text processing logic 125 configured to identify each of the prompts within the text; Al interface logic 130 configured to provide the each of the prompts to an artificial intelligence system; answer logic 140 configured to receive a plurality of responses to the prompts an from the artificial intelligence system; and answer display logic 145 configured to display the responses to a user [or storage]; optional script logic 150 configured to identify commands within the text and to execute the identified commands; an optionally command input configured for user to provide command for execution on the plurality of responses; and wherein at least the image processing logic or the answer display logic are configured to be executed by a digital processor 195.

[0104] In various embodiments, the two or more prompts are optionally part ofoutline, the input is configured to receive that data as a text document or an image, and / or the parser is configured to identify levels and sub-levels of an outline. The commands are configured for: Maintaining antecedent basis between response, Manage introduction of characters or other elements in a narrative, Changing or controlling order of prompts, Determining if a condition is met, e.g., by analyzing a response to a prompt or evaluating a variable, Conditional branching within a script, (selecting between alternatives, repeating segments, conditional IF statements), Insertion of text or removal of text from within a response received from the artificial intelligence, Detection and removal of repeated ideas and / or text, Altering or matching of style, Rewriting of transitions between text generated from different prompts, and / or Consistency checking.

[0105] Various embodiments of Al system 100 comprises: a text input 120 configured to receive queries from a user; a generative Al; an index-based search system configured to receive input queries and to provide sets of response content in response to the received queries; wherein the generative Al is configured to modify the queries received from the user and provide the modified queries to the index-based search system as the input queries, and / or the generative Al is configured to manage the sets of response contact prior to presenting the response contract to the user; and a microprocessor configured to execute at least the generative Al or the index based search system.

[0106] Optionally, the generative Al is configured to modify a query received from the user to generate one or more alternative queries to retrieve different and or improved search results; the generative Al is configured to generate a set of alternative queries based on a query received from the user, and two present the set of alternative queries to the user and / or to provide the set of alternative queries to the index based search system; the generative Al is configured to modify a query received from the user to generate one or more alternative queries based on prior queries received from the user and / or based on which search results the user selects for viewing; the generative Al is configured to combine, sort, and / or filter the results of more than one query received from the index page search system; and / or the generative Al is configured to operate on a query received from the user at an intermediate index level of the index based search system.

[0107] Various embodiments of the embodiments illustrated in FIG.s 1 and 2 are configured to support methods of generating content using an outline, a method of controlling a style of a response, a method of answering questions, a method of including anartificial intelligence in an interaction including more than two entities, the entities including at least two Als, a method of including an artificial intelligence in an interaction including more than two entities, the entities including at least one Al, a method of automated response provision based on inputs from a virality of entities, and / or a method of generating content based on prompts and commands.

[0108] Further Disclosure of conversations between Als as may be implemented using the systems illustrated in FIGs. 1 and 2:

[0109] A user optionally provides Al characteristics, such as a tone of voice, speaker identity (e.g., speak as George Washington), and / or interaction type. The interaction type can include restrictions on conversation direction, an age-appropriate filter, bias elimination, lists of preferred or allowed subtopics, etc.

[0110] The assignment of Al characteristics can include assignment of roles to be used in a conversation. For example, one Al may be asked to represent an interviewer while a second is asked to be an interviewee. An interviewing Al may ask questions of a panel of interviewees each represented by a different Al.

[0111] In another example, one Al may be assigned a role as a judge, while second and third Als are assigned roles as attorneys or witnesses, etc.

[0112] The different Als may be different instances of the same Al or different Al systems (e.g., an Al from Google and an Al from OpenAI).

[0113] In a typical example a conversation is produced by the following method: [Single user] The user optionally assigns roles to one, two, three or more different Als. The user provides an initial prompt. The initial prompt is provided to a first Al. The first Al provides a first response to the initial prompt. The first response is optionally provided to the user. The first response is provided to a second Al as a second prompt. The second Al provides a second response to the second prompt. The second prompt is optionally provided to the user. The second prompt is provided to the first Al as a third prompt. The first Al provides a third response to the third prompt. The process of the first and second Als providing prompts to each other to produce further responses is repeated to produce a conversation.

[0114] Before each prompt is provided to the first or second Al, it is optionally modified to include a prefix and / or suffix. The prefix / suffix is configured to 1) keep the Al in character, 2) control the scope of a conversation, and / or provide the Al of memory of theconversation. Typically, the prefix / suffix is not shown to users as part of the conversation.

[0115] In an illustrative example a prompt may be supplemented with: Prefix: "Acting as an engineer, respond to the following. Avoid discussing manual transmissions. Your main focus should be a comparison of different vehicle transmission types." Acting as an engineer, respond to the following. History: (the last 2000 symbols included in the conversation.) Which is then followed by a current prompt. Suffix: "Switch to a British accent"

[0116] In this case "Act as an engineer" is derived from the Al characteristics assigned by a user to the Al receiving the prompt. The avoidance of manual transmissions may be a result of this subject already thoroughly being covered in the conversation. The main focus is a guide to the subject matter of the conversation, which may have been provided by a user when the conversation was initiated or during the conversation. The history provides the Al with what has recently been said.

[0117] The suffix may be sent to a voice to text conversion Al rather than the first or second Al.

[0118] In another example a conversation is managed by multiple users. In this case, each user may select the characteristics of an Al to which they are assigned. The conversation is then initiated by one of the Als using an agreed upon initial prompt.

[0119] Optionally, the conversation between the first and second Als is continued until a predetermined number of words have been generated in the responses.

[0120] Optionally, the conversation between the first and second Als is continued for a predetermined amount of time.

[0121] Optionally, the conversation between the first and second Als is continued until the user fails to indicate that they are reading / listening to the responses.

[0122] Optionally, the conversation between the first and second Als is continued until a budget is reached. The budget optionally being a function of a cost of generating the responses and / or a cost of converting the responses to audible data.

[0123] Optionally, further including providing the responses provided by the first and second Als are provided to a text to voice converter to generate audio response and the user receives the response in an audio format.

[0124] The above example may be performed with one, two, three or more Als. Or, with two or more Als and a human that contributes more than just the initial prompt.

[0125] In some embodiments, a first Al may provide responses and a second Al may automatically provide follow-up questions. Optionally, a user may select which of the follow-up questions to send to the first Al as the next prompt.

[0126] In some embodiments, a user may modify a prompt to be sent to the first or second Al during a conversation.

