Systems and methods for enabling context-limited artificial intelligence tasks

Abstract

System and methods for generating a context-selection interface and executing one or more context-limited operations within a user-defined, context-limited action space are disclosed. A first set of context elements is received and a graphical interface including graphical elements representative of each the first set of context elements is generated. A selection of a first context set including context elements selected from the first set of context elements is received and a first user-defined, context-limited action space defined by the context elements of the first context set is generated. A contextually appropriate artificial intelligence operation is executed based on the first user-defined, context-limited action space and a first hierarchical graphical element representative of the contextually appropriate artificial intelligence operation is generated via the graphical interface. The first hierarchical graphical element is illustrated in a hierarchical arrangement with the graphical elements representative of the first context set.

Description

SYSTEMS AND METHODS FOR ENABLING CONTEXT-LIMITED ARTIFICIAL INTELLIGENCE TASKSTechnical Field

[0001] This application relates generally to context-limiting for artificial intelligence operations, and more particularly, to systems, methods, and interfaces for generating user-defined, context-limited action spaces and performing context-appropriate operations therein.Background

[0002] Current artificial intelligence (Al) processes are generated and operate within knowledge domains. Some knowledge domains are broad (e. ., generalized knowledge) while other knowledge domains may be partially constrained (e. ., a medical knowledge domain). Additionally, some current Al processes include context-aware processes that allow operations to be performed within certain scopes, such as performing a summarization process on a first set of N search results. Although current systems are able to perform some context-aware processes, current Al processes are not capable of allowing a user to define limited contexts within pretrained knowledge domains.

[0003] In addition, current Al processes may generate incorrect or unsupported outputs. For example, the output of a large language model is dependent on the input used to generate or train the large language model and may include sources that have incorrect, outdated, or otherwise undesirable information. Additionally, generative models, such as large language models, may “hallucinate” and generate statements that appear to be factual but are not supported within the knowledge base in which the large language model is expected to operate.Summary

[0004] In various embodiments, a system for generating a context-selection interface and executing one or more context-limited artificial intelligence operations within a user-defined, contextlimited action space is disclosed. The system includes a non-transitory memory and a processor communicatively coupled to the non-transitory memory. The processor is configured to read a set of instructions to: receive of a first set of context elements; generate a graphical interface including graphical elements representative of each context element in the first set of context elements; receive, via the graphical interface, a selection of a first context set including context elements selected from the first set of context elements; generate a first user-defined, context-limited action space comprising a context space defined by the context elements of the first context set; receive, via the graphical interface, a selection of a first contextually appropriate artificial intelligence operation; execute thefirst contextually appropriate artificial intelligence operation based on the first user-defined, contextlimited action space; and generate, via the graphical interface, a first hierarchical graphical element representative of the first contextually appropriate artificial intelligence operation. The first hierarchical graphical element is illustrated in a hierarchical arrangement with each of the graphical elements representative of each context element in the first context set.

[0005] In various embodiments, a computer-implemented method for generating a contextselection interface and executing one or more context-limited artificial intelligence operations within a user-defined, context-limited action space is disclosed. The computer-implemented method includes the steps of receiving of a first set of context elements; generating a graphical interface including graphical elements representative of each context element in the first set of context elements; receiving, via the graphical interface, a selection of a first context set including context elements selected from the first set of context elements; generating a first user-defined, context-limited action space comprising a context space defined by the context elements of the first context set; receiving, via the graphical interface, a selection of a first contextually appropriate artificial intelligence operation; executing the first contextually appropriate artificial intelligence operation based on the first user-defined, context-limited action space; and generating, via the graphical interface, a first hierarchical graphical element representative of the first contextually appropriate artificial intelligence operation. The first hierarchical graphical element is illustrated in a hierarchical arrangement with each of the graphical elements representative of each context element in the first context set.

[0006] In various embodiments, a non-transitory computer readable medium having instructions stored thereon is disclosed. The instructions, when executed by at least one processor, cause at least one device to implement a context-limiting environment framework for generating a context- sei ection interface and executing one or more context-limited artificial intelligence operations within a user-defined, context-limited action space. The context-limiting environment framework is implemented by performing operations including: receiving of a first set of context elements; generating a graphical interface including graphical elements representative of each context element in the first set of context elements; receiving, via the graphical interface, a selection of a first context set including context elements selected from the first set of context elements; generating a first user- defined, context-limited action space comprising a context space defined by the context elements of the first context set; receiving, via the graphical interface, a selection of a first contextually appropriate artificial intelligence operation; executing the first contextually appropriate artificial intelligence operation based on the first user-defined, context-limited action space; and generating, via thegraphical interface, a first hierarchical graphical element representative of the first contextually appropriate artificial intelligence operation. The first hierarchical graphical element is illustrated in a hierarchical arrangement with each of the graphical elements representative of each context element in the first context set.Brief Description of the Drawings

[0007] The features and advantages of the present invention will be more fully disclosed in, or rendered obvious by the following detailed description of the preferred embodiments, which are to be considered together with the accompanying drawings wherein like numbers refer to like parts and further wherein:

[0008] FIG. 1 illustrates a block diagram of a context-limiting environment framework for performing Al tasks, in accordance with some embodiments;

[0009] FIGS. 2A-2K illustrate various embodiments of user interface screens generated during execution of a context-limiting framework, in accordance with some embodiments;

[0010] FIG. 3 illustrates a method of generating a user-defined, context-limited action space via a graphical user interface and executing one or more additional processes within the user-defined, context-limited action space, in accordance with some embodiments;

[0011] FIG. 4 illustrates a network environment configured to provide a context-limiting environment, in accordance with some embodiments; and

[0012] FIG. 5 illustrates a computer system configured to implement one or more processes, in accordance with some embodiments.Detailed Description

[0013] This description of the exemplary embodiments is intended to be read in connection with the accompanying drawings, which are to be considered part of the entire written description. Terms concerning data connections, coupling and the like, such as “connected” and “interconnected,” and / or “in signal communication with” refer to a relationship wherein systems or elements are electrically connected (e.g., wired, wireless, etc.) to one another either directly or indirectly through intervening systems, unless expressly described otherwise. The term “operatively coupled” is such a coupling or connection that allows the pertinent structures to operate as intended by virtue of that relationship.

[0014] In the following, various embodiments are described with respect to the claimed systems as well as with respect to the claimed methods. Features, advantages, or alternative embodiments herein may be assigned to the other claimed objects and vice versa. In other words, claims for the systems may be improved with features described or claimed in the context of the methods. In this case, the functional features of the method are embodied by objective units of the systems. While the present disclosure is susceptible to various modifications and alternative forms, specific embodiments are shown by way of example in the drawings and will be described in detail herein. The objectives and advantages of the claimed subject matter will become more apparent from the following detailed description of these exemplary embodiments in connection with the accompanying drawings.

[0015] Furthermore, in the following, various embodiments are described with respect to methods and systems for enabling context-limited artificial intelligence (Al) tasks for a domainspecific knowledge base using selection and linking of context elements using a real-time graphical interface. In various embodiments, the graphical interface is configured to illustrate connections between context elements that may be modified, generated, and / or removed in real-time using the graphical interface. The context elements may be arranged in directed and / or non-directed arrangements. In some embodiments, the graphical user interface includes a pinboard interface configured to include graphical representations of context elements and graphical representations of connections between context elements. In some embodiments, the graphical user interface is configured to facilitate a workflow (e.g., a research workflow) beginning at a broad and / or shallow focus and narrowing to a deep focus on selected topics, contexts, information, etc.

