System and method for evaluating inventions

Abstract

The user can enter into a user interface information about the invention and receive an evaluation of the patentability of the invention and receive those publication materials that are closest to the invention. The user can enter into a user interface feedback about the presented publication materials to try to find closer or more relevant results. The search for prior art can use artificial intelligence to map the concepts of the invention to and then find publication materials that are most similar to the concepts. A patentability score can be provided to show how known or patentable the invention is. The patentability score can be provided in a report and can be displayed graphically and / or numerically.

Description

SYSTEM AND METHOD FOR EVALUATING INVENTIONSCROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. Patent Application No.: 63 / 699,050 filed September 25, 2024, entitled SYSTEM AND METHOD FOR EVALUATING INVENTIONS, which is hereby incorporated by reference herein.FIELD OF THE DISCLOSURE

[0002] The present disclosure relates generally to a system and method for evaluating inventions or new technical concepts. More particularly, the present disclosure relates to a system and method for, evaluating inventions against prior art, in a software application with user flexible and customizable options.BACKGROUND OF THE DISCLOSURE

[0003] In the field of intellectual property, the evaluation of new ideas or inventions or new technical concepts or such engineering principles against existing prior art is a critical step in the patent application process. Prior art refers to any publicly available documentation that an invention is already known and includes previous patents, published patent applications, scientific articles, technical papers, and other publicly available information. The assessment of prior art is essential to determine the novelty of an idea, which is one of the key criteria for patentability. Current systems or tools for evaluating prior art involve manual searches through vast databases of patents and other literature. This process is time-consuming, labour-intensive, and often requires specialized knowledge to navigate and interpret the results. Moreover, the sheer volume of existing prior art makes it challenging to conduct a thorough and comprehensive evaluation, increasing the risk of overlooking relevant information.SUMMARY OF THE DISCLOSURE

[0004] Various details of the present disclosure are hereinafter summarized to provide a basic understanding. This summary is not an extensive overview of the disclosure and is neither intended to identify certain elements of the disclosure, nor to delineate the scope thereof. Rather, the primary purpose of this summary is to present some concepts of the disclosure in a simplified form prior to the more detailed description that is presented hereinafter.

[0005] The present application provides a system, method and computer readable medium for evaluating technical concept(s) or ideas. The user can enter into a user interface information about the invention and receive an evaluation of the patentability of the invention and receive those publication materials that are closest to the invention. The user can enter into a user interface feedback about the presented publication materials to try to find closer search results. The search for prior art can use artificial intelligence to map the concepts of the invention to and then find publication materials that are most similar to the concepts. The user interface can display a patentability score to show how known or patentable the invention is.

[0006] According to an embodiment a system for evaluating an invention against prior art references is disclosed that includes at least one processor, and a memory including instructions that, when executed by the at least one processor, cause the at least one processor to receive a description of the invention in a user interface, display in the user interface a set of prior art references that are gathered from a search of a database of publication materials that in response to the description are most similar, receive in the user interface at least one feedback of the differences of at least one of the references, and display in the user interface a second set of prior art references that are gathered from a search of the database in response to the at least one feedback.

[0007] In another embodiment, a system for evaluating an invention against prior art references is disclosed that includes at least one processor, and a memory including instructions that, when executed by the at least one processor, cause the at least one processor to receive a description of the invention in a user interface, display in the user interface a set of prior art references that are gathered from a search of a database of publication materials that in response to the description are most similar, and display in the user interface a patentability score of the invention based on a mapping of the prior art references to the description of the invention.

[0008] In another embodiment, a method of evaluating an invention against prior art references is disclosed that includes receiving a description of the invention in a user interface, displaying in the user interface a set of prior art references that are gathered from a search of a database of publication materials that in response to the description are most similar, receiving in the user interface at least one feedback of the difference of at least one of the references, and displaying in the user interface a second set of prior art references that are gathered from a search of the database in response to the at least one feedback.

[0009] In another embodiment, a method of evaluating an invention against prior art references is disclosed that includes receiving a description of the invention in a user interface, displaying in the user interface a set of prior art references that are gathered from a search of a database of publication materials that in response to the description are most similar, and displaying in the user interface a patentability score of the invention based on a mapping of the prior art references to the description of the invention.

[0010] In another embodiment, a computer readable medium with instructions for evaluating an invention against prior art references is disclosed where the instruction include receive a description of the invention, display a set of prior art references that are gathered from a search of a database of publication materials that in response to the description are most similar, receive at least one feedback of the difference of at least one of the references, and display a second set of prior art references that are gathered from a search of the database in response to the at least one feedback.

[0011] In another embodiment, a computer readable medium with instructions for evaluating an invention against prior art references is disclosed where the instructions include receiving a description of the invention, displaying a set of prior art references that are gathered from a search of a database of publication materials that in response to the description are most similar, and displaying a patentability score of the invention based on a mapping of the prior art references to the description of the invention.

[0012] Any combinations of the various embodiments and implementations disclosed herein can be used in a further embodiment, consistent with the disclosure. These and other aspects and features can be appreciated from the following description of certain embodiments presented herein in accordance with the disclosure and the accompanying drawings and claims.BRIEF DESCRIPTION OF THE DRAWINGS

[0013] FIG. 1 is a schematic illustration of a user interface that displays an embodiment of receiving description and displaying an output, that can be employed to execute one or more embodiments of the present disclosure.

[0014] FIG. 2 is a schematic illustration of flow showing methods, according to example embodiments of the present disclosure.

[0015] FIG. 3 is a schematic illustration of a user interface that seeks a description that can be employed to execute one or more embodiments of the present disclosure.

[0016] FIG. 4 is a schematic illustration of a user interface that allows user interaction, that can be employed to execute one or more embodiments of the present disclosure.

[0017] FIG. 5 is a schematic illustration of a user interface that seeks a description that can be employed to execute one or more embodiments of the present disclosure.

[0018] FIG. 6 is a schematic illustration of a user interface that seeks a description, that can be employed to execute one or more embodiments of the present disclosure.

[0019] FIG. 7 is a schematic illustration of a user interface that seeks a description that can be employed to execute one or more embodiments of the present disclosure.

[0020] FIG. 8 is a schematic illustration of a block diagram of a machine in the example form of a computer system within which a set of instructions may be executed for causing the machine to perform any one or more of the methodologies herein discussed.

[0021] FIG. 9 is a schematic illustration of a network system in the example form of a computer system within which a set of instructions may be executed for causing the machine to perform any one or more of the methodologies herein discussed.