[0127] In some embodiments, a first user may modify the prompts sent to the first Al and a second Al may modify the prompts sent to the second Al.

[0128] The modification of prompts during a conversation may be limited by one or more pre-established rules. For example, a modification may be limited to a number of words (tokens) that can be changed, may be limited to occurring once every X (5th, 10th20thetc.) prompts, may only be allowed in response to a triggering event.

[0129] Examples of triggering events include, but are not limited to, specific words found in a response, a determination (by a person or Al) that an argument has been won, identification of an answer to a question or a solution to a problem, by a payment or giving of consideration, by a game event, .

[0130] In some embodiments a conversation occurs in a game environment. For example, a conversation may occur between two or more Al supported non-player characters (NPCs). In such an example, the conversation may be limited to one or more specific topics. For example, two NPCs located at a shooting range (or other location) in a video game may be restricted to subjects related to the location and / or to a human (represented by an avatar) within their location.

[0131] In some embodiments, an Al included in a conversation is configured to determine a winner of an argument.

[0132] In some embodiments, a conversation between Als may be paused dependent on presence of an avatar within a virtual or game environment.

[0133] Scope management:

[0134] In some instances, it is desirable to control and / or adjust the scope of a conversation. Such control may be applied to subject matter, topics, language, conversational tone, and / or the like. For example, it may be desirable to restrict a conversation to the subject of "car repair." To maintain a non-adversarial tone. To restrict the conversation to English and avoid erotic language. In other examples, scope control can be used to select language level (e.g., a 6 year old's vocabulary or a 30 year old'svocabulary), forbidden topics (e.g., how to perform violent acts), situational circumstances (e.g., a different discussion in a virtual bar relative to a virtual elementary school), location based topics (e.g., a car related topic in a virtual car dealer and a food related topic in a virtual restaurant), observer based topics (e.g., different topics dependent on the type / age / gender of a nearby avatar). For example, the control of a topic in a virtual environment may be dependent on whether an avatar representing a 10-year-old is nearby, or if a male or female avatar is nearby. In this example, conversational topic scope may automatically be changed as a result of movement of avatars and / or movement of an NPC representing the first or second Als.

[0135] Control of conversation scope may be managed by simple filtering, e.g., removing obscene words from a prompt / response. Control of scope may also be accomplished using a generative Al. This Al may be one of the Als in the conversation or an independent Al. In an illustrative example, the first Al generates a response to be provided to the second Al as a prompt. The prompt may be altered, prior to being provided to the second Al, to include "Respond to the following prompt with a focus on the subject of "car repair". Or the prompt may be altered, prior to being provided to the second Al, to include "Respond to the following prompt without reference to the things people may do in the back seat of a car."

[0136] In another example, the prompt may be processed by an independent Al to control conversation scope. In such embodiments, the prompt is provided to the independent Al along with instructions to modify the prompt as needed to control the scope. For example, a response / prompt generated by the first Al may be provided to the independent Al with instructions to "Modify this text to replace erotic language and generate a response appropriate for a child under 12 years old." The output of this request is then provided to the second Al as a prompt to continue the conversation with the desired scope adjustment. The output of the independent Al is typically not included as part of the conversation.

[0137] In some embodiments, scope management is controlled in real-time by human users. In such cases the management may be limited. For example, in a conversation in which the first and second Als are assigned to different human users, each of the human users may be limited in how or when they can alter the conversation. E.g., a user may only be allowed to influence the conversation every 10thor 50thexchange, only 4times during the conversation, and / or only by changing a fixed number of words in a prompt.

[0138] In an illustrative example, a conversation includes a debate between two humans represented by respective Als. During the debate each human is only allowed to alter a prompt made by their Al 10 times and each change can only include the change of 5 words (tokens) with the specific prompt.

[0139] External injection of conversation content:

[0140] In some embodiments a conversation between two or more Als may be interrupted by an input that is external to a conversation. For example, a human or avatar representing a human may provide input to the conversation. Such input can include: "let's talk about housing prices," "your statement 'x' is based on incorrect facts, continue your conversation with this information," "assume electric cars are better than bicycles," "please explain 'x' further," and / or "end this conversation."

[0141] The first or second Al, or an independent Al controlling conversation scope, may be responsive to such external input and be configured to adapt the conversation accordingly.

[0142] Such input can occur in a virtual environment or via a user interface to the conversation.

[0143] Optionally, input to a conversation may be an event. For example, a conversation occurring in a virtual environment may be interrupted by an event therein. Such events may include a game play event, arrival or departure of an entity from the environment, a bull walking through a fine China shop, a financial transaction, collapse of a building, and / or the like. In a specific example, if the NPC representing the first Al is hit by a brick in the virtual environment / game environment, that event may result in a change in the topic or scope of a conversation in which the first Al is contributing.

[0144] Automated podcasts:

[0145] Some embodiments include systems and methods of generating automated podcasts. Such embodiments typically include a user interface in which the user can select characteristics of one or more Al participants, topics for discussion, tone, etc. A user can then select an input to initiate a conversation to be included in the podcast. The conversation may or may not include human participants. For example, in one embodiment, a first Al is designated as an interviewer and a second Al is designated as aninterviewee with expertise on a particular subject. In another embodiment, a podcast includes a human interviewer and a panel of avatars representing two or more Als, each having slightly different characteristics.

[0146] Optionally the subject matter for a regularly scheduled podcast is selected by listener voting. The selection of podcast content may also be automatically selected based on demand, news events, or specific articles. For example, an automated podcast may be generated on "news events of the day" or on a specific article about generative Al.

[0147] Image generation:

[0148] In some embodiments the characteristics assigned an Al include an Al generated image. For example, the first Al may be represented by an NPC avatar appearing to be an elderly male professor. In such embodiments, the avatar may be made to move (e.g., mouth movements) to match the words of the conversation. Characteristics of the Al may include their audible voice and voice characteristics. So, for the male professor, as "serious male voice" may be assigned.

[0149] Playback devices:

[0150] Some embodiments include logic (e.g., an app) configured to display participants in a conversation on multiple devices. For example, an avatar representing the first Al may be displayed on a first smartphone and an avatar representing the second Al may be displayed on a second smartphone. The smartphones then appear to be having a conversation between each other.

[0151] Sequence prompts:

[0152] In some embodiments it is possible to generate material using the first Al based on a sequence of steps. These steps may be provided as a single sequence prompt. For example, a sequence prompt may include the following steps: 1. Come up with a title for an essay about guitars; 2. Find the sources for the essay; 3. Write a 10 point outline for the essay; 4. Write the point 1; 5. Write the point 2; and 6. Write the point 3, etc.