[0016] In some embodiments, systems, and methods for enabling context-limited Al tasks for a domain-specific knowledge base are configured to generate context-limited datasets, domains, and / or areas of operation for one or more trained models, such as one or more generative models, one or more context models, etc. A context-limiting environment framework is configured to allow dynamic identification of user-defined limited context spaces within a broad knowledge domain. As one non-limiting example, a user may initiate an interaction with a context-limiting environment framework configured to operate within a medical knowledge domain. During an initial interaction (e.g., interactions via one or more initial interfaces), the context-limiting environment framework performs operations within the broadly defined medical knowledge domain. For example, searches for content, requests for generated content, and / or other Al-driven operations will operate on all documents and content available to the system within the medical knowledge domain.

[0017] After an initial selection of content elements, a user may utilize the context selection interface to identify a user-defined, context-limited action space within the broadly defined medical knowledge domain. For example, a user may initially select one generated response and two documents identified via a search related to a first topic, such as tracheotomy tubes. Subsequent to selecting the context elements, a user may interact with a graphical interface, as discussed in greater detail below, to generate a user-defined, context-limited action space that is limited to the context elements previously selected and related to tracheotomy tubes. After the user-defined, context-limited action space is defined, a user may execute additional Al-driven operations that will be limited to the user-defined, context-limited action space, such that a generalized request (e.g., summarize the content) is executed as a context-limited request within the user-defined, context-limited action space.

[0018] In one non-limiting embodiment, the initial interface page includes one of a search page and / or a chat interface configured to provide interactions with a broad medical knowledge domain. A search page may allow a user to search for topics of interest within the medical knowledge domain, such as topics related to specific medical conditions, procedures, etc. As one non-limiting example, a user may initiate a search regarding tracheostomy tubes, for example, by entering a natural language query such as, “What concerns should I be aware of when changing a tracheostomy tube?” The search page may present search results one or more context elements, such as one or more generated response (e.g., a natural language response generated by a generative model configured to operate within the medical knowledge domain), one or more relevant documents stored within a search repository (e.g., one or more medical articles, textbooks, journals, etc.), and / or any other suitable search results. A user may provide one or more inputs to select one or more of the context elements related to the initial search query.

[0019] After selecting a set of context elements, a context selection interface including each of the selected context elements may be generated. A user may select some or all of the previously selected context elements to generate a user-defined, context-limited action space for performing one or more additional processes. To continue the prior example, a user may have previously selected context elements related to tracheostomy tubes to be included in the context selection interface. The user may select some or all of the context elements related to tracheostomy tubes, causing a user- defined, context-limited action space to be defined based on the content elements related to tracheostomy tubes. The user may execute one or more additional tasks, such as Al-driven summarization, Al-driven generative tasks, search tasks, etc. that are executed within and limited to the user-defined, context limited action space related to tracheostomy tubes. By limiting the contextof the additional processes, a user may narrow operation of one or more Al tasks to a specific area of interest to the user, dynamically, in real-time during interaction with the context selection interface.

[0020] FIG. 1 illustrates a block diagram of a context-limiting environment framework 200 for performing Al tasks, in accordance with some embodiments. The context-limiting environment framework 200 is configured to receive a selection of context elements 202a-202c from a user via one or more interfaces, such as one or more initial interfaces, and generate a context-selection interface 204 including graphical representations of the context-elements 202a-202c. In some embodiments, the initial interfaces are configured to provide context elements (e.g., search results, generated content, etc. generated based on a broadly defined knowledge domain. As one non-limiting example, in some embodiments, an initial interface a search interface for searching within a generalized medical knowledge domain. As another non-limiting example, in some embodiments, an initial interface includes a chat interface including an Al-driven chatbot configured to generate answers based on a generalized medical knowledge domain.

[0021] In some embodiments, the context-selection interface 204 allows a user to identify (e.g. , select) at least one of the selected context elements 202a-202c (e.g. , context set 208) and generate a user-defined, context-limited action space 210 for operation and / or targeting of one or more additional processing tasks, such as one or more Al-driven and / or Al-based processes. In some embodiments, a subset of the selected context elements 202a-202c may be designated (e.g., further selected) to generate the user-defined, context-limited action space 210. The user-defined, contextlimited action space 210 includes a user-defined sub-domain and / or sub-portion of the broader knowledge domain. For example, the set of selected context elements 202a-202c may include one or more articles, sources, and / or documents within a broad knowledge base (e.g., a medical domain) that, collectively, are utilized to a define a narrow knowledge base (e.g., a user-defined knowledge domain) within the broad knowledge base. In some embodiments, the context set 208 may include context elements combining one or more broad knowledge domains to generate a user-defined knowledge domain.

[0022] The context-limiting environment framework 200 is configured to execute one or more Al-driven processes 212 within and / or based on the user-defined, context-limited action space 210. For example, Al-drive process 212 may include, but is not limited to, generative artificial intelligence tasks, summarization tasks, search tasks, etc. As one non-limiting example, a context-limiting environment framework 200 may be configured to generate a natural language summary of contentwithin the user-defined, context-limited action space 210. Although exemplary embodiments are discussed herein, it will be appreciated that any Al-driven process, such as generative tasks, search tasks, etc., can be performed within and / or on the context-limited, user-defined, context-limited action space 210.

[0023] In some embodiments, one or more initial interfaces are generated by and / or conjunction with the context-limiting environment framework 200. The initial interfaces are configured to facilitate selection or identification of one or more context elements 202a-202c. For example, FIG. 2A illustrates an initial search interface 250a. The search interface 250a includes a query slot 252 configured to receive a natural language query. In some embodiments, the search interface 250 also includes a set of suggest searches and / or actions 253, such as common, machinegenerated, and / or recent searches. In some embodiments, the search interface 250a, may include one or more recommended topics, searches, context-limited action spaces, etc. For example, in some embodiments, a research interface may include one or more suggested research topics, one or more guides to generating research-related context-limited action spaces, and / or any other suitable predetermined input. In some embodiments, the included and / or recommended interface elements may be generated based on prior user interactions with a platform and / or environment. Although search interface 250a is discussed herein, it will be appreciated that additional initial interfaces, such as a chat interface, may be provided by the context-limiting environment framework 200.

[0024] The search interface 250a is configured to receive a natural language query within the query slot 252. In response to receiving the query, the context-limiting environment framework 200 may execute one or more processes, such as a generative Al process and / or a search process, to generate responses to the user query. For example, as illustrated in FIG. 2B, a search response interface 252b may include a natural language response context element 258a may generated and displayed within the natural language response slot 254. Additionally and / or alternatively, and as illustrated in FIG. 2C, a search response interface 252c may include a set of result context elements 258b, 258c identified in response to a search process and displayed within a query result slot 256. The natural language response context element 258a may be generated according to any suitable generative process, such as, for example, utilizing a large language model configured to generate a natural language response based on one or more documents provided in a set of query results. The set of result context elements 258b, 258c may be generated according to any suitable search process, such as, for example, one or more algorithmic and / or model-based search processes.