[0022] FIG. 10 is a schematic illustration of flow showing methods, according to example embodiments of the present disclosure.

[0023] FIG. 11 is a schematic illustration of a user interface that displays a patentability score, key points of the invention, and relevant references.

[0024] FIG. 12 is a schematic illustration of a user interface that displays a detailed patentabilty score.

[0025] FIG. 13 is a schematic illustration of a user interface that displays aspects of inventions.

[0026] FIG. 14 is a schematic illustration of a user interface for various types of searches.DETAILED DESCRIPTION

[0027] The present application provides a system, method and computer readable medium for evaluating new ideas or new technical concept or inventions. The user can enter into a user interface information about the invention and receive an evaluation of the patentability of the invention and receive those publication materials that are closest or most relevant to the invention. The user can enter into a user interface feedback about the presented publication materials to try to find closer or more relevant search results. The search for prior art can use artificial intelligence to map the concepts of the invention to and then find publication materials that are most similar to the concepts. This can be done using vectors such as embeddings and cosine similarity. A patentability score can be provided to indicate how patentable the idea is and a patentability report can be generated and provided.

[0028] With the advent of advanced data processing technologies and artificial intelligence, there is an opportunity to improve the efficiency and accuracy of prior art evaluation. Automated systems can leverage natural language processing (NLP), embeddings, and / or machine learning algorithms to quickly filter through large datasets, identify similar prior art, and provide insights into the potential patentability of a new idea or invention or new technical concept. These systems can also facilitate the organization and visualization of prior art data, making it easier for inventors, patent agents, and attorneys to assess the novelty of an invention. Despite these advancements, existing automated systems still face several challenges. They often lack the ability to understand the context and nuances of technical descriptions, leading to false positives and negatives in search results. They do not allow for feedback and / or allow for a patent score to quickly and objectively evaluate the patentability of an idea or invention using a patentability score.

[0029] Therefore, there is a need for a more robust and comprehensive system and method that can effectively evaluate an invention against identified prior art. Such a system should incorporate embeddings, advanced NLP and / or machine learning techniques to accurately analyse and interpret technical descriptions. It should also integrate seamlessly with existing patent databases and provide user-friendly tools for organizing, visualizing, and assessing prior art information. The development of such a system would significantly enhance the patent novelty evaluation process by providing a patentability score and / or receiving feedback, reducing the time and effort required to identify similar prior art and increasing the likelihood of successful patent applications.

[0030] Embodiments in accordance with the present disclosure generally relate to a system and a method thereof, that allows for evaluating technical concepts or inventions. Unlike existing artificial intelligence (Al), which can do general things, there does not exist a way to evaluate the new technical concept(s) or inventions that can be mapped against prior art references to determine the patentability. The reason is that generative Al is not specifically trained on the right data to identify and filter new technical concepts or inventions against the prior art, that allow for the mapping of technical concepts of inventions. Also, generative Al is not trained on publication materials such as patent information and scientific literature.

[0031] Models can assist in evaluating new technical concepts or inventions by analysing large datasets and producing indicators to evaluate the same. For instance, some Al systems utilize neural networks to evaluate new inventions based on patterns and trends identified in existing data. Despite these advancements, current Al models have significant limitations. Al-powered search tools that can help evaluate the novelty of technical concepts(s) or inventions by comparing them against vast databases of publication materials. Many are not specifically tailored for accurate evaluation along with indicators to assess the evaluation, often requiring extensive customization and fine- tuning to be effective in this domain. Furthermore, the quality of evaluation of the new technical concepts or inventions by existing Al systems can be inconsistent, as these models may not fully understand the nuanced requirements for distinct and legally viable technical concept(s) or inventions and may hallucinate.

[0032] Therefore, there is a need for an improved system and method that can efficiently evaluate novel ideas or inventions otherwise, while also assessing their novelty and potentially their non-obviousness against prior art references. Such a system would leverage advanced Al technologies, including embeddings, deep learning, machine learning, and / or sophisticated NLP algorithms, to enhance the patentability evaluation process. It would also incorporate comprehensive databases and intelligent search capabilities to ensure thorough and accurate evaluation of new technical concepts or inventions, reducing the risk of legal disputes and time consumed during prosecution stage.

[0033] In some embodiments, Al can be used such as at least one large language model (LLM) to filter technical concept(s) using cosine similarity. The LLM can compare vector such as embeddings to quickly figure out if an invention is similar to a prior publication. In some embodiments, an LLM can be trained on general purpose information, while filtering LLMs can be trained on publications and prior art. The LLM can filter based on a similarity assessment such ascomparing an input to the LLM to vectors in the vector database of an LLM to see how similar it is to existing materials the LLM was trained on. A rules logic can be used to fine tune the filtering. In some embodiments, a rules LLM can be trained on the specific task of determining whether an idea is patentable.

[0034] The at least one LLM can be trained in the following way. First, the LLM can be pretrained by inputting vast amounts of textual information through a neural network architecture, so the LLM can learn general language patterns and structures such as learning the statistical relationships between words and phrases. This enables the system to process the vast amount of information in a computationally efficient manner. Through this, the LLM can begin to understand language. Second, the LLM can be fine-tuned to perform a specific task such as determining patentability of a new idea. This is done by training on a smaller task-specific information set using specialized methods which adjust the neural network weights. The LLM can be trained on patent application examination data for example. The LLM can learn the rules and how a patent is reviewed to determine patentability.

[0035] Finally, the LLM can be refined further, based on feedback received from an external system or by a human to enhance the LLM, this may include receiving feedback from a third party based on their review of the outputs of the LLM. In some examples, the LLM can also utilize retrieval-augmented generation (RAG) where the LLM looks up or augments the LLM’s knowledge with information from an external database before generating a response. This can help with improving accuracy by ensuring up to date information in the LLM. For example, this can be used to input new publications into the database to ensure that patentable ideas are accurately identified. This technical implementation of RAG may involve specialized indexing and retrieval methods that improve the processing efficiency when compared to conventional database approaches.

[0036] The LLM can implement a transformer-based neural network architecture or Al model for natural language processing. It can process input data in parallel through a self-attention mechanism and use encoders to input data and decoders to generate output data. In some embodiments, the LLM can process ideas or inventive concepts as discrete units that it uses to compare against other technical concepts in publications as process called mapping. The mapping process can utilize embeddings and structure the publications to allow for quick determination of similar publications to the received invention description. By technically decomposing publications into discrete technical concepts, the patentability assessment can be performed more precisely andaccurately with increased computational efficiency. The LLM can be optimized so that it uses less computing resources so that the system runs faster and uses less power.