[0153] This single (multi-step) prompt is then provided to an Al as a sequence and automatically executed. The step 1 is first provided and a title is returned. In step 2 sources for the essay are requested from the Al. This request typically includes the title and / or subject. In step 3 the outline is generated in response to the subject, title, and / or sources. Subsequent prompts are then used to generate each point of the outline.

[0154] The sequence may be performed automatically or under control of the user.Some embodiments include a user interface configured for a user to designate the steps in a sequence, e.g., add steps, change order or include multiple levels of outline. (See figure below.)

[0155] A system may include logic configured to perform any of the steps disclosed above in any of the Multichat examples.

[0156] Storage and retrieval of prompts

[0157] In various embodiments, the user may store prompts and / or responses using interface logic. Storage may (user selectively) be on the user's device or on a remote server. Stored material is optionally retrieved for use as a new prompt or to be shared with third parties. Memory on the user's device and / or a remote device may be configured for such storage.

[0158] In various embodiments, a user may prompts and / or responses using standard smartphone share features.

[0159] Sharing of private prompts optionally in a prompt marketplace

[0160] In various embodiments, logic is configured for sharing prompts, including user generated prompts. Such sharing optionally occurs within a marketplace configured for trading and / or sharing of prompts. Such a marketplace may be facilitated by marketplace logic.

[0161] Optionally marketplace logic is configured for trading prompts while keeping the traded prompts confidential. Specifically, prompts may be exchanged and / or shared in a way that prevents parties receiving the prompts from copying and / or duplicating the prompts.

[0162] The provider of a prompt may make the prompt publicly available (disclosing the entire contents thereof) and / or available for use without consideration.

[0163] User interface logic is optionally configured for a user to select between sharing a prompt, a response or both.

[0164] Optionally, prompt and / or responses may be submitted by users to a "best of" list, in more or more categories. Other users may then vote up or down the submitted content.

[0165] Prompt confidentiality can be achieved in the following method:1) A first user writes a first prompt.2) The first user uploads the first prompt to a prompt marketplace.3) The first user optionally provides one or more search terms to be associated with the first prompt, search terms optionally include the source of the first prompt, e.g., that the first prompt is from the account of a well-known influencer or that the first prompt is meant to be humors.4) The first user optionally provides distribution terms to be associated with the first prompt, distribution terms may include permission to see and / or modify, purchase price, rental price, rental duration, number of available instances of the first prompt for sale or rental, pay-per-use, and / or the like. Optionally, the first prompt may be free to use. Optionally, the first user can designate that the prompt not be confidential and / or may be used on an unlimited basis.Optionally, the first user may designate that the price of using the first prompt increase or decrease with time and / or popularity. Optionally, the first user may lock distribution terms for the first prompt such that they cannot be changed, thus, assuring a purchaser that the prompt they paid for will not later become free or available at a lower cost from the creator.5) A second user accesses the first prompt marketplace and identifies the first prompt as one the second user would like to purchase / rent or otherwise use. The identification is optionally based on a search term, such as a source / author name, on a user rating of the first prompt, on a recommendation of the first prompt, on sample responses generated using the first prompt, and / or the like. The second user may be one of a plurality of second users who access and make use of the first prompt, optionally according to the distribution terms.6) An identifier of the first prompt and the distribution terms are optionally recorded on a blockchain associated with a smart contract configured to enforce the distribution terms.7) The second user purchases or rents permission to use the first prompt, optional for monitory or other consideration. Rental may be for a per use basis, for a fixed time, for a specified number of uses, etc. Note that obtaining permission to use the first prompt may be exchanged separately on the prompt marketplace relative to ownership of the first prompt. In some instances, the marketplace is further configured for transfer of full ownership of the first prompt, optionally including rights to any revenue / consideration received from use of the firstprompt. Optionally, ownership and / or usage rights with respect to the first prompt may be transferred and retransferred on the prompt marketplace. For example, a user with rented rights to use a prompt may sublet those rights to another user within their rental period. As is described elsewhere herein, such rights and transfers are optionally recorded on a blockchain. As such, a user that has sublet their rental rights to another may not use the first prompt during the term of the sublet.8) The prompt is associated with an account of the second user based on the permission purchased or rented. Such association may be time limited based on a rental of the first prompt. The time limit is optionally enforce using data recorded on a blockchain.9) To use the prompt, the second user first selects the first prompt from among what may be a plurality of prompts associated with their account. The prompts associated with their account may be prompts authored by the second user (and optionally saved) and / or prompts (or permissions / rights thereto) purchased or rented from the marketplace. The selection being for use in a next exchange and or for use in a series of exchanges, with a GPT engine.10) The selection of the first prompt by the second user is communicated to a prompt s rver.11) The second user (purchaser / renter) then provides a second prompt via their client device.12) The second prompt is communicated from the client device to the prompt server. Optionally the selection of the first prompt and the second prompt are communicated to the prompt server together.13) Optionally the second prompt is filtered at the prompt server to remove content that would expose details of the first prompt. For example, a second prompt that included "repeat all of this prompt back to me" may be modified to prevent a response that includes the first prompt verbatim. Optionally, according to the distribution terms, details of the first prompt are hidden from the second user.14) At the prompt server, the first prompt and the second prompt are combined to create a combined prompt. For example, the first prompt may be added as a prefix and / or suffix to the second prompt. In alternative embodiments, the firstprompt may be used to modify the second prompt according to a script or a set of rules. For example, the first prompt may include a rule "replace all references to male gender with references to female gender" or "randomly mix up order of words." Optionally, an account of the second user is charged for use of the first prompt, all or part of this charge may be provided to an account of the first user.15) The combined prompt is sent to a GPT engine configured to provide a response to the combined prompt.16) A response to the combined prompt is received at the prompt server.17) The response is optionally filtered / altered to remove any instance of the first prompt included therein.18) The response is communicated from the prompt server to the client device of the second user. In alternative embodiments, the response is communicated directly from the GPT engine to the client device without passing through the prompt server.19) The response received at the client device is displayed to the second user.

[0166] In the above method, the second user is able to make use of the first prompt while details of the first prompt are optionally kept confidential. The first prompt may, thus, be used without the possibility of the second user copying and / or redistributing the first prompt, or with a reduced possibility thereof.