[0025] Each of the search result interfaces 250b, 250c include context-selection elements 260a-260c displayed in conjunction with each context element 258a-258c. For example, with respect to the search interface 250a, context elements 258a may include the natural language response and may be displayed in conjunction with a first context-selection element 260a. Similarly, each of the query results for the natural language query may be displayed on search result interface 250c in conjunction with corresponding context-selection elements 260a-260c. The context elements 258a- 258c may include any suitable content and / or materials identified in response to one or more initial interface interactions, such as documents, images, text, generated responses, etc. The responses to an initial interaction, such as responses to a search query provided via the search query slot 252, are provided by one or more models configured to operate within a broad knowledge domain. For example, a query entered via the search interface 250a may generate an initial set of context elements 258a-258c selected from a broad knowledge domain, such as a medical knowledge domain. Each of the context elements 258a-258c (e.g., the natural language response, query results, etc.) has an associated context selection element 260a-260c that allows selection, or flagging, of the corresponding context element 258a-258c for inclusion within a context-limiting process and / or within a context selection interface 270, discussed in greater detail below.

[0026] In the illustrated embodiment, the context-selection elements 260a-260c include a graphical element representative of a pin, e.g., a graphical interface element allowing a user to “pin” the selected context element to a corresponding context-selection interface (e.g., “board”), discussed in greater detail below. After selecting a set of context elements, a context selection interface, such as context selection interface 270a illustrated in FIG. 2D may be generated. The selected context elements 258a-258c may include multiple modalities, such as documents, tables, images, etc. As will be appreciated based on the discussion below, the selected context elements 258a-258c and corresponding context selection interface allow a user to generate a user-defined, context-limited action space for additional processes.

[0027] In some embodiments, context- sei ection elements 260a-260c may allow selection of predefined context elements, such as the natural language response context element 258a, documents provided in response to an executed search, e.g., context elements 258b, 258c, etc. Additionally and / or alternatively, context- sei ection elements 260a-260c may be configured to allow selection of portions of predefined context elements, such as textual snippets (e.g., sentences, paragraphs, etc.) within a document and / or natural language response. Although embodiments are discussed herein with respect to context elements 258a-258c, it will be appreciated that the methods for generating user-defined,context-limited action spaces and performing Al-driven processes within the user-defined, contextlimited action spaces may be applied based on any suitable context elements and / or portions of a context element.

[0028] An initial interface, such as the search interface 250a, may be configured to allow selection and / or definition of any suitable context elements. In some embodiments, the search interface 250a may be configured to select context elements in real-time responsive to user inputs. For example, in some embodiments, a search result interface 250b, 250c may allow a user to select any number and / or type of presented context element. As another example, in some embodiments, the initial interface may define a smallest context element (e.g., a sentence, paragraph, generated response, etc.) and allow selection of each instance of a smallest context element within the initial interface. Although certain embodiments are discussed herein, it will be appreciated that any suitable process for selecting context elements may be employed to allow a user to select one or more context elements through an initial interface.

[0029] FIG. 2D illustrates a context selection interface 270a, in accordance with some embodiments. The context selection interface 270a may be generated in response to a user input, such as selection of an interface element configured to cause generation of a context selection interface, responsive to selection of a set of context elements, and / or responsive to any other suitable input. In some embodiments, the context selection interface 270a includes a context selection area 272 including graphical representations of previously selected context elements 258a-258c. In some embodiments, the context selection interface 270 includes a “pinboard” interface and the graphical representations of the selected context elements 258a-258c are configured to mimic notes or other elements “pinned” to the pinboard interface. In some embodiments, a context element 258a-258c includes a graphical representation selected, at least in part, based on an underlying type of the context element 258a-258c. For example, in some embodiments, a color of a graphical representation may be related to a type of the corresponding context element 258a-258c. Although specific embodiments are discussed herein, it will be appreciated that any suitable graphical modification (or no graphical modification) may be applied based on the type of the corresponding context element 258a-258c.

[0030] In some embodiments, the context selection interface 270a includes a contextual action slot 274 configured to display interface elements related to one or more contextually-appropriate actions. For example, as illustrated in FIG. 2D, when none of the context elements 258a-258c are selected, the contextual action slot 274 provides tips regrading selection of one or more contextelements 258a-258c to provide for execution of additional processes and / or tasks. As shown in FIG. 2E, selection of a single element causes the contextual action slot 274 of the context selection interface 270b to display the underlying content of the selected context element. For example, as illustrated in FIG. 2E, a first selected context element 258a includes a question-answer pair including a query and the natural language response context element, which is displayed in the contextual action slot 274 when the corresponding context element 258a is selected. Similarly, if a second context element 258b were selected, the underlying document, returned as a search result responsive to a user query, would be displayed in the contextual action slot 274. As a further example, in embodiments including imagebased content elements, the contextual action slot 274 may display the image when a corresponding contextual element is selected.

[0031] In some embodiments, the contextual action slot 274 provides for modification of a context or content for a context element 258a and / or generation of a new content element. For example, in some embodiments, the contextual action slot 274 displays the content of a context element 258a in response to the context element 258a being selected. A user may further select sub-content within the displayed content (e.g., a sentence, paragraph, image, etc.) and generate a content element for the selected sub-content. The generated content element may be generated in addition to the original context element 258a and / or may replace the context element 258a. In some embodiments, the content associated with the context element 258a is limited to the selected sub-content.

[0032] In some embodiments, the context selection interface 270a is configured to allow selection of at least one of the context elements 258a-258c to generate a user-defined, context-limited action space. For example, in some embodiments, a user may select each of the context elements 258a- 258c that are displayed on the context selection interface 270a to define and / or generate a user-defined, context-limited action space that encompasses the subject matter of each of the underlying context elements 258a-258c. The user-defined, context limited action space represents a user-defined, narrow (or narrowed) knowledge subdomain within the broader knowledge domain utilized by the initial interface interactions.

[0033] In some embodiments, and responsive to selection of two or more context elements 258a-258c, one or more contextual actions may be displayed and / or enabled within the contextual action slot 274. For example, as illustrated in FIG. 2F, selection of two or more of the context elements 258a-258c may cause the context selection interface 270b to display a set of contextual actions 276a, 276b within the contextual action slot 274. The set of contextual actions 276a, 276b may be domaindefined, defined by a set of selected context elements 258a-258c, etc. For example, in the illustrated embodiment, the contextual actions include initiating a new artificial intelligence-driven chat session or generating a hierarchical interface element referencing the selecting context elements 258a-258c (as discussed in greater detail below), although it will be appreciated that any suitable task may be presented within the contextual actions.

[0034] A user may select a contextual action 276a, 276b to initiate an operation, such as an Al-driven operation, within the user-defined, context-limited action space defined by the selected context elements 258a-258c. For example, continuing the example from FIG. 2F, selection of a first contextual action 276a initiates an Al-driven chat session that has a limited working knowledge base defined by the user-defined, context-limited action space. Similarly, in some embodiments, selection of a second contextual action 276b initiates an Al-driven text editing process that is configured to receive and execute commands within the user-defined, context-limited action space. Although exemplary embodiments are discussed herein, it will be appreciated that any suitable processes, tasks, etc. operating within and / or on the user-defined, limited-context action space may be initiated by selection of a corresponding contextual action 276a, 276b.

[0035] In some embodiments, an initiated contextual action 276a, 276b (e.g., one or more interface elements associated with an initiated contextual action 276a, 276b) may be displayed within the contextual action slot 274. The contextual action slot 274 may be configured to receive inputs (such as textual inputs) and / or display outputs (such as generated outputs) related to the initiated process. In some embodiments, additional contextually appropriate actions may be displayed and / or initiated within the contextual action slot 274. For example, as illustrated in FIG. 2G, selection of a “Start Al conversation” contextual action 276a causes an Al-driven chat session to be launched and a corresponding interface to be displayed within the contextual action slot. The interface for the AI- driven chat session includes one or more additional contextually appropriate actions 282 that may be executed.