[0037] The present disclosure provides a system, method and a computer readable medium for evaluating inventions or new technical concept(s). The system is capable of executing instructions to receive input, process the input to identify similar prior art, assess the input against the state of art and thereby display a patentability score of an invention against the state of art respectively. Beneficially, the system is designed to be more effective, efficient, and reliable. Further, the system can offer a robust tool for businesses or users seeking to protect and enhance their patent portfolio with newer solutions. Furthermore, the system can provide an advanced, automated solution that leverages cutting-edge technologies to enhance the evaluation of new inventions and patenting process overall.Evaluating invention(s) embodiment

[0038] In accordance with the present disclosure, a user interface of a system 200 for evaluating inventions or new technical concepts is disclosed in FIG. 1. The user interface of system 200 is configured to include a web browser or software application with a user interface for allowing an end user to enter title and description of an invention in which the user is seeking to evaluate the technical concepts or solutions or inventions as shown in FIG. 7. The descriptions in accordance with an embodiment includes title of the invention 201 and description 202 of the invention. The title 201 can be a crisp description of the invention in less than fifteen words, however not limiting to fifteen words in various embodiments. In an example embodiment, referring to FIG. 7 it is shown that a title 201 can be described as ‘improved stereo speaker’ .

[0039] Further, the description 202 can be relating to details about an invention summarising the novel aspects of the invention. It can relate to functionality, performance or the like of a system or device or apparatus or hardware or software. This can include, but is not limited to, challenges or problems. In an example embodiment, referring to FIG. 7 it is shown that description of the invention can be as described in description 202. In an optional embodiment only title 201 or only description 202 may be provided by the user.

[0040] In a further embodiment, the technical concept or inventions description 202 can be descriptive in text or specific keywords of the solution or invention can be provided. The invention can also be described textually or through specific keywords that encapsulate the details of domainof interest. This includes descriptive terms that outline the scope, focus, and specific novel aspects or objectives within a particular technical field.

[0041] The user interface of system 200 in accordance with the present disclosure further includes an option of allowing the end user to submit the entered title 201 and description 202 of the invention via a designated submit button 203 as shown in FIG. 2, 3, 5, 6 and 7.

[0042] In a further detailed embodiment, the functioning of the system is illustrated in FIG. 8 is a block diagram of machine in the example form of a computer system 300 comprising a processor and a memory including instructions, further processes the user provided description of the invention to identify similar prior art by mapping and / or filtering against a database of publication materials. The publication materials can be gathered from various database(s) and indexed and stored on a server. In an embodiment the state of prior art identified from the various database(s) including free and / or paid data sources that include publication materials such as patent information and nonpatent literature. The publication materials can be structured as embeddings in a database on the server.

[0043] The system 200 in accordance with the present disclosure is configured to include a processor and a memory with specific instructions to be performed by a machine or computer. The user inputs a description of the invention they are interested for evaluation against the prior art references. In some embodiments, a title can also be entered. There can also be a category field that the user is prompted to fill out as shown in FIG. 6. The system is configured to enable various main categories, including but not limited to electronics, computer science, biotechnology, artificial intelligence, block chain, chemistry, mechanical, life sciences. The user interface of the system in some embodiment of the present disclosure, is also configured to enable various sub categories, including but not limited to semiconductor devices, communication systems, software engineering, algorithms and data structures, computer networks, genomics, bioinformatics, environmental biotechnology, machine learning, robotics, biochemistry, thermodynamics, material science, neuroscience, and immunology. The subcategories can be dynamically changed to be relevant to the category that is selected. A set of rules or programming can be used to display certain subcategories based on the category selected. In some embodiments, the category can be determined based on the description provided. For example, the description can be analyzed and classified using artificial intelligence to a category. In some embodiments, this category and / or subcategory can be used to limit the searching that is performed.

[0044] The system processes this description and categories provided to understand the novelty aspect and keywords. The system then maps this information against a database(s) of publication materials to identify similar prior art. This database can include patent databases containing information about existing patents; and non-patent literature containing scientific papers, articles, and other publications that are not patents. In some embodiments, the invention description can be distilled into an embedding or multiple embeddings. The system 200 can then compare the invention description embedding against other prior art that are also distilled into embeddings.

[0045] In some embodiments, the system 200 can receive the invention disclosure by upload, input through a user interface, or by transfer from one system or software to another system or software. The transfer can be performed, for example, by an application programming interface (API) call where the system retrieves one or more invention disclosures from another system or software application.

[0046] The system 200 searches through a server database(s) to ensure a comprehensive search. The server database(s) can include material retrieved and indexed from free and / or paid data sources. This ensures that the search is thorough and covers all possible similar and related prior art. The system identifies the state of the art from the databases. This involves comparing the user- provided title and description with the contents of the databases to find matches or similar or related information of patents and / or scientific literature. This can be done using vectors such as embeddings and comparing using cosine similarity. By leveraging free and / or paid data sources, and considering publication materials including patent and non-patent literature, the system aims to provide a comprehensive view of the current state of the art, thereby mapping and assessing the invention to its best possible outcome against the prior art references.

[0047] The system 200 in accordance with the present disclosure further processes to compare the user input title and / or description with the identified publication materials from the databases. In a specific embodiment the comparison includes mapping the invention or new technical concepts based on the user description against the concepts present in the identified publication materials. The mapping can be done using the comparison of vectors such as embeddings. The system further retains the concepts that are already documented in the publication materials based on the description and reflects the same to the end user via a user interface 208 of FIG. 5. This can involve using keywords or phrases from the description and / or title 210. In some embodiments, the keywords can be used to search or filter the result set to then allow for the mapping of features to occur.

[0048] The system 200 in an embodiment maps the new technical concepts or inventions against the concepts present in the identified publication materials. This involves extracting key technical concepts and details from the publication materials identified as similar prior art and comparing them to the user inputted description with the extracted concepts from the publication materials to find similarities and / or overlaps. During the comparison process, the system identifies any overlaps or similarities between the user inputted description of the invention against those already documented in the publication materials. The process can also involve an initial search with keywords than a mapping to narrow down the results. As such, the mapping can be the second stage. The system specifically retains the concepts that are already documented, or otherwise ensures to reflect such publication materials or prior art references that are found to be similar to or the same as existing documented or patented concepts for further rating by the end user. After retaining such documented concepts, the system presents those concepts, which are considered to be related or similar or closely related to the description of the invention, including both patent and non-patent literature. In some embodiments, embeddings can be used to search and compare the similarity of the invention disclosure. The comparison of embeddings can be the mapping. Other techniques can be used to narrow the mapping of embeddings when searching through millions of publication materials.