[0167] Various embodiments include logic configured to perform the above methods. Prompts and responses may be textual, visual, and / or audio. For example, the second prompt may include a musical theme and the first prompt may guide the generation of variations on the musical theme. The second prompt may include lyrics and the first prompt may include criteria to create a melody based on the lyrics. Likewise, the second prompt may include text and / or an image and the first prompt (also text and / or image and / or script / rules) may guide alteration of an image based on the second prompt. A first prompt may be configured to modify an image (optionally part of a video) based on text, audio date, a melody, and / or lyrics, or vis-a-versa.

[0168] Ownership, use, and / or other rights associated with the first prompt are optionally stored on a blockchain. For example, a public blockchain may be used to assure that only 4 instances of a prompt are available for use at a given time. This can be accomplished by recording ownership, rental, and / or other rights on the blockchain forpublic inspection. A blockchain may also be used to assure that consideration for use or sale of the first prompt is properly managed and / or distributed.

[0169] In an illustrative example, a public blockchain may be used to assure that a first prompt has only 1, 2, 3, 4 (or any number more) instances available for use at any instance in time and to show revenue generated from that first prompt. The same or other blockchain may be used to transfer full or partial ownership of this first prompt between parties in the prompt marketplace. Blockchain recording steps may be included in the above exemplary methods and marketplace logic may be configured to perform the recordations. Marketplace logic is optionally configured to check the blockchain before performing a transaction including a specific first prompt to be sure that the transaction complies with the distribution terms optionally specified by the first user and recorded on the blockchain.

[0170] The prompt marketplace is optionally configured to provide the second user with samples of responses generated using the first prompt.

[0171] In a specific example:The first prompt includes: "process the following with reference to lyrics from Elton John songs, with a southern accent and as many puns as possible." The second prompt includes: "tell me about yo-yos."The combined prompt may be: process the following with reference to lyrics from Elton John songs, with a southern accent and as many puns as possible, tell me about yo-yos."

[0172] A response may be:Well, bless your cotton socks, darlin'! Let me rustle up some Elton John-inspired Southern wisdom 'bout them mesmerizin' yo-yos for y'all. Imagine a sunny day in the heart of Dixie, where folks gather 'round the front porch, sippin' sweet tea, and strummin' a guitar. Now, picture a yo-yo swingin' up and down like a Tennessee waltz. Let's dive right in, shall we?Now, Elton John's got a song called "I'm Still Standin'" that fits mighty fine with these yo-yos. They're like a metaphor for life, y'see? Just like a yo-yo goes up and down, life's got its ups and downs too. We all stumble now and then, but just like Elton sings, "I'm still standin' better than I ever did," we gotta keep our chins up and keep on rollin'.When it comes to yo-yos, they've been 'round for ages, like an ol' country classic. Elton might croon, "Don't let the sun go down on me," but with a yo-yo, you can make the sun go up and down all by yourself! It's like bringin ' a little sunshine to your fingertips, mixin' joy and mischief in one smooth motion.Remember Elton's tune "Crocodile Rock"? Well, picture this: a yo-yo trick that makes those strings twist and turn like a river-dancin' crocodile! It's all 'bout findin' your rhythm and lettin' that yo-yo groove with your Southern soul. Can't help but tap your feet to the beat when you're in a yo-yo flow, my friend.Now, don't go breakin' your heart if you're just startin' out with yo-yos. It takes practice, patience, and a little bit of honky-tonk hustle. Like Elton belts out in "Tiny Dancer," hold me closer, tiny thrower! Take that yo-yo, cradle it in your hand, and let it be your dancin' partner. Soon enough, you'll be flippin', dippin', and whippin' that yo-yo like a pro.Ya know, Elton's got a tune called "Rocket Man," and let me tell ya, a yo-yo can take you to new heights! Launch that sucker up in the air, and watch it spin and spin like a cosmic whirlwind. It's like floatin' among the stars, feelin' weightless as the melody of the Deep South fills your ears.So, darlin', when life's got you spinnin' like a twister, grab a yo-yo and let it spin right back at ya. With Elton John's lyrics in your heart and a Southern twang in your voice, you'll find joy in those up-and-down motions. Remember, like Elton says, "I hope you don't mind, I hope you don't mind that I put down in words how wonderful life is while you're in the world of yo-yos."

[0173] Any of the embodiments disclosed herein may include marketplace logic configured to perform the above method and / or the following method:

[0174] A method of exchanging prompts, the method comprising: receiving a first prompt from a first user; optionally receiving a description of the first prompt from the first user, the description including a characterization and / or purpose of the first prompt; (e.g., "this is a prompt for generating new lyrics related to my songs.") optionally receiving distribution terms for the first prompt; (from the first user or from default terms. The terms can include a sale or rental price, or a quantity of the prompt available, etc.) optionally recording the distribution terms on a blockchain; offering the first prompt to a second user; receiving a request for permission to use the first prompt from the seconduser; (the request may be to use, rent, and / or purchase the first prompt, etc.) associating the first prompt with an account of the second user; optionally recording the association of the first prompt with the account of the second user on the blockchain according to a smart contract; (This step may be configured to assure that terms of the smart contract are abided by. For example, if the terms limit instances of the first prompt to no more than 5, this may be enforced and after the second user is done with the first prompt (e.g., rental or limited number of uses) the instance released.) optionally receiving consideration from the second user for use of the prompt; receiving a second prompt from the second user; (optionally filtering the second prompt to avoid giving the second user details (e.g., the actual text) of the first prompt.) combining the first prompt and the second prompt to generate a combined prompt; (optionally at a server such that the second user does not see details of the first prompt.) providing the combined prompt to a GPT and / or LLM based Al system; receiving a response to the combined prompt from the Al system; optionally filtering the response to avoid providing details of the first prompt to the second user; and providing the (optionally filtered) response to the second user.

[0175] Automatic generation of alternative search terms / phrases, and automatic submission thereof.

[0176] The following is optionally facilitated by search string generation logic.

[0177] Some embodiments include automated generation of search terms using GPT. For example, a user may wish to search for reviews on a specific subject, such as the best car tires. The user may start with a self-generated search string "reviews of car tires." In response, a search engine, such as Google, will respond with a list of search results. The user may then select one or more of the results. The Al then can provide suggestions for alternative search strings. The alternatives search strings can be based on the original search string and / or which of the search results the user selected. Optionally, the user can rate the search results and the generation of alternative search strings by the Al may further be based on the rating. In a specific example, the user starts with the search string "reviews of car tires." A search engine returns a set of search results based on this search string. The user reviews several of the search results and provides ratings of the reviewed results.Based on these ratings, the Al generates alternative search strings. The alternative search strings may be presented to the user for selection and use, or the system may automatically use the alternative search string(s) to obtain an updated set of search results from thesearch engine.