[0036] The additional contextually appropriate actions 282 are also limited to the user-defined, context-limited action space. For example, selection of a natural language summarization process action 282, as illustrated in FIG. 2G, initiates a summarization process that generates a summary of the previously selected contextual elements 258a-258c defining the user-defined, context-limited action space. Similarly, initiation of one or more additional requests via a chat interface may cause one or more chat operations e.g., answer generation, summarization, searching, etc. that will beperformed within the limited context defined by the selected contextual elements 258a-258c. As one non-limiting example, a chat operation my include a request to identify the “best sentence” related to a topic, subject, etc. that will cause an artificial intelligence-driven chat process to identify a best sentence related to the topic within the limited context defined by the selected contextual elements 258a-258c. FIG. 2H illustrates an example embodiment of a summarization process performed for the user-defined, context-limited action space represented by the selection of context elements 258a-258c.

[0037] With reference again to FIG. 2G, in some embodiments, selection of a contextual action 276a, 276b generates a hierarchical context element 278a in the context selection interface 270d. The hierarchical context element 278a is representative of content associated with the executed contextual action 276a, 276b. For example, as illustrated in FIG. 2G, a hierarchical context element 278a is representative of a selected “Start Al conversation” contextual action 276a. The hierarchical context element 278a is representative and associated with any content generated during the corresponding Al chat session. For example, if a “Summarization” action 282 is selected, the hierarchical context element 278a will be associated with and include the corresponding summarized output of the AI- driven chat session. As noted above, the output of the Al-driven chat session is limited to the user- defined, context-limited action space. In some embodiments, the hierarchical context element 278a includes a label representative of the selected contextual action 276a, 276b, such as a “chat” label indicating it is representative of an Al-driven chat session.

[0038] In some embodiments, a set of edges representative of a relationship between a hierarchical context element 278a and constituent context elements 258a-258c are generated and displayed. The set of edges may include directional edges 280a-280c representative of the hierarchical relationship between the hierarchical context element 278a and the corresponding context elements 258a-258c. Although embodiments are illustrated herein within directional edges 280a-280c, it will be appreciated that the context selection interface 270 may alternatively and / or additionally include non-directi onal edges.

[0039] In some embodiments, a contextual action 276b may execute an integrated, Al-driven editor. The artificial intelligence-driven editor may define an editing space (e. , text editing space, code editing space, command execution space, etc.) that allows editing and / or execution of commands within the user-defined, context-limited action space. As one non-limiting example, the artificial intelligence-driven editor may allow text entry and / or editing to define a textual document. The artificial intelligence-driven editor may allow for any text editing operations, such as text entry, textformatting, etc. In some embodiments, the artificial intelligence-driven editor allows for execution of a set of contextual commands that perform one or more predetermined functions within the user- defined, context-limited action space. When a contextual command is selected, the contextual command may be executed within the user-defined, context-limited action space.

[0040] In some embodiments, the context selection interface 270f is configured to allow realtime definitions and / or modifications of one or more user-defined, context-limited action spaces. For example, in some embodiments, selection of a second set of context elements 258a-258c and / or hierarchical elements 278a allow a user to define an additional and / or refined user-defined, contextlimited action space. For example, as illustrated in FIG. 21, in some embodiments, a subset of the previously selected context elements 258b, 258c and a hierarchical element 278a may be selected to define a second user-defined, context-limited action space. The second user-defined, context-limited action space includes content created within and / or associated with the first user-defined, contextlimited action space, such as textual content generated via an Al-driven chat session and associated with the first hierarchical element 278a.

[0041] For example, and as previously discussed, a user may initiate an Al-driven chat session to generate textual content, such as a summary of content within the first user-defined, context limited action space defined by three content elements 258a-258c. The generated text may be associated with (e.g., stored with, linked to, etc.) the hierarchical element 278a. When the hierarchical element 278a is selected as part of a user-defined, context-limited action space, the content e.g., generated text) associated with the hierarchical element 278a is incorporated into the second user-defined, contextlimited action space. In some embodiments, the second user-defined, context limited action space includes only the content associated with the hierarchical element 278a and the selected context elements 258b, 258c e.g., excluding the content of the unselected context element 258a). In some embodiments, the second user-defined, context-limited action space is based on the a user-defined, context-limited action space of the hierarchical element 278a (e.g., the first user-defined, contextlimited action space), the content associated with the hierarchical element 278a, and the selected context elements 258b, 258c.

[0042] In some embodiments, additional contextual elements may be added to the context selection interface 270g and selected, either alone or in combination with existing context elements 258a-258c, to define additional user-defined, context-limited action spaces. For example, as illustrated in FIG. 2J, a fourth contextual element 258d may be added to the context selection interface 270g. Thefourth contextual element 258d may be added by returning to one or more initial interfaces and selecting additional context elements, uploading one or more context elements directly to a system executing a context-limiting environment framework 200, and / or through any other suitable process. The fourth contextual element 258d may include any suitable contextual element, such as a document, paper, generated content, etc.

[0043] After adding the additional context element(s) 258d, a user may interact with the context selection interface 270g to select an additional set of context elements and / or hierarchal elements to define a third user-defined, context-limited action space. For example, as shown in FIG. 2K, a user may select a first hierarchical element 278a and an additional context element 258d to define a third user-defined, context-limited action space. An additional Al-driven operation, such as an Al-driven editor process, may be implemented based on the third user-defined, context-limited action space. The additional Al-driven operation may be represented by a second hierarchical element 278b. In some embodiments, each additionally added context element and / or additional user-defined, context limited action space allows for expansion, contraction, and / or refining of one or more user- defined, context-limiting action spaces and / or performance of one or more additional actions within one or more user-defined, context-limiting action spaces.

[0044] The disclosed context-limiting environment framework 200 allows a user to dynamically generate or adjust a user-defined, context-limited action space for performing additional functionalities. The context selection interfaces 270a-270h provides visualization of contextual connections between operations so that a user can identify and / or adjust context-limited action spaces that were used to generate additional content, such as generative content associated with an Al-driven editor session.

[0045] In some embodiments, the user-defined, context-limited action space may be used to perform one or more adjustments to one or more models prior to executing a selected Al-driven process. For example, a user-defined, context-limited action space may be used to fine-tune a pretrained large language model to focus the LLM on content included within the user-defined, context-limited action space. As another example, the user-defined, context-limited action space may include a training dataset for adjusting one or more previously trained models.

[0046] In some embodiments, the user-defined, context-limited action space may be used to generate a context limitation for operation of one or more trained models, such as an LLM. For example, a user-defined, context-limited action space may be used to generate a context-limitingprompt to direct an LLM to perform operations within the user-defined, context-limited action space. In some embodiments, the user-defined, context-limited action space includes additional restrictions on operation of a trained model, such as a requirement that the trained model provide citations to sources within the user-defined, context-limited action space for each output.

[0047] In some embodiments, a state of the context selection interface 270a-270h and the underlying elements (e.g., the selected context elements 258a-258d, the hierarchical elements 278a, 278b, the directed connections / relationships, etc.) may be stored and / or persisted for future use. For example, in some embodiments, a user may initiate a first session to select a set of context elements, generate one or more user-defined, context-limited action spaces, and perform one or more additional tasks based on the user-defined, context-limited action spaces. A user may subsequently initiate a second session in which the actions performed during the first session (e.g., selection of context elements, generation of user-defined, context-limited action spaces, outputs of additional tasks) are persisted and may be the basis of one or more additional tasks, such as defining one or more new user- defined, context-limited action spaces, performing one or more additional tasks, etc.