[0049] In one embodiment, the database(s) of publication materials may include published patents, granted patents, expired patents, withdrawn patents, abandoned patents and / or non-patent literature.

[0050] In an embodiment, the evaluation of the new technical concepts or invention is implemented by an artificial intelligence or a large language model (LLM) trained on a diverse corpus of patents and scientific publications. In every embodiment, the invention to be evaluated in accordance with the system against what has been already existing in the state of art. In some embodiments, the system can use Natural Language processing to interpret the user provided inputs to evaluate against the prior art references. The generative artificial intelligence may be any one of but not limited to neural networks, support vector machine (SVMs), generative adversarial network (GANs) or Rule-based systems. It can also include retrieval-augmented generation (RAG) in the process of optimizing the large language model.

[0051] In some embodiments of the present disclosure, the user interface of the system receives the title and description of the invention or new technical concept, and the system first processes this input to make it usable for further analysis. Natural Language Processing (NLP)techniques like tokenization, stemming, and lemmatization are used to break down and understand text. Alternatively, embedding techniques (like word2vec, GloVe, or BERT) convert words or sentences into numerical vectors that capture semantic meaning. Using the model prediction, the extracted features, the Al modelled system makes predictions based on the task it was trained to perform. The systems might combine multiple predictions or use additional logic to make a final decision and simple decision-making based on predefined rules. Combining predictions from multiple models to improve accuracy. Output generation finally, the Al system generates an output based on the predictions and decisions made.

[0052] In a further embodiment the system used NLP to display both prior art references from the database and internally submitted inventions that are from an internal database within the organization. In a specific embodiment, the internal database includes previously submitted inventions that are unpublished.

[0053] In a further detailed embodiment, the system starts from the identified publication materials, evaluating the invention using an Al model, identifying key phrases, methodologies, and innovations described. Alternatively, search techniques can use vector databases (such as embedding databases) of publication materials. The system generates and displays the prior art references evaluated against the new technical concepts or invention based on the user's description, using algorithms designed to assess the novelty and non-obviousness of the user inputted innovative ideas within the specified technical area. These identified publication materials are then mapped against the inventions to identify any similarities or matches. The system further displays any publication materials that match or closely resemble those found in the prior art, ensuring that the invention is accurately being evaluated to assess the inventions novelty and non-obviousness. Accordingly, the system displays similar publication materials to the user, potentially with additional information regarding the prior art references thus generated.

[0054] In some embodiments, the system also retrieves results from multiple databases, including those in non-English languages. The system queries multiple databases based on the provided input, which may include USPTO, EPO, WIPO, Google Scholar, IEEE Xplore and nonEnglish databases that contain similar prior art in languages other than English. For any database that is in a non-English language different from the user’s input, the system automatically detects the language of the identified documents. Machine translation, such as Al-based machine translation, are then used to translate the non-English documents into the user's preferred language, e.g., English. This can involve both text-based translation and, in some cases, Optical Character Recognition(OCR) for images, scanned patents, or other documents that are not in a machine-readable format. Translation models such as those powered by Transformer-based architectures (e.g., Google’s Neural Machine Translation, DeepL, etc.) may be used to ensure high-quality translations.

[0055] The system can alternatively instruct the trained generative artificial intelligence to determine the patentability of the user inputted invention against the pending and granted patents in force. In yet another embodiment, the system also instructs the trained generative artificial intelligence to display prior art references from patents are no more legally in force. In a further embodiment, the system also instructs the trained generative artificial intelligence to display prior art references from non-patent literature.

[0056] The plurality of prior art references is generated by leveraging trained artificial intelligence and / or an LLM are presented to the user via a web page or software application display 205, 208 of the system 200 as shown in FIG. 1, 3 and 5. The generated prior art references are displayed separately in a plurality of segments for example not limited to 205, 206 and 207 of the web page or a software application 208 with both auto-generated rating and / or user feedback facilities. A plurality of graphical indicators can be used with every generated prior art reference for allowing the end user to rate the generated prior art reference based on its difference and / or closeness and / or relevance (or any other review metric not limited to afore-stated).

[0057] For example, referring to example embodiment in FIG. 1 and 3, displayed are the prior art references 205a, 205b, 205c, 206, and 207. The user interface of the system displays a most relevant figure and a summary of the prior art reference using artificial intelligence and / or an LLM. In some embodiments the figure may be optionally displayed.

[0058] The user interface displays a patentability score of the invention based on a mapping of the prior art references to the description of the invention represented as old to new 204 of FIG. 1 and 3. The score indicating closer to slide bar old or known denotes that the user inputted invention when mapped against the prior art shares significant similarities with the invention in terms of structure, function, or application. Further, the claims of the prior art may cover much of the same territory as the invention. Furthermore, the prior art may be in the same field or a closely related field as the invention. Yet, preferably the slide bar closer to old (or known) denotes that the differences between the prior art and the invention are minor and might be considered obvious by someone skilled in the field.

[0059] In an embodiment, the score indicating closer to slide bar new or patentable denotes that the user inputted invention when mapped against the prior art shares differences from the invention in terms of structure, function, or application. The claims of the prior art may not overlap significantly with those of the invention. Further, the prior art is in a different or only tangentially related field from the invention. Yet, preferably the slide bar closer to new denotes that the differences between the prior art and the invention are substantial and non-obvious to someone skilled in the field. Accordingly, the slide bar indicating the old to new guides the end user in assessing the patentability of the user inputted invention.

[0060] The patentability score can be displayed numerically or with other indicators. FIG. 11 is an illustration of a user interface that displays a patentability score, key points of the invention, and relevant references. Invention report card 600 is a report on the patentability of an idea or invention that can be generated and provided. In some embodiments, the report can be provided in print form on paper and / or provided on a display or user interface. The invention report card 600 includes a patentability score 602 that displays graphically and / or numerically a score of the patentability of the invention or idea.