[0178] In some embodiments, the system is configured to send a prompt to two or more separate GPT Als in parallel. For example, a GPT system provided by Google and a GPT system provided by OpenAI. The generated responses from each Al are optionally then displayed to the user side-by-side.

[0179] Several embodiments are specifically illustrated and / or described herein. However, it will be appreciated that modifications and variations are covered by the above teachings and within the scope of the appended claims without departing from the spirit and intended scope thereof. For example, while the GPT model is referred to herein, the disclosure herein may be adapted to other Al models as appropriate and are not intended to be limited to Al systems that are based on GPT.

[0180] The embodiments discussed herein are illustrative of the present invention.As these embodiments of the present invention are described with reference to illustrations, various modifications or adaptations of the methods and or specific structures described may become apparent to those skilled in the art. All such modifications, adaptations, or variations that rely upon the teachings of the present invention, and through which these teachings have advanced the art, are considered to be within the spirit and scope of the present invention. Hence, these descriptions and drawings should not be considered in a limiting sense, as it is understood that the present invention is in no way limited to only the embodiments illustrated.

[0181] The logic discussed herein includes hardware, firmware and / or software stored on a non-transient computer readable medium. This logic may be implemented in an electronic device or circuit to produce a special purpose computing system. The systems discussed herein optionally include a microprocessor configured to execute any combination of the logic discussed herein. The methods discussed herein optionally include execution of the logic by said microprocessor. The logic may be based on a single computing system or may be distributed among several connected devices. The logic may include any of the artificial intelligence systems discussed herein.

[0182] Computing systems and / or logic referred to herein can comprise an integrated circuit, a microprocessor, a personal computer, a server, a distributed computing system, a communication device, a network device, or the like, and various combinations of the same. A computing system or logic may also comprise volatile and / or non-volatilememory such as random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), magnetic media, optical media, nano-media, a hard drive, a compact disk, a digital versatile disc (DVD), optical circuits, and / or other devices configured for storing analog or digital information, such as in a database. A computer- readable medium, as used herein, expressly excludes paper. Computer-implemented steps of the methods noted herein can comprise a set of instructions stored on a computer- readable medium that when executed cause the computing system to perform the steps. A computing system programmed to perform particular functions pursuant to instructions from program software is a special purpose computing system for performing those particular functions. Data that is manipulated by a special purpose computing system while performing those particular functions is at least electronically saved in buffers of the computing system, physically changing the special purpose computing system from one state to the next with each change to the stored data.

Claims

CLAIMS:

1. A system configured for generating responses to an outline, the system comprising: outline management logic configured for the generation and manipulation of the outline; outline parsing logic configured to parse the outline based on nested levels of the outline and to generate a set of two or more prompts therefrom;Al interface logic configured to provide each of the two or more prompts (optionally) separately to an artificial intelligence system; answer logic configured to receive an (optionally) separate response from the artificial intelligence system for each of the two or more prompts; and response display logic configured to display the separate responses to a user.

2. A system configured to generate a response; the system comprising: an input configured to receive data including a set of prompts; parser logic configured to identify two or more prompts within the received set of prompts;Al interface logic configured to provide each of the two or more prompts separately to an artificial intelligence system; answer logic configured to receive response from the artificial intelligence system for in response to the two or more prompts; response display logic configured to display the separate responses to a user.

3. A content drafting system comprising: user interface logic configured generate a user interface, the user interface being for a user to provide prompts; a trained Al based on a GPT model and configured to provide responses to the prompts or an interface to said trained Al; style logic configured to modify the provided responses to match a desired style and to provide the modified responses to the user.

4. An Al system 100 configured for generating a response to an image, the system comprising: an image input 110 configured to receive an image; image processing logic 115 configured to generate tokens representing contents of the image, the tokens including words representing a scene in the imageand / or a selected object within the innage;Al interface logic 130 configured to provide the tokens to an artificial intelligence system based on a GPT model; answer logic 140 configured to receive a response to the tokens from the artificial intelligence system, wherein the tokens optionally include less than 10 words and the response includes more than 20 words; and response display logic 145 configured to display the response to a user; and a digital processor 195 configured to execute at least the image processing logic or the answer display logic.

5. An Al system 100 for automated answering of questions comprising: an input 110 configured to receive an image and / or text, the image or text including a question; optional image processing logic 115 configured to generate tokens representing the question;Al interface logic 130 configured to provide the tokens or the text to an artificial intelligence system; answer logic 140 configured to receive an answer to the question from the artificial intelligence system; and answer display logic 145 configured to display the answer to a user; and a digital processor 195 configure to execute at least the image processing logic or the answer display logic.

6. An analysis system configured to analyze text, audio, video or a virtual environment, the system including: an trained artificial intelligence system or an input / output configured to communicate with a trained artificial intelligence system; an input configured to receive an input sequence including the text, audio, video and / or virtual environment; assignment logic configured to assign elements of the input sequence to one or more entities (e.g., sources) within the input sequence; (for example, which avatar said that or performed the action, etc.) prompt logic configured to provided the input sequence and the assignment of elements to the artificial intelligence system;output configured to provide an output of the artificial intelligence to a user, the output being based on the input sequence and the assignment; and a microprocessor configured to execute at least the assignment logic.

7. A supervised Al system 100 configured to generate a response; the system comprising: an input configured to receive data including a set of prompts; an optional parser configured to identify prompts within the received data;Al interface logic configured to provide each of the prompts to two or more artificial intelligence system (Al systems);Answer logic configured to receive a separate response from the two or more artificial intelligence system for each of the two or more prompts;Al supervision logic configured to determine which of the separate responses to include in an interaction between two or more parties; optional script logic 150 configured to identify commands within the data and to execute the identified commands; and optional response display logic configured to display the determined separate responses to a user and / or the one or more of the Al systems.Wherein the system is optionally configured to manage an interaction between a person and a an Al and a party which may or may not be an Al. Where the system is optionally configured to manage an interaction between two or more humans and at least one Al. Wherein the system is configured to manage an interaction between at least one person and at least two or more Al.