[0048] Although embodiments are discussed herein including a graphical interface utilizing a “pinboard” layout, it will be appreciated that additional interface designs and / or elements may be utilized to generate user-defined, context-limited action spaces. For example, in some embodiments, a list-view layout may be provided to allow for selection of context elements for generating in a user- defined, context-limited action space. The list-view layout may include hierarchical relationships e.g., parent-child relationships), identify a type for a content element (e.g., document, stub, quote, image, etc.), and / or include any other relevant information for generating user-defined context-limited action spaces.

[0049] FIG. 3 illustrates a method 300 of generating a user-defined, context-limited action space via a graphical user interface and executing one or more additional processes within the user- defined, context-limited action space, in accordance with some embodiments. At step 302, a selection of at least one context element is received. For example, in some embodiments, a selection of context elements may be received via one or more initial interfaces, such as one or more search interfaces, chat interfaces, etc.

[0050] At step 304, a graphical interface, such as context selection interface 270a-270h, is generated. The graphical interface includes representations of the selected context elements, such as context elements 258a-258c. In some embodiments, the graphical interface includes a pinboardinterface configured to display each of the context elements as a card or other graphical element represented on a background that allows for movement and arrangement of the graphical elements. In some embodiments, the graphical interface includes a list interface configured to display each of the context elements as a list including additional information for each of the selected context elements.

[0051] At step 306, a selection of at least one context element is received via user interactions with the graphical interface generated at step 304. A user may select context elements at one or more hierarchical levels. For example, after an initial selection of context elements at step 304, each context element may be represented at a first hierarchical level. Each of the context elements may further be unassociated. A user may select one or more of the selected context elements, identifying a context set that is used to generate a user-defined, context-limited action space. The user-defined, contextlimited action space includes a context / action space that is confined to the contents of the selected context elements.

[0052] As another example, during an iterative implementation of step 306, one or more hierarchical elements may be included in the graphical interface (as discussed in greater detail below with respect to step 312). The hierarchical context element may be positioned at a different hierarchical level as compared to the initial set of selected context elements. A user may select the hierarchical element and one or more of the initial content elements identifying a second context set that is used to generate a second user-defined, context-limited action space. The second user-defined, context-limited action space includes a context / action space that is confined to the contents of the selected context elements and hierarchical elements.

[0053] At step 308, an additional process, such as a contextual process / action, is selected by a user and, at step 310, the contextual process is executed within the user-defined, context-limited action space. As discussed above, contextual processes may include Al-driven processes such as chat sessions, editor sessions, etc. Contextual processes may additionally include non-AI processes and / or hybrid processes. The contextual process may perform one or more Al-driven subprocesses, such as generative processes, search processes, etc., each of which is limited to the user-defined, contextlimited action space.

[0054] At step 312, a hierarchical interface element representative of the executed contextual process (e.g., representative of an output of a contextual process, transcript of an contextual process, input provided during a contextual process, etc.) is generated and included in the graphical interface generated at step 304. The hierarchical element may include a similar graphical element with respectto the graphical elements representative of the context elements and / or may include one or more modifications indicating a hierarchical element. In some embodiments, generation of the hierarchical interface element includes generation of hierarchical graphical indicators, such as directed and / or undirected edges between the generated hierarchical element and corresponding context elements and / or other hierarchical elements selected to define the user-defined, context-limited action space of the generated hierarchical element.

[0055] FIG. 4 illustrates a network environment 2 configured to provide a context-limiting environment framework, in accordance with some embodiments. The network environment 2 includes a plurality of devices or systems configured to communicate over one or more network channels, illustrated as a network cloud 22. For example, in various embodiments, the network environment 2 may include, but is not limited to, a context-selection computing device 4, a web server 6, a cloudbased engine 8 including one or more processing devices 10, a database 14, and / or one or more user computing devices 16, 18, 20 operatively coupled over the network 22. The context- sei ection computing device 4, the web server 6, the processing device(s) 10, and / or the user computing devices 16, 18, 20 may each be a suitable computing device that includes any hardware or hardware and software combination for processing and handling information. For example, each computing device may include, but is not limited to, one or more processors, one or more field-programmable gate arrays (FPGAs), one or more application-specific integrated circuits (ASICs), one or more state machines, digital circuitry, and / or any other suitable circuitry. In addition, each computing device may transmit and receive data over the communication network 22.

[0056] In some embodiments, each of the context- sei ection computing device 4 and the processing device(s) 10 may be a computer, a workstation, a laptop, a server such as a cloud-based server, or any other suitable device. In some embodiments, each of the processing devices 10 is a server that includes one or more processing units, such as one or more graphical processing units (GPUs), one or more central processing units (CPUs), and / or one or more processing cores. Each processing device 10 may, in some embodiments, execute one or more virtual machines. In some embodiments, processing resources (e.g., capabilities) of the one or more processing devices 10 are offered as a cloud-based service (e.g., cloud computing). For example, the cloud-based engine 8 may offer computing and storage resources of the one or more processing devices 10 to the contextselection computing device 4.

[0057] In some embodiments, each of the user computing devices 16, 18, 20 may be a cellular phone, a smart phone, a tablet, a personal assistant device, a voice assistant device, a digital assistant, a laptop, a computer, or any other suitable device. In some embodiments, the web server 6 hosts one or more network environments, such as an e-commerce network environment. In some embodiments, the context-selection computing device 4, the processing devices 10, and / or the web server 6 are operated by the network environment provider, and the user computing devices 16, 18, 20 are operated by users of the network environment. In some embodiments, the processing devices 10 are operated by a third party (e.g., a cloud-computing provider).

[0058] Although FIG. 4 illustrates three user computing devices 16, 18, 20, the network environment 2 may include any number of user computing devices 16, 18, 20. Similarly, the network environment 2 may include any number of the context-selection computing device 4, the web server 6, the processing devices 10, the workstation(s) 12, and / or the databases 14. It will further be appreciated that additional systems, servers, storage mechanism, etc. may be included within the network environment 2. In addition, although embodiments are illustrated herein having individual, discrete systems, it will be appreciated that, in some embodiments, one or more systems may be combined into a single logical and / or physical system. For example, in various embodiments, one or more of the context-selection computing device 4, the web server 6, the workstation(s) 12, the database 14, the user computing devices 16, 18, 20, and / or the router 24 may be combined into a single logical and / or physical system. Similarly, although embodiments are illustrated having a single instance of each device or system, it will be appreciated that additional instances of a device may be implemented within the network environment 2. In some embodiments, two or more systems may be operated on shared hardware in which each system operates as a separate, discrete system utilizing the shared hardware, for example, according to one or more virtualization schemes.

[0059] The communication network 22 may be a WiFi® network, a cellular network such as a 3 GPP® network, a Bluetooth® network, a satellite network, a wireless local area network (LAN), a network utilizing radio-frequency (RF) communication protocols, a Near Field Communication (NFC) network, a wireless Metropolitan Area Network (MAN) connecting multiple wireless LANs, a wide area network (WAN), or any other suitable network. The communication network 22 may provide access to, for example, the Internet.

[0060] Each of the user computing devices 16-20 may communicate with the web server 6 over the communication network 22. For example, each of the user computing devices 16, 18, 20 maybe operable to view, access, and interact with a website, such as an e-commerce website, hosted by the web server 6. The web server 6 may transmit user session data related to a user’s activity (e.g., interactions) on the website. For example, a user may operate one of the user computing devices 16, 18, 20 to initiate a web browser that is directed to the website hosted by the web server 6. The user may, via the web browser, interact with one or more graphical interface pages for generating user- defined, context-limited action spaces and / or performing one or more activities or operations withing a user-defined, context-limited action space.