[0061] The patentability score can be composed of a plurality of indicators that are used to measure the patentability of an idea or invention. The plurality of indicators can include things such as robustness, uniqueness, novelty, and obviousness. The robustness indicator can try to quantify the quality of disclosure. The robustness can use various indicators to indicate how robust the disclosure is. Some indicators of robustness can be text length, technical depth, and completeness of the description of the invention or idea. The text length is based on the number of words with certain thresholds counting for a certain score. For example, less than 100 words can be one score, 101-200 another score, and so on. The max score might be for 500 or 1000 words, whatever the user wants to use for scoring. The technical depth can include indicators such as whether equations are used, sentence complexity, and readability. Known measurements such as Flesch- Kincaid can be used. Otherwise it can be measured items such as on sentence length and word complexity to determine technical depth. The completeness indicator measures how much an invention disclosure form (IDF) is filled out. An invention disclosure form is a form with a series of questions and spaces to fill out about an invention or idea. The questions can include things like the title of the invention, description of the invention, attachments, when it was invented, who are the inventors, the closest known prior art to the invention and other information about the invention. The form can be provided in a user interface in some embodiments. The invention disclosure form can be customizable by theuser. The completeness indicator can measure completeness by percent of the invention disclosure form is completed. For example, the score can be calculated that a form that is filled out 80% a score of 8 out 10 is provided. Other weights or factors can be used.

[0062] Uniqueness scoring can be based on number of unique elements identified in the description of the invention or idea. The unique elements can be identified by Al, such as an LLM, that uses items such as keywords, key phrases, and similarity checks to determine uniqueness. In order to determine the unique elements the text can be converted to embeddings and cosine similarity can be used for comparisons. The score can be based on the number of unique elements with each element scoring a percentage up to some threshold. For example, five unique elements.

[0063] The novelty indicator can be used to indicate how novel an idea is compared to prior art, such as previously published documents. The novelty score can be generated based on mapping and / or similarity. The key concepts, summary, keywords / key phrases from the invention can be mapped to key concepts from the prior art to see if there are matches. To understand how close key concepts are from one another, vectors can be compared to one another. The key concepts can be extracted from the invention disclosure or generated by Al based on the invention disclosure. The summary can be generated by Al based on the invention disclosure. The keywords / phrases can be generated by Al based on the invention disclosure. Any one or more of the different search methods can be used or all of them can be used. The novelty indicator can consider the prior art found by the searches based on similarity. This can be based on mapping key concepts or similarity of the documents. The novelty score can be calculated by thresholds, percentage, or by a specified formula. The thresholds can be based on ranges of similarity to arrive at a score. For example, a similarity 0.4-.0.5 is one threshold and is given a score 6.5 or 65%. In another example, the similarity can be converted into a percentage directly such as [ 10-(similarity* 10)] . For example, a similarity of 0.9 (quite similar) would be scored as following [10-(0.9*10)]=l or 10%. In another example, the similarity can be scored using [10-(similarity squared* 10)]. In this case, a similarity of 0.5 would be scored as following [ 10-(0.25 * 10)]=0.75 or 75%. In some cases, the average similarity score can be used to calculate the novelty score. The average similarity can be of the top 2, 5, or 10 references.

[0064] The obviousness indicator can be used to indicate how obvious an idea is compared to the prior art, such as previously published documents. There are a few ways that obviousness can be scored such as combining the top few patents (two or three) from the novelty search and comparing the combined documents similarity to the invention description (key concepts, summary, or keywords / key phrase). The system can map using Al the key concepts to the combined references.In some embodiments, the key concepts of prior art are distilled by Al then mapped to key concepts of the invention. For example, if there is high similarity between a key concept of the prior art to a key concept of the invention disclosure, that element is said to be shown by the prior art. For obviousness, there can be a mapping of key concepts to two or more references. For example, the closest match of a primary reference can be found for the novelty. Then a reference that has overlapping key concepts, but also show other key concepts of the invention can be combined in an obviousness combination. While this is described in relation to an obviousness score, some techniques can be used in patent searching to figure out patentability of an idea or invention or in trying to invalidate a patent. Currently, there is no good way to automatically come up with obviousness-type invalidity charts.

[0065] The user can select the weighting of the indicators to arrive at a patentability score. In some embodiments, the patentability score can just be based on novelty and obviousness, or just based on novelty. It can also include at least one of completeness, robustness, uniqueness, novelty, and obviousness. For example, the patentability score can include robustness, uniqueness, novelty, and obviousness with each factor having an equal weight in scoring. The numerical patentability score can be based on score of 0-10, or 0-100, or some other configuration. A score of ten or close to ten can be considered very patentable or a good invention or idea.

[0066] FIG. 11 includes patentability score key points 604, a link to a detailed patentability score 606, key points of the invention 608, and relevant references 610. In some embodiments, an Al generated (for example, LLM-based) summary of the invention or idea can be shown in invention report 600. The patentability score key points 604 describes aspects of the patentability score. For example, it can comment on indicators such as robustness, uniqueness, novelty, and obviousness (103 combination). The patentability score key points can give few word summaries of how each of the scoring indicators fared in the patent report 600. The link to a detailed patentability score 606 can be a display as illustrated in FIG. 12. FIG. 12 is an illustration of a patentability score in detail. A patentability score 602 can be shown numerically in this instance. The patentability score 602 can be an overall score in some embodiments. The patentability score 602 can be composed of indicators robustness 612, uniqueness 614, novelty 616, and obviousness 618. These indicators are described in more detail above. The detailed patentability score can include scores for each of the patentability score indicators, for example, their weights in coming up with the overall patentability score 602 and a description of the indicator score. The key points of the invention 608 can be generated or extractedby an LLM. They can be generated by using embeddings and then comparing similarity among the embeddings in one example.

[0067] The relevant references 610 are publications such as prior art patent publications that relate to the invention. The relevant references 610 can be found based on mapping and / or similarity. The key concepts, summary, keywords / key phrases from the invention description can be mapped to key concepts from the prior art to see if there are matches. To understand how close key concepts are from one another, vectors can be compared to one another. The key concepts can be extracted from the invention disclosure or generated by Al based on the invention disclosure. The summary can be generated by Al based on the invention disclosure. The keywords / phrases can be generated by Al based on the invention disclosure. Any one or more of the different search methods can be used or all of them can be used to locate relevant references. The user can choose the search methods used to find the relevant references 610. A user interface can show comparisons of different search methodologies such as in FIG. 14.