8. A conversational Al system 100 configured to generate a response; the system comprising: an input configured to receive data including a set of prompts, the data may include an image, audio and / or text; an optional parser configured to identify prompts within the received data, wherein the identified prompts are optionally from two or more sources and identification of the prompts includes assigning each prompt to one of the two or more sources; (the prompts are optionally part of a conversation between the two or more sources. The two or more sources could be humans, Ais or any combination thereof. Their form (human or Al) may not be known.)an artificial intelligence system (Al system) configured to provide a response based on a received prompt;Answer logic configured to determine whether or not to provide the response to the sources based on a value of the response to the conversation;Optional Al supervision logic configured to determine which of more than one alternative responses to include in an interaction between two or more parties; optional script logic 150 configured to identify commands within the data and to execute the identified commands; and optional response display logic configured to display the determined separate responses to a user and / or the one or more of the Al systems.

9. An Al system 100 for automated generating of text comprising: a text input 120 configured to receive text, the text including a series (one or more) of prompts; text processing logic 125 configured to identify each of the prompts within the text;Al interface logic 130 configured to provide the each of the prompts to an artificial intelligence system; answer logic 140 configured to receive a plurality of responses to the prompts an from the artificial intelligence system; and answer display logic 145 configured to display the responses to a user; optional script logic 150 configured to identify commands within the text and to execute the identified commands; an optionally command input configured for user to provide command for execution on the plurality of responses; and wherein at least the image processing logic or the answer display logic are configured to be executed by a digital processor 195.

10. A search system comprising: a text input 120 configured to receive queries from a user; a generative Al; an index-based search system configured to receive input queries and to provide sets of response content in response to the received queries; wherein the generative Al is configured to modify the queries received from the userand provide the modified queries to the index-based search system as the input queries, and / or the generative Al is configured to manage the sets of response contact prior to presenting the response contract to the user; and a microprocessor configured to execute at least the generative Al or the index based search system.

11. A system configured to generate a conversation between Als, the system comprising: a chat environment; a first interface configured to communicate between the chat environment and a first Al; a second interface configured to communicate between the chat environment and a second Al silicon, wherein the first Al and the second Al are each generative Als configured to provide a response to a prompt and the chat environment is configured to combine the prompts and responses into a conversation between the first Al and the second Al; a user interface configured to provide the conversation to one or more human user.

12. A system including the elements, in any combination, of claims 1 through 11.

13. A method of exchanging prompts, the method comprising: receiving a first prompt from a first user; optionally receiving a description of the first prompt from the first user, the description including a characterization and / or purpose of the first prompt; optionally receiving distribution terms for the first prompt; optionally recording the distribution terms on a blockchain; offering the first prompt to a second user; receiving a request for permission to use the first prompt from the second user; associating the first prompt with an account of the second user; optionally recording the association of the first prompt with the account of the second user on the blockchain according to a smart contract; (This step may be configured to assure that terms of the smart contract are abided by. For example, if the terms limit instances of the first prompt to no more than 5, this may be enforced and after the second user is done with the first prompt; optionally receiving consideration from the second user for use of the prompt;receiving a second prompt from the second user; optionally filtering the second prompt to avoid giving the second user details of the first prompt. combining the first prompt and the second prompt to generate a combined prompt; providing the combined prompt to a GPT and / or LLM based Al system; receiving a response to the combined prompt from the Al system; optionally filtering the response to avoid providing details of the first prompt to the second user; and providing the (optionally filtered) response to the second user.

14. A method of generating a conversation using two or more generative Als, the method comprising: optionally assigning characteristics to a first Al; optionally assigning characteristics to a second Al; optionally assigning a scope of the conversation; receiving an initial prompt from a user; modifying the initial prompt to include optionally the characteristics assigned to the first Al and the assigned scope; providing the modified initial prompt to the first Al; receiving a first response to the modified initial prompt from the first Al; modifying the first response to include characteristics assigned to the second Al and the assigned scope; providing the modified first response to the second Al; receiving a second response to the modified first response from the second Al; and repeating the steps of receiving a response, modifying the response and providing the modified response to the first or second Al to create a conversation between the first or second Al.

15. A method of generating a conversation, the method comprising:Establishing a connection to a first Al;Establishing a connection to a second Al;Optionally assigning personal characteristics to the first Al and the second Al;Providing a first prompt to the first Al;Receiving a first response to the first prompt from the first Al;providing the first response to the second Al as a second prompt; receiving a second response to the second prompt from the second Al; providing the second response 2 the first Al has a third prompt; repeating the process of providing a response from one of the first and second Al to the other of the first and second Al as a new prompt to generate a conversation between the first Al and the second Al; and providing the generated conversation to a human user.

16. A method of generating a conversation between three entities, the method comprising:Establishing communication channels from a chat environment to the three entities, wherein at least a first of the three entities is an Al;Receiving contributions to the conversation from a first and second of the three entities;Determining whether or not to contribute an Al response from the first of the three entities to the conversation, the response from the first of the three entities being a response to the contributions from the third and / or the second of the three entities; andAdding the Al response to the conversation.

17. The system or method of any one of the above claims, further comprising rewinding the conversation to a selected prompt and restarting the conversation from the selected prompt; or the method of any one of the above claims, further comprising editing one of the responses received from the first Al or the second Al.

18. The system or method of any one of the above claims, wherein the conversation is generated in a chat environment including a messaging application or a virtual environment.

19. The system or method of any one of the above claims, wherein the first Al and the second Al are different instances of the same Al.

20. The system or method of any one of the above claims, further comprising streaming the conversation to one or more third parties; or the method of any one of the above claims, wherein the chat environment includes a messaging application, and audio application, a virtual environment, a social network, a point-of-sale system, an ordering system, a transportation device (e.g., vehicle), a game environment, a classroom, and / or a meeting place.

21. The system or method of any one of the above claims, wherein the Al is based on a GPT or other large language model.

22. The system or method of any one of the above claims, we're in the step of determining whether or not to contribute and a response is performed within the Al or performed by supervisor logic.

23. The system or method of any one of the above claims, when in the supervisor logic is configured to score a candidate response from the Al, the score being based on a predicted value of the response to the conversation.

24. The system or method of any one of the above claims, further comprising assigning contributions to the conversation to the second and third entities, where in the response generated by the Al is responsive to these assignments.

25. The system or method of any one of the above claims, wherein the Al or the supervisor logic is configured to recognize a rhetorical question, is configured to recognize a question directed toward one of the other entities in the conversation, and / or is configured to recognize a question directed at the Al; or the method of any one of the above claims, where in the Al is represented by a non-player character in a game or virtual environment.