[0061] The context-selection computing device 4 is further operable to communicate with the database 14 over the communication network 22. For example, the context- sei ection computing device 4 may store data to, and read data from, the database 14. The database 14 may be a remote storage device, such as a cloud-based server, a disk e.g., a hard disk), a memory device on another application server, a networked computer, or any other suitable remote storage. Although shown remote to the context-selection computing device 4, in some embodiments, the database 14 may be a local storage device, such as a hard drive, a non-volatile memory, or a USB stick. The context- sei ection computing device 4 may store interaction data received from the web server 6 in the database 14. The contextselection computing device 4 may also receive from the web server 6 user session data identifying events associated with browsing sessions, and may store the user session data in the database 14.

[0062] FIG. 5 illustrates a block diagram of a computing device 50, in accordance with some embodiments. In some embodiments, each of the context-selection computing device 4, the web server 6, the one or more processing devices 10, the workstation(s) 12, and / or the user computing devices 16, 18, 20 in FIG. 4 may include the features shown in FIG. 5. Although FIG. 5 is described with respect to certain components shown therein, it will be appreciated that the elements of the computing device 50 may be combined, omitted, and / or replicated. In addition, it will be appreciated that additional elements other than those illustrated in FIG. 5 may be added to the computing device.

[0063] As shown in FIG. 5, the computing device 50 may include one or more processors 52, an instruction memory 54, a working memory 56, one or more input / output devices 58, a transceiver 60, one or more communication ports 62, a display 64 with a user interface 66, and an optional location device 68, all operatively coupled to one or more data buses 70. The data buses 70 allow for communication among the various components. The data buses 70 may include wired, or wireless, communication channels.

[0064] The one or more processors 52 may include any processing circuitry operable to control operations of the computing device 50. In some embodiments, the one or more processors 52 include one or more distinct processors, each having one or more cores (e.g., processing circuits). Each of the distinct processors may have the same or different structure. The one or more processors 52 may include one or more central processing units (CPUs), one or more graphics processing units (GPUs), application specific integrated circuits (ASICs), digital signal processors (DSPs), a chip multiprocessor (CMP), a network processor, an input / output (I / O) processor, a media access control (MAC) processor, a radio baseband processor, a co-processor, a microprocessor such as a complex instruction set computer (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, and / or a very long instruction word (VLIW) microprocessor, or other processing device. The one or more processors 52 may also be implemented by a controller, a microcontroller, an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a programmable logic device (PLD), etc.

[0065] In some embodiments, the one or more processors 52 are configured to implement an operating system (OS) and / or various applications. Examples of an OS include, for example, operating systems generally known under various trade names such as Apple macOS™, Microsoft Windows™, Android™, Linux™, and / or any other proprietary or open-source OS. Examples of applications include, for example, network applications, local applications, data input / output applications, user interaction applications, etc.

[0066] The instruction memory 54 may store instructions that are accessed (e.g., read) and executed by at least one of the one or more processors 52. For example, the instruction memory 54 may be a non-transitory, computer-readable storage medium such as a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), flash memory (e.g. NOR and / or NAND flash memory), content addressable memory (CAM), polymer memory (e.g., ferroelectric polymer memory), phase-change memory (e.g., ovonic memory), ferroelectric memory, silicon-oxide- nitride-oxide-silicon (SONOS) memory, a removable disk, CD-ROM, any non-volatile memory, or any other suitable memory. The one or more processors 52 may be configured to perform a certain function or operation by executing code, stored on the instruction memory 54, embodying the function or operation. For example, the one or more processors 52 may be configured to execute code stored in the instruction memory 54 to perform one or more of any function, method, or operation disclosed herein.

[0067] Additionally, the one or more processors 52 may store data to, and read data from, the working memory 56. For example, the one or more processors 52 may store a working set of instructions to the working memory 56, such as instructions loaded from the instruction memory 54. The one or more processors 52 may also use the working memory 56 to store dynamic data created during one or more operations. The working memory 56 may include, for example, random access memory (RAM) such as a static random access memory (SRAM) or dynamic random access memory (DRAM), Double-Data-Rate DRAM (DDR-RAM), synchronous DRAM (SDRAM), an EEPROM, flash memory (e.g. NOR and / or NAND flash memory), content addressable memory (CAM), polymer memory (e.g., ferroelectric polymer memory), phase-change memory (e.g., ovonic memory), ferroelectric memory, silicon-oxide-nitride-oxide-silicon (SONOS) memory, a removable disk, CD- ROM, any non-volatile memory, or any other suitable memory. Although embodiments are illustrated herein including separate instruction memory 54 and working memory 56, it will be appreciated that the computing device 50 may include a single memory unit configured to operate as both instruction memory and working memory. Further, although embodiments are discussed herein including nonvolatile memory, it will be appreciated that computing device 50 may include volatile memory components in addition to at least one non-volatile memory component.

[0068] In some embodiments, the instruction memory 54 and / or the working memory 56 includes an instruction set, in the form of a file for executing various methods, such as methods for generating user-defined, context-limited action spaces using a graphical interface and executing one or more additional processes within the user-defined, context-limited action space, as described herein. The instruction set may be stored in any acceptable form of machine-readable instructions, including source code or various appropriate programming languages. Some examples of programming languages that may be used to store the instruction set include, but are not limited to: Java, JavaScript, C, C++, C#, Python, Objective-C, Visual Basic, .NET, HTML, CSS, SQL, NoSQL, Rust, Perl, etc. In some embodiments a compiler or interpreter is configured to convert the instruction set into machine executable code for execution by the one or more processors 52.

[0069] The input-output devices 58 may include any suitable device that allows for data input or output. For example, the input-output devices 58 may include one or more of a keyboard, a touchpad, a mouse, a stylus, a touchscreen, a physical button, a speaker, a microphone, a keypad, a click wheel, a motion sensor, a camera, and / or any other suitable input or output device.

[0070] The transceiver 60 and / or the communication port(s) 62 allow for communication with a network, such as the communication network 22 of FIG. 1. For example, if the communication network 22 of FIG. 1 is a cellular network, the transceiver 60 is configured to allow communications with the cellular network. In some embodiments, the transceiver 60 is selected based on the type of the communication network 22 the computing device 50 will be operating in. The one or more processors 52 are operable to receive data from, or send data to, a network, such as the communication network 22 of FIG. 1, via the transceiver 60.

[0071] The communication port(s) 62 may include any suitable hardware, software, and / or combination of hardware and software that is capable of coupling the computing device 50 to one or more networks and / or additional devices. The communication port(s) 62 may be arranged to operate with any suitable technique for controlling information signals using a desired set of communications protocols, services, or operating procedures. The communication port(s) 62 may include the appropriate physical connectors to connect with a corresponding communications medium, whether wired or wireless, for example, a serial port such as a universal asynchronous receiver / transmitter (UART) connection, a Universal Serial Bus (USB) connection, or any other suitable communication port or connection. In some embodiments, the communication port(s) 62 allows for the programming of executable instructions in the instruction memory 54. In some embodiments, the communication port(s) 62 allow for the transfer (e.g., uploading or downloading) of data, such as machine learning model training data.