[0068] FIG. 14 illustrates a user interface where different search methodologies can be compared against one another with top references showing. The references can be publications that are prior art to the invention. Invention key points 670 shows a search methodology based on searching the key points of the invention disclosure against publications. The key points can be extracted or generated by an LLM from the invention description. The summary 672 shows a search methodology based on search the summary of the invention disclosure against publications. The summary can be generated by an LLM from the invention disclosure. The keywords extracted from the invention disclosure 674 shows a search methodology based on searching keywords against publications. The keywords can be extracted from the invention disclosure using an LLM. The keywords extracted from the summary 676 shows a search methodology based on searching keywords from the summary against publications. The keywords can be extracted from an LLM generated summary of the invention disclosure by the same or another LLM. Each search methodology can have a patentability score associated with it. The patentability score can be based on the closeness of the publications, for example, from the similarity of the publications. The patentability score can be calculated as described for the novelty indicator in some embodiments. Each of the search methodologies can have a user selectable number of publications or references 678 that are displayed. In this example, five references are shown. The user can click into the references to bring up information about the reference such as figures, an LLM generated summary,an LLM generated novelty aspects, the abstract, the claims, bibliographic information such as filing date, priority date, inventors, owner, etc. and even the specification.

[0069] The user can in some embodiments, further refine the results by evaluating the generated prior art based on the similarity with the user inputted invention. For example, referring to FIG. 3 it is shown that the slide bar 206a, 207a indicates an option allowing the user to rate the prior art as different or same or based on relevance. In some embodiments the user may evaluate the resulted or generated or displayed prior art as different or same using the slide bar based on core elements and features of the invention and compare these core elements against the prior art generated. The end user may determine if the prior art includes all the features of the invention in the same or similar or close manner and combination and verify if the purpose and function of the prior art match those of the invention. Further, the end user may also check if the claims made in the prior art reference cover the same scope as the invention.

[0070] Accordingly, the end user may rate the prior art as different using the slide bar 206a, 207a if the prior art lacks key elements or includes additional features that significantly change its purpose and function compared to the proposed idea, it is considered different. Further, the end user may rate the prior art as same using the slide bar 206a, 207a if the prior art does not lack key elements or does not include substantial distinct features that significantly change its purpose and function compared to the proposed idea, it is considered same.

[0071] Further additionally, in some embodiments as shown in FIG. 3, the user may also be provided with a prompt box 206b, 207b allowing the end user to effectively describe the features that are distinct in the invention when compared to the generated prior art. Upon inputting such text, the system will further refine the results based in the indicator and prompt text inputted and display the updated prior art references. This allows the end user to assess the patentability of the invention based on a second set of prior art references that are gathered from a search of the database in response to the at least one rating.

[0072] In yet another embodiment, as shown in FIG. 5 the end user may also be provided with an option to rate the invention as different or same 210a. In some embodiments, the feedback options may also vary such as indicating close or far 210b. For example, in FIG. 5, 210a or 210b may be optionally used by the end user to provide feedback of the invention. The end user may determine if the prior art includes all the features of the invention in the same or similar or close manner and combination and verify if the purpose and function of the prior art match those of theinvention. Further, the end user may also check if the claims made in the prior art reference cover the same scope as the invention. Accordingly, the feedback may be provided. The graphical indicator used can allow a spectrum of possibilities between different feedback options.

[0073] In yet a further embodiment, referring to FIG. 4, the user is also provided with an option to determine the patentability of an invention through a user interface of an interactive chatbot. The user may interact or brainstorm with the user interface by giving direct instructions in the form of a chat 211 to refine the generated results. The chat function illustrated in FIG. 4 enables refinement of results by real-time conversation with the user. The chat function in some embodiments, may ask follow up questions to better understand the user’s intent and the user can provide feedback. As shown, the system 200 can gather information in the chat 211 such as: “How would you describe your invention in a few words?” The user can then enter into the user interface of system 200 the invention. Here it is a wearable fitness tracker. The system 200 can then break out the features, which can be keywords, concepts, or phrases. These features are used in the mapping to compare against prior art references to see if the features are shown, partially shown, or not shown in the prior art. The system can display the results as described in reference to FIGS. 1, 3, and 5. The results can also be displayed in the chat 211 including a graphical indicator of how patentable the invention is, an Al summary of the prior art, an Al summary of the features of the prior art, a relevant figure of the prior art. Feedback can be provided through the chat 211. Further, based on the user’s response, the chat function may adjust and refine the direction of the conversation.

[0074] Referring to the system 200 in FIG. 5, it is shown that a first generated prior art includes a set of first graphical indicators for presenting the different or same 210a of the first generated prior art. It also configured to further include a prompt box 210c. The prompt box has been specifically configured for the end user to input further instructions to refine the generated prior art in some embodiments. As shown, different graphical indicators can be used to receive feedback from the user. For example, a sliding bar (FIG. 3), a set of circles (FIG. 5), a set of stars, or any other feedback graphical indicator can be used.

[0075] In some embodiments of the present disclosure the system is configured to display a plurality of prior art references with or without graphical indicators, not limited to a first and a second prior art references. All plurality set of prior art references generated are provided with indicators for presenting the different to same, close or far or any other optional feedbacks to refine the generated results and evaluate them against the inputted technical concept or invention.

[0076] The plurality of generated prior arts references can further be modified based on the rating and brainstorming provided for its distinct features. The web browser displaying the set of results can be changed in real time and obtain more refined updated set of results. The generated set of prior art references in an embodiment can further be made comprehensive in nature by using the prompt boxes 206b, 207b, and 210c The prompt boxes, enable the user to provide text based on different options which further allow the user to further instruct the system 200 to display the second set of updated results based on rating and prompt instructions.

[0077] In an embodiment the prompt boxes 206b, 207b and 210c allow the user to provide real-time feedback and thus allowing refinement of results displayed. The end users can provide additional instructions or keywords in the prompt box, allowing the system to instantly refine and update the results based on this new input. Further, the end users can engage in an iterative process, gradually refining their search criteria until they achieve the desired set of updated prior art references.

[0078] The system is made user friendly and more flexible allowing the users gain more control over the searching, refinement and evaluation of the invention, specifying exactly what they want to see. This is particularly useful as the user can tailor the results to their specific needs, adding constraints or preferences directly by rating the prior references and inputting instructions into the prompt box.

[0079] The prompt boxes aid in increasing efficiency of the system 200. By refining results in real-time, users save time they would otherwise spend navigating through not so relevant set of results, which are not desirable by the end user. The system in accordance with the present disclosure, can retain wanted and most similar prior art references, presenting a more focused and similar set of results to be generated, displayed and thereby evaluated. The prompt box makes the search process more interactive and engaging, encouraging users to experiment with different instructions. By implementing the additional prompt box in the web browser provides a powerful tool for users to refine and customize search results in real-time, leading to more efficient, relevant, and satisfying search experiences.