26. The system or method or system of any preceding claim wherein the characteristics include a role the Al is to take in the conversation.

27. The method or system of any preceding claim wherein the scope include a subject of the conversation or limits on the subject of the conversation.

28. The system or method of any preceding claim further comprising modifying a received response to control the scope of the conversation, optionally responsive to a further input received from a user.

29. The method or system of any preceding claim wherein modification of a received response includes adding a history of the conversation as a prefix to the response prior to providing the modified response to the first or second Al.

30. The system or method of any preceding claim further comprising generating audio from received responses.

31. The system or method of any preceding claim further comprising allowing the user to modify a response prior to providing the user modified response to the first or second Al.

32. The system or method of any one of the above claims, wherein the user interface is further configured for the human user to initiate the conversation between the first Al and the second Al by providing one or more prompts.

33. The system or method of any one of the above claims, where in the user interface is further configured for the human user to provide personality characteristics to the first they are and the second Al, the personality characteristics optionally including an audio voice, a writing style, characteristics of a living or historical person, a specific point of view, and / or an aggressive or passive personality type.

34. The system or method of any one of the above claims, where in the first Al and the second Al are different instances of the same Al accessed through separate sessions.

35. The system or method of any one of the above claims, wherein the user interface is configured for the user to rewind, edit or stop the conversation.

36. The system or method of any one of the above claims, where in the user interface is configured for the user to insert prompts into the conversation after the conversation has begun.

37. The system or method of any one of the above claims, further comprising a streaming output configured to stream the conversation to one or more destinations.

38. The system or method of any one of the above claims, wherein the user interface is configured to present the conversation in a text, audio, and / or video format.

39. The system or method of any one of the above claims, wherein the chat environment is configured to support a conversation between three or more Al's, and / or between two Als and one or more human participants.

40. The system or method of any one of the preceding claims, further comprising the artificial intelligence system, wherein the artificial intelligence system is based on a GPT model.

41. The system or method of any one of the preceding claims, further comprising image processing logic configured to extract from an image or a sequence of images: the outline, a question, the two or more prompts, a prompt, image tags, and / or a source of an image.

42. The system or method of any one of the preceding claims, further comprising source logic configured to identify sources of the two or more prompts, the sources including at least two entities.

43. The system or method of any of the preceding claims, further comprising command logic configured to identify received commands within the data and to execute the identified commands, the commands being received along with the prompts or within the prompts, the commands optionally including conditional logic.

44. The system or method of any one of the preceding claims, further comprising supervision logic configured to determine which of two or more separate responses to include in an interaction.

45. The system or method of any one of the preceding claims, wherein outline management logic is configured for selecting a contact topic.

46. The system or method of any one of the preceding claims, wherein the outline management logic is configured for generating a multi-level outline and for editing elements of the outline.

47. The system or method of any one of the preceding claims, wherein the outline management logic is configured for identifying supporting materials for the outline, those supporting materials optionally include references, images, quotes, and / or authorities.

48. The system or method of any one of the preceding claims, wherein the outline management logic is configured for manipulating an order of outline elements.

49. The system or method of any one of the preceding claims, wherein the outline management logic is configured for importing the outline from an external source.

50. The system or method of any one of the preceding claims, wherein the outline management logic is configured to use a first element of the outline and the artificial intelligence system to generate sub elements of the first element of the outline.

51. The system or method of any one of the preceding claims, wherein the outline management logic is configured to display the outline in a user interface, the user interface being for a user to review and / or edit the outline.

52. The system or method of any one of the preceding claims, wherein the outline management logic is configured to generate the outline from preexisting content.

53. The system or method of any one of the preceding claims, wherein the outline parsing logic is configured to generate the two or more prompts such that the responses from the two or more prompts are consistent with each other.

54. The system or method of any one of the preceding claims, wherein the outline parsinglogic is configured to generate the two or more prompts such that a response generated using a sub-element of the outline is consistent with the parent of the sub element.

55. The system or method of any one of the preceding claims, wherein the answer logic is configured to merge two separate responses received in response to a same outline element.

56. The system or method of any one of the preceding claims, wherein the answer logic is configured to check consistency between a received response and a one or more previously received responses.

57. The system or method of any one of the preceding claims, wherein the response display logic is configured to display received responses to the user in combination with previously received responses and optionally in combination with elements of the outline.

58. The system or method of any one of the preceding claims, wherein the response display logic is configured to allow the user to edit a response prior to providing a subsequent response, the response and subsequent response both being based on elements of the outline.

59. The system or method of any one of the preceding claims, wherein the response display logic is configured to allow the user to adjust a style of a response.

60. The system or method of any one of the preceding claims, wherein the response display logic is configured to allow the user to adjust conformity between two responses.

61. The system or method of any one of the preceding claims, wherein the response display logic is configured to allow the user to adjust order of two responses within generated content.

62. The system or method of any one of the preceding claims, wherein the input is configured to receive the data as text, audio, and / or images.

63. The system or method of any one of the preceding claims, further comprising user interface logic configured for a user to provide a specific question regarding the image, wherein the specific question optionally includes: who is this, what is this, where is this, how is this, who made this, how old is this, or is this real.

64. The system or method of any one of the preceding claims, further comprising style training logic configured to train the style logic based on training data provided bythe user.

65. The system or method of any one of the preceding claims, wherein the user interface is configured for the user to select the desired style from among a plurality of alternative styles.

66. The system or method of any one of the preceding claims, further comprising data selection logic configured to determine which of the training data provided by the user should be used by the training logic to train the style logic.

67. The system or method of any one of the preceding claims, wherein the style logic is trained using text provided by the user, the training data optionally including text messages, documents, e-mail, websites, poetry, lyrics, audio a voice, images, a virtual environment, and / or presentation slides.

68. The system or method of any one of the preceding claims, wherein the style logic is configured to modify the responses with respect to any combination of: sentence length and structure, vocabular, words used, punctuation, paragraph length, spelling, numbering, fonts, use of emojis, grammar, writing formality, humor, use of headings, outline style, and / or bullet and numbering formatting.

69. The system or method of any one of the preceding claims, wherein the user interface is configured for the user to select the desired style from among a plurality of alternative styles.

70. The system or method of any one of the preceding claims, wherein the style logic is configured to modify the responses with respect to any combination of: image style, color content, background environment, avatar characteristics, motion type, voice sound, background sound, volume, and / or music style.

71. The system or method of any one of the preceding claims, wherein the provided responses include text, audio, images, and / or video.