[0072] In some embodiments, the communication port(s) 62 are configured to couple the computing device 50 to a network. The network may include local area networks (LAN) as well as wide area networks (WAN) including without limitation Internet, wired channels, wireless channels, communication devices including telephones, computers, wire, radio, optical and / or other electromagnetic channels, and combinations thereof, including other devices and / or components capable of / associated with communicating data. For example, the communication environments may include in-body communications, various devices, and various modes of communications such as wireless communications, wired communications, and combinations of the same.

[0073] In some embodiments, the transceiver 60 and / or the communication port(s) 62 are configured to utilize one or more communication protocols. Examples of wired protocols may include, but are not limited to, Universal Serial Bus (USB) communication, RS-232, RS-422, RS-423, RS-485 serial protocols, FireWire, Ethernet, Fibre Channel, MIDI, ATA, Serial ATA, PCI Express, T-l (andvariants), Industry Standard Architecture (ISA) parallel communication, Small Computer System Interface (SCSI) communication, or Peripheral Component Interconnect (PCI) communication, etc. Examples of wireless protocols may include, but are not limited to, the Institute of Electrical and Electronics Engineers (IEEE) 802. xx series of protocols, such as IEEE 802.1 la / b / g / n / ac / ag / ax / be, IEEE 802.16, IEEE 802.20, GSM cellular radiotelephone system protocols with GPRS, CDMA cellular radiotelephone communication systems with IxRTT, EDGE systems, EV-DO systems, EV- DV systems, HSDPA systems, Wi-Fi Legacy, Wi-Fi 1 / 2 / 3 / 4 / 5 / 6 / 6E, wireless personal area network (PAN) protocols, Bluetooth Specification versions 5.0, 6, 7, legacy Bluetooth protocols, passive or active radio-frequency identification (RFID) protocols, Ultra-Wide Band (UWB), Digital Office (DO), Digital Home, Trusted Platform Module (TPM), ZigBee, etc.

[0074] The display 64 may include a screen such as, for example, a Liquid Crystal Display (LCD) screen, a light-emitting diode (LED) screen, an organic LED (OLED) screen, a movable display, a projection, etc. In some embodiments, the display 64 may include a coder / decoder, also known as Codecs, to convert digital media data into analog signals. For example, the visual peripheral output device may include video Codecs, audio Codecs, or any other suitable type of Codec.

[0075] The optional location device 68 may be communicatively coupled to a location network and operable to receive position data from the location network. For example, in some embodiments, the location device 68 includes a GPS device configured to receive position data identifying a latitude and longitude from one or more satellites of a GPS constellation. As another example, in some embodiments, the location device 68 is a cellular device configured to receive location data from one or more localized cellular towers. Based on the position data, the computing device 50 may determine a local geographical area (e.g., town, city, state, etc.) of its position.

[0076] In some embodiments, the computing device 50 is configured to implement one or more modules or engines, each of which is constructed, programmed, configured, or otherwise adapted, to autonomously carry out a function or set of functions. A module / engine may include a component or arrangement of components implemented using hardware, such as by an application specific integrated circuit (ASIC) or field-programmable gate array (FPGA), for example, or as a combination of hardware and software, such as by a microprocessor system and a set of program instructions that adapt the module / engine to implement the particular functionality, which (while being executed) transform the microprocessor system into a special-purpose device. A module / engine may also be implemented as a combination of the two, with certain functions facilitated by hardware alone,and other functions facilitated by a combination of hardware and software. In certain implementations, at least a portion, and in some cases, all, of a module / engine may be executed on the processor(s) of one or more computing platforms that are made up of hardware (e. ., one or more processors, data storage devices such as memory or drive storage, input / output facilities such as network interface devices, video devices, keyboard, mouse or touchscreen devices, etc. that execute an operating system, system programs, and application programs, while also implementing the engine using multitasking, multithreading, distributed (e.g., cluster, peer-peer, cloud, etc.) processing where appropriate, or other such techniques. Accordingly, each module / engine may be realized in a variety of physically realizable configurations, and should generally not be limited to any particular implementation exemplified herein, unless such limitations are expressly called out. In addition, a module / engine may itself be composed of more than one sub- modules or sub-engines, each of which may be regarded as a module / engine in its own right. Moreover, in the embodiments described herein, each of the various modules / engines corresponds to a defined autonomous functionality; however, it should be understood that in other contemplated embodiments, each functionality may be distributed to more than one module / engine. Likewise, in other contemplated embodiments, multiple defined functionalities may be implemented by a single module / engine that performs those multiple functions, possibly alongside other functions, or distributed differently among a set of modules / engines than specifically illustrated in the embodiments herein.

[0077] Selection of contexts for execution of Al-driven processes is currently limited to only contexts defined by the models themselves. To the extent a context can be limited, such processes can be burdensome and time consuming for users, especially where such limitations must be enabled within the models themselves and / or defined at model deployment. Users frequently have to perform multiple, unintuitive steps to attempt to limit a context of a model and, ultimately, still have to rely on the model itself to correctly determine a context. Systems including graphical user interfaces configured to allow user-defined, context-limited action spaces, significantly reduce this problem, allowing users to easily define and / or modify context-limited domains for operation of models and / or processes. For example, in some embodiments described herein, when a user selects a context element, a corresponding interface element representative of the context element is generated. Each context interface element includes, or is in the form of, a link to the corresponding selected context information. Each context interface element thus serves as a programmatically defined shortcut to a context element, allowing a user to easily group and / or arrange context elements to intuitively generate user-defined, context-limited action spaces. This may be particularly beneficial for computing devicesexecuted with large models that require large training datasets to provide limited context executions to produce trusted results.

[0078] Although the subject matter has been described in terms of exemplary embodiments, it is not limited thereto. Rather, the appended claims should be construed broadly, to include other variants and embodiments, which may be made by those skilled in the art.

Claims

ClaimsWhat is claimed is:

1. A system for generating a context-selection interface and executing one or more contextlimited artificial intelligence operations within a user-defined, context-limited action space, comprising: a non-transitory memory; a processor communicatively coupled to the non-transitory memory, wherein the processor is configured to read a set of instructions to: receive of a first set of context elements; generate a graphical interface including graphical elements representative of each context element in the first set of context elements; receive, via the graphical interface, a selection of a first context set including context elements selected from the first set of context elements; generate a first user-defined, context-limited action space comprising a context space defined by the context elements of the first context set; receive, via the graphical interface, a selection of a first contextually appropriate artificial intelligence operation; execute the first contextually appropriate artificial intelligence operation based on the first user-defined, context-limited action space; and generate, via the graphical interface, a first hierarchical graphical element representative of the first contextually appropriate artificial intelligence operation, wherein the first hierarchical graphical element is illustrated in a hierarchical arrangement with each of the graphical elements representative of each context element in the first context set.

2. The system of claim 1, wherein the graphical interface comprises a pinboard interface.

3. The system of claim 1, wherein each context element in the first context set comprises a textbased content element.

4. The system of claim 1, wherein the processor is configured to read the set of instructions to: receive a second set of context elements; generate, via the graphical interface, a graphical element representative of each context element in the second set of context elements;receive, via the graphical interface, a selection of a second context set including context elements selected from the second set of context elements; generate a second user-defined, context-limited action space comprising a context space defined by the context elements of the second context set; execute a second contextually appropriate artificial intelligence operation based on the second user-defined, context-limited action space; and generate, via the graphical interface, a second hierarchical graphical element representative of the second contextually appropriate artificial intelligence operation, wherein the second hierarchical graphical element is illustrated in a hierarchical arrangement with each of the graphical elements representative of each context element in the second context set.