[0080] FIG. 6, in accordance with some embodiments, illustrates a user interface where a title 201, description 202 and a category 212 are requested. FIG. 7, in accordance with some embodiments, illustrates a user interface where a title 201 and description 202 are requested.

[0081] In accordance with the present disclosure, a method 100 for evaluating an invention against prior art references is further disclosed in FIG. 2. The method includes allowing an end user to enter details about an invention into a web browser or software application within a user interface. In some embodiments, the user can enter the invention information into an invention disclosure form that is customizable. The invention disclosure form can be any form for requesting information about an invention. The user can enter information relating to any technical area in which the user is seeking to evaluate the invention against a plurality of prior art references. The description can be relating to details about an invention summarising the novel aspects of the invention. It can relate to functionality, performance or the like of a system or device or apparatus or hardware or software. This can include, but is not limited to, challenges in operation, efficiency, reliability, or compatibility. In an example embodiment, referring to FIG. 2 it is shown that the method includes receiving a title in an optional embodiment and preferably receiving description of the invention 101 in the user interface. In some embodiments, only description of the invention can be received 101. In an optional embodiment only title may be received in the user interface.

[0082] The method 100 in accordance with the present disclosure enables the end user to submit the received invention disclosure form input of title and / or description via a selector present in the user interface, which is a submit option 102.

[0083] The method 100 in accordance with the present disclosure, comprises a step of identifying similar prior arts based on the user provided description of the invention, by mapping and / or filtering against a database of publication materials and displaying the similar prior art references 103. This mapping and filtering can be done using an Al model such as an LLM and can be performed using vectors such as embeddings and cosine similarity. In an embodiment the state of art identified from both free and paid data sources that include publication materials such as patent information and non-patent literature is retained in the system.

[0084] In some embodiments, the method further comprises of comparing the received title and / or description of the invention with the identified publication materials from the databases and retain the similar results. In a specific embodiment the comparison includes mapping the description of the invention provided by the user against the concepts or prior art present in the identified publication materials and displaying the similar prior art references 103 that are already documented in the publication materials.

[0085] In one embodiment, the database of publication materials may include published patents, granted patents, expired patents, withdrawn patents, abandoned patents and / or non-patent literature.

[0086] In an embodiment, the method 100 of evaluating the invention against the prior art references is implemented using a generative artificial intelligence or an LLM trained on a diverse corpus of patents and scientific publications. The LLM can search as described above using various search methodologies and by comparing similarity of the invention disclosure (or aspects of the invention disclosure as described above) to publications such as prior art patent and scientific publications. The similarity can be performed by creating vectors such as embeddings and then comparing the vectors. The search can also be completed by generating the key aspects of the invention disclosure and the publications and mapping the similarity of the key aspects between the invention and the publications. In yet another embodiment, the method also comprises of evaluating the invention against both prior art references from the database and internally submitted inventions that are from an internal database within the organization, wherein the internal database includes previously submitted inventions that are unpublished. In a further embodiment the method uses NLP and / or an Al model to display both prior art references from the database and internally submitted inventions that are from an internal database within the organization.

[0087] In some embodiments, the method also retrieves results from multiple databases, including those in non-English languages. The method includes the step of queries multiple databases based on the provided input, which may include USPTO, EPO, WIPO, Google Scholar, IEEE Xplore and non- English databases that contain similar prior art in languages other than English. For any database that is in a non-English language different from the user's input, the system automatically detects the language of the identified documents. Machine translation, such as AL based machine translation, are then used to translate the non-English documents into the user's preferred language, e.g., English. This can involve both text-based translation and, in some cases, Optical Character Recognition (OCR) for images, scanned patents, or other documents that are not in a machine-readable format. Translation models such as those powered by Transformer-based architectures (e.g., Google’s Neural Machine Translation, DeepL, etc.) may be used to ensure high- quality translations.

[0088] The method comprises of generating and displaying a plurality of prior art references 104 by leveraging trained artificial intelligence and / or an LLM and subsequently displaying the same to the user via a web page of a web browser or a user interface of a software application. The priorart references are displayed in separate in a plurality of segments for example not limited to a web page with patentability score 105. The patentability score can include an invention report or patentability score report such as invention report card. A plurality of prior art references is provided with a patentability score that is auto generated by the system of the present disclosure.

[0089] In some embodiments, the patentability score of the invention is based on a mapping of the prior art references to the description of the invention represented as known to patentable (or old to new or some combination of descriptors). The score indicating closer to slide bar known denotes that the user inputted invention when mapped against the prior art shares significant similarities with the invention in terms of structure, function, or application. Further, the claims of the prior art may cover much of the same territory as the invention. Furthermore, the prior art may be in the same field or a closely related field as the invention. Yet, preferably the slide bar closer to old denotes that the differences between the prior art and the invention are minor and might be considered obvious by someone skilled in the field. The mapping can indicate what features are shown / not shown and present a graphical display of what features are shown versus not shown. This mapping can be used to determine the score based on the number of features that are shown. For example, if all the features are not shown or some are not shown and others only partially shown, it can display the indicator toward new or patentable. If all the features are known the graphical indicator can display as old or known.

[0090] In an embodiment, the score indicating closer to slide bar patentable or new denotes that the user inputted invention when mapped against the prior art shares differences from the invention in terms of structure, function, or application. The claims of the prior art may not overlap significantly with those of the invention. Further, the prior art is in a different or only tangentially related field from the invention. Yet, preferably the slide bar closer to new denotes that the differences between the prior art and the invention are substantial and non-obvious to someone skilled in the field. Accordingly, the slide bar indicating the old to new guides the end user in assessing the patentability of the user inputted invention.

[0091] The method 100 in accordance with the present disclosure, further comprises of receiving feedback 106 via feedback facilities such as different, same, close or far. The user can evaluate the displayed prior art references and provides feedback. For example, in one embodiment the user can also further refine the generated prior art reference against the invention based on his / her feedback in terms of an interactive chatbot. The user may interact or brainstorm with the user interface by giving direct instructions in the form of a chat to refine the generated results. The chatfunction enables refinement of results by real-time conversation with the user. The chat function in some embodiments, may ask follow up questions to better understand the user’s intent. The structured interaction using the chat function leads to more precise outcome and not similar publication materials may be filtered out. Further, based on the user’s response, the chat function may adjust and refine the direction of the conversation. In a further beneficial embodiment, the chat function streamlines the end users experience and continually sharpens the accuracy of its responses, leading to more similar publication materials to be displayed.