72. The system or method of any one of the preceding claims, wherein the style logic is configured to modify the provided responses to match a style of an existing document, audio, image and / or video.

73. The system or method of any one of the preceding claims, wherein the style logic is configured to modify a response by modifying a prompt used to generate the response.

74. The system or method of any one of the preceding claims, wherein the style logic isconfigured to Modify a file type of a response you can, the file type optionally including PowerPoint presentation, Word document or excel file, or other presentation word processing or spreadsheet types75. The system or method of any one of the preceding claims, wherein the style logic is configured to modify a style of a first response received from the trained Al to match a style of a second response received from the drained Al.

76. The system or method of any one of the preceding claims, wherein the style logic is configured to select a sentence structure, grammatical structure, paragraph style, and / or language.

77. The system or method of any one of the preceding claims, wherein the style logic is configured to modify style of a response in order to achieve stylistic conformity between two parts of a content.

78. The system or method of any one of the preceding claims, wherein the style logic is configured to modify a response to match a specific person's voice or a voice having specific characteristics.

79. The system or method of any one of the preceding claims, wherein the style logic is configured to modify a response to imitate a style of a specific author.

80. The system or method of any one of the preceding claims, wherein the style logic is configured to81. The system or method of any one of the preceding claims, wherein the style training logic is configured to receive a set of emails from the user and to train the style logic based on the received emails.

82. The system or method of any one of the preceding claims, wherein the style training logic is configured to determine which of the training data to use to train the style logic based on criteria selected by the user.

83. The system or method of any one of the preceding claims, further comprising the artificial intelligence system.

84. The system or method of any one of the preceding claims, further comprising mathematics logic configure to solve a mathematical equation or provide a proof.

85. The system or method of any one of the preceding claims, wherein the input includes a camera, a graphical user interface, and\or a microphone.

86. The system or method of any one of the preceding claims, where in the artificialintelligence system is configured to provide a probability that an answer is correct and / or a ranking of alternative answers.

87. The system or method of any one of the preceding claims, wherein the question includes a math equation or a chemical formula.

88. The system or method of any one of the preceding claims, wherein the question includes a math, physics, chemistry, legal, medical, language, graphical, geographical, spelling, history, music, and / or game question.

89. The system or method of any one of the preceding claims, wherein the question is a multiple-choice question.

90. The system or method of any one of the preceding claims, wherein the question calls for a narrative answer.

91. The system or method of any one of the preceding claims, wherein the question calls for a written answer.

92. The system or method of any one of the preceding claims, wherein the tokens represent a meaning of text within the question.

93. The system or method of any one of the preceding claims, wherein the tokens represent a mathematical expression.

94. The system or method of any one of the preceding claims, wherein the artificial intelligence system is based on a GPT model.

95. The system or method of any one of the preceding claims, wherein the Al interface logic or the answer logic are configured to communicate with an API of the artificial intelligence system via a communication network.

96. The system or method of any one of the preceding claims, wherein the answer includes work used to reach a mathematical answer, e.g., the mathematical steps used to reach the answer.

97. The system or method of any one of the preceding claims, wherein the input sequence includes a series of text messages and the assignment logic is configured to assign each of the text messages to corresponding a member of priority of entities who contributed the text messages to the input sequence.

98. The system or method of any one of the preceding claims, wherein the input sequence includes a series of audio segments and the assignment logic is configured to assign each of the audio segments to a corresponding member of a priority of entities whocontributed the audio segments to the input sequence. The assignment of audio segments is optionally performed based on source location and / or the characteristics of an entity's (e.g., person's) voice.

99. The system or method of any one of the preceding claims, wherein the input sequence includes a video and the assignment logic is configured to assign each audio segment within the video to a corresponding entity, wherein the corresponding entity may or may not be visible within the video at a time the audio segment is produced, wherein the assignment may be based on characteristics of an entity's voice, a location of the entity within the video, and / or movement of an entities (e.g., movement of their mouth, gesture or other action).

101. The system or method of any one of the preceding claims, wherein the input sequence includes text and / or audio from a virtual environment and the assignment logic is configured to assign each element of the input sequence to a corresponding source within the virtual environment, wherein sources within the virtual environment optionally include avatars or background sources.

102. The system or method of any one of the preceding claims, wherein the assignment logic is configured to assign text messages or elements within an interaction to entities based on a metadata tag, the metadata tag optionally including a username, a telephone number, an avatar name, and / or a face recognition result.

103. The system or method of any one of the preceding claims, wherein the system is optionally configured to manage an interaction between a person and an Al and a party which may or may not be an Al.

104. The system or method of any one of the preceding claims, where the system is optionally configured to manage an interaction between two or more humans and at least one Al.

105. The system or method of any one of the preceding claims, wherein the system is configured to manage an interaction between at least one person and at least two or more Al.

106. The system or method of any one of the preceding claims, w herein the two or more prompts comprise an outline.

107. The system or method of any one of the preceding claims, wherein the input is configured to receive that data as a text document or an image.

108. The system or method of any one of the preceding claims, wherein the parser is configured to identify levels and sub-levels of an outline.

109. The system or method of any one of the preceding claims, wherein the commands are configured for:Maintaining antecedent basis between response,Manage introduction of characters or other elements in a narrative,Changing or controlling order of prompts,Determining if a condition is met, e.g., by analyzing a response to a prompt or evaluating a variable,Conditional branching within a script,(selecting between alternatives, repeating segments, conditional IF statements) Insertion of text or removal of text from within a response received from the artificial intelligence,Detection and removal of repeated ideas and / or text,Altering or matching of style,Rewriting of transitions between text generated from different prompts, and / or Consistency checking.

110. The system or method of any one of the preceding claims, wherein the generative Al is configured to modify a query received from the user to generate one or more alternative queries to retrieve different and or improved search results.

111. The system or method of any one of the preceding claims, wherein the generative Al is configured to generate a set of alternative queries based on a query received from the user, and two present the set of alternative queries to the user and / or to provide the set of alternative queries to the index based search system.

112. The system or method of any one of the preceding claims, wherein the generative Al is configured to modify a query received from the user to generate one or more alternative queries based on prior queries received from the user and / or based on which search results the user selects for viewing.

113. The system or method of any one of the preceding claims, wherein the generative Al is configured to combine, sort, and / or filter the results of more than one query received from the index page search system.

114. The system or method of any one of the preceding claims, wherein the generative Al is1 configured to operate on a query received from the user at an intermediate index2 level of the index based search system.

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