5. The system of claim 1, wherein the processor is configured to read the set of instructions to: receive a second set of context elements; generate, via the graphical interface, a graphical element representative of each context element in the second set of context elements; receive, via the graphical interface, a selection of a second context set including context elements selected from the first set of context elements and the second set of context elements; generate a second user-defined, context-limited action space comprising a context space defined by the context elements of the second context set; and execute a second contextually appropriate artificial intelligence operation based on the second user-defined, context-limited action space.

6. The system of claim 5, wherein the processor is configured to read the set of instructions to generate, via the graphical interface, a second hierarchical graphical element representative of the second contextually appropriate artificial intelligence operation, wherein the second hierarchical graphical element is illustrated in a hierarchical arrangement with each of the graphical elements representative of each context element in the second context set.

7. The system of claim 1, wherein the processor is configured to read the set of instructions to: receive, via the graphical interface, a selection of a second context set including context elements selected from the first set of context elements and the first hierarchical element; generate a second user-defined, context-limited action space comprising a context space defined by the context elements of the second context set; and execute a second contextually appropriate artificial intelligence operation based on the second user-defined, context-limited action space.

8. The system of claim 1, wherein the processor is configured to read the set of instructions to: receive a second set of context elements; generate, via the graphical interface, a graphical element representative of each context element in the second set of context elements; receive, via the graphical interface, a selection of a second context set including context elements selected from the second set of context elements and the first hierarchical graphical element; generate a second user-defined, context-limited action space comprising a context space defined by the context elements of the second context set; execute a second contextually appropriate artificial intelligence operation based on the second user-defined, context-limited action space; and generate, via the graphical interface, a second hierarchical graphical element representative of the second contextually appropriate artificial intelligence operation, wherein the second hierarchical graphical element is illustrated in a tiered hierarchical arrangement with each of the graphical elements representative of each context element in the first context set and the second context set.

9. The system of claim 1, wherein the hierarchical arrangement including the context elements and the first hierarchical graphical element are stored in a database in conjunction with the content of each of the context elements and the output of the first contextually appropriate artificial intelligence operation.

10. A computer-implemented method for generating a context-selection interface and executing one or more context-limited artificial intelligence operations within a user-defined, context-limited action space, comprising: receiving of a first set of context elements; generating a graphical interface including graphical elements representative of each context element in the first set of context elements; receiving, via the graphical interface, a selection of a first context set including context elements selected from the first set of context elements; generating a first user-defined, context-limited action space comprising a context space defined by the context elements of the first context set; receiving, via the graphical interface, a selection of a first contextually appropriate artificial intelligence operation; executing the first contextually appropriate artificial intelligence operation based on the first user-defined, context-limited action space; andgenerating, via the graphical interface, a first hierarchical graphical element representative of the first contextually appropriate artificial intelligence operation, wherein the first hierarchical graphical element is illustrated in a hierarchical arrangement with each of the graphical elements representative of each context element in the first context set.

11. The computer-implemented method of claim 10, wherein the graphical interface comprises a pinboard interface.

12. The computer-implemented method of claim 10, wherein each context element in the first context set comprises a text-based content element.

13. The computer-implemented method of claim 10, comprising: receiving a second set of context elements; generating, via the graphical interface, a graphical element representative of each context element in the second set of context elements; receiving, via the graphical interface, a selection of a second context set including context elements selected from the second set of context elements; generating a second user-defined, context-limited action space comprising a context space defined by the context elements of the second context set; executing a second contextually appropriate artificial intelligence operation based on the second user-defined, context-limited action space; and generating, via the graphical interface, a second hierarchical graphical element representative of the second contextually appropriate artificial intelligence operation, wherein the second hierarchical graphical element is illustrated in a hierarchical arrangement with each of the graphical elements representative of each context element in the second context set.

14. The computer-implemented method of claim 10, comprising: receiving a second set of context elements; generating, via the graphical interface, a graphical element representative of each context element in the second set of context elements; receiving, via the graphical interface, a selection of a second context set including context elements selected from the first set of context elements and the second set of context elements; generating a second user-defined, context-limited action space comprising a context space defined by the context elements of the second context set; and executing a second contextually appropriate artificial intelligence operation based on the second user-defined, context-limited action space.

15. The computer-implemented method of claim 14, comprising generating, via the graphical interface, a second hierarchical graphical element representative of the second contextually appropriate artificial intelligence operation, wherein the second hierarchical graphical element is illustrated in a hierarchical arrangement with each of the graphical elements representative of each context element in the second context set.

16. The computer-implemented method of claim 10, comprising: receiving, via the graphical interface, a selection of a second context set including context elements selected from the first set of context elements and the first hierarchical element; generating a second user-defined, context-limited action space comprising a context space defined by the context elements of the second context set; and executing a second contextually appropriate artificial intelligence operation based on the second user-defined, context-limited action space.

17. The computer-implemented method of claim 10, comprising: receiving a second set of context elements; generating, via the graphical interface, a graphical element representative of each context element in the second set of context elements; receiving, via the graphical interface, a selection of a second context set including context elements selected from the second set of context elements and the first hierarchical graphical element; generating a second user-defined, context-limited action space comprising a context space defined by the context elements of the second context set; executing a second contextually appropriate artificial intelligence operation based on the second user-defined, context-limited action space; and generating, via the graphical interface, a second hierarchical graphical element representative of the second contextually appropriate artificial intelligence operation, wherein the second hierarchical graphical element is illustrated in a tiered hierarchical arrangement with each of the graphical elements representative of each context element in the first context set and the second context set.

18. The computer-implemented method of claim 10, wherein the hierarchical arrangement including the context elements and the first hierarchical graphical element are stored in a database in conjunction with the content of each of the context elements and the output of the first contextually appropriate artificial intelligence operation.

19. A non-transitory computer readable medium having instructions stored thereon, wherein the instructions, when executed by at least one processor, cause at least one device to implement a context-limiting environment framework for generating a context-selection interface and executing one or more context-limited artificial intelligence operations within a user-defined, context-limited action space, wherein the context-limiting environment framework is implement by performing operations comprising: receiving of a first set of context elements; generating a graphical interface including graphical elements representative of each context element in the first set of context elements; receiving, via the graphical interface, a selection of a first context set including context elements selected from the first set of context elements; generating a first user-defined, context-limited action space comprising a context space defined by the context elements of the first context set; receiving, via the graphical interface, a selection of a first contextually appropriate artificial intelligence operation; executing the first contextually appropriate artificial intelligence operation based on the first user-defined, context-limited action space; and generating, via the graphical interface, a first hierarchical graphical element representative of the first contextually appropriate artificial intelligence operation, wherein the first hierarchical graphical element is illustrated in a hierarchical arrangement with each of the graphical elements representative of each context element in the first context set.

20. The non-transitory computer readable medium of claim 19, wherein the instructions cause the at least one device to perform operation comprising: receiving a second set of context elements; generating, via the graphical interface, a graphical element representative of each context element in the second set of context elements; receiving, via the graphical interface, a selection of a second context set including context elements selected from the second set of context elements and the first hierarchical graphical element; generating a second user-defined, context-limited action space comprising a context space defined by the context elements of the second context set; executing a second contextually appropriate artificial intelligence operation based on the second user-defined, context-limited action space; and generating, via the graphical interface, a second hierarchical graphical element representative of the second contextually appropriate artificial intelligence operation, wherein the second hierarchicalgraphical element is illustrated in a tiered hierarchical arrangement with each of the graphical elements representative of each context element in the first context set and the second context set.

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