[0092] The method in accordance with the present disclosure comprises of displaying prior art references that includes a set of first graphical indicators for presenting the feedback options against the prior art references. The method also includes further entering instructions from the end user into a prompt box for further aiding in refining the displayed prior art references.

[0093] The method in some embodiments, allows the user to further refine the results by providing additional feedback facilities that will aid in evaluating the displayed prior art based on the similarity with the user inputted invention. For example, the prior art references displayed include a slide bar that indicates an option allowing the user to rate the prior art as different or same and close or far or any other feedback facility. In some embodiments the user may evaluate the resulted or generated prior art as different or same using the slide bar based on core elements and features of the invention and compare these core elements against the prior art displayed. The end user may determine if the prior art includes all the features of the proposed idea or user inputted invention in the same manner and combination and verify if the purpose and function of the prior art match those of the invention. Further, the end user may also check if the claims made in the prior art reference cover the same scope as the invention.

[0094] Accordingly, the end user may rate the prior art as different using the slide bars if the prior art lacks key elements or includes additional features that significantly change its purpose and function compared to the proposed idea, it is considered different. Further, the end user may rate the prior art as same using the slide bar if the prior art does not lack key elements or does not include substantial distinct features that significantly change its purpose and function compared to the proposed idea, it is considered same.

[0095] The method in accordance with the present disclosure comprises displaying prior art references that includes a prompt box, allowing the end user to enter instructions into the prompt box for further giving instructions as to how different the displayed prior art is against the userinputted invention. In some embodiments as shown in the prompt box allows the end user to effectively describe the features that are distinct in the invention when compared to the generated prior art.

[0096] The method in accordance with the present disclosure, upon receiving all the feedback 106 facilities, will further refine and display the updated prior art references 107. The updated set of prior art references are refined based on the various feedback facilities provided by the end user. This allows the end user to not only assess the novelty of the inputted invention but also assess the patentability of the invention based on a second set of prior art references that are gathered from a search of the database in response to the at least one rating.

[0097] FIG. 13 illustrates a user interface where a user can view multiple invention disclosures at the same time and keep track of invention disclosures as well as generating and viewing invention report cards (IRC). FIG 13 includes a reference identifier 640 that can include sequential or case reference numbers of the inventions. A simple sequential number is shown as an example, but more complex numerical or alphanumerical reference numbers can be used. For example, the reference identifier can be the initials of the company, something referring to patents, or a number and a country code. Invention name 642 can be a title or name of the invention for reference purposes. A status indication 644 can show information about where the invention is in the overall process. For example, a complete status indication 644 can denote that everything is done for the particular disclosure. Other types of status indications 644 can include filed, in process, newly received, pending, and the like. An overall patentability score 646 can be shown in this column where the patentability score is on a 0-10 scale. The summary 648 can be an Al generated summary using an LLM to generate the summary. Alternatively, the summary can be from the invention disclosure. The action column 650 provides user interaction buttons to generate a new invention report card or patentability report (as shown in FIGS. 10 and 11) or to view a previously run patentability report. As mentioned above, the invention disclosures can be uploaded to the system, transferred to the system, or entered via the system’s user interface.

[0098] In yet another embodiment, a method 500 of evaluating an invention against prior art references is disclosed in FIG. 10. The method includes allowing an end user to enter details about an idea and / or invention into a web browser or software application within a user interface, which can include a chatbot such as FIG. 4, relating to any technical area in which the user is seeking to evaluate the invention against a plurality of prior art references. The description can relate to details about an invention summarising the novel aspects of the invention. It can relate to functionality,performance or the like, but not limited to a system or device or apparatus or hardware or software or plants or chemistry or metallurgy. This can include, but is not limited to, challenges or problems. In an example embodiment, referring to FIG. 10 it is shown that the method includes receiving a title optionally and preferably receiving description 501 of the invention in the user interface. In some embodiments, only the description 501 of the invention can be received. In an optional embodiment, the title may be received in the user interface.

[0099] The method 500 in accordance with the present disclosure enables the end user to submit the received invention disclosure form input including title and description via a selector present in the user interface, which is a submit option 502. In some embodiments the invention disclosure form can include other fields such as date of invention, known prior art, inventors, related documents (which can be uploaded), and any other field desired.

[0100] The method 500 in accordance with the present disclosure, comprises a step of identifying similar prior art based on the user provided description of the invention, by searching 503 by mapping and / or filtering against a database(s) of publication materials and displaying the similar prior art references 504. The database(s) can reside on a server accessible by the user interface. In an embodiment the state of art identified from the database(s) includes both free and / or paid data sources that include publication materials such as patent information and non-patent literature is retained in the system for performing the method. The mapping and / or filtering can be done based on vectors (such as embeddings) and cosine similarity.

[0101] In some embodiments, the method further comprises searching 503 by comparing the received title and description of the invention with the identified publication materials from the database(s) and displaying the similar results 504. In a specific embodiment the comparison includes mapping the description of the invention provided by the user against the concepts or prior art present in the identified publication materials and retaining the similar prior art references that are already documented in the publication materials.

[0102] In one embodiment, the database of publication materials may include published patents, granted patents, expired patents, withdrawn patents, abandoned patents and / or non-patent literature.

[0103] In an embodiment, the method 500 of evaluating the invention against the prior art references is implemented using an artificial intelligence and / or an LLM trained on a diverse corpus of patents and scientific publications. In yet another embodiment, the method also comprises ofevaluating the invention against both prior art references from the database and internally submitted inventions that are from an internal database within the organization, wherein the internal database includes previously submitted inventions that are unpublished. In a further embodiment the method uses NLP to display both prior art references from the database and internally submitted inventions that are from an internal database within the organization. This ensures that the search is thorough and covers all possible similar and related prior art.

[0104] The method includes generating and displaying a plurality of prior art references 504 by leveraging trained artificial intelligence and / or an LLM and subsequently displaying the same to the user via a web page of a web browser or a user interface of a software application. The prior art references are displayed in separate in a plurality of segments for example not limited to a web page with patentability score 505. A plurality of prior art references is provided with a patentability score that is auto generated by the system of the present disclosure.

[0105] In some embodiments, the patentability score of the invention is based on a mapping of the prior art references to the description of the invention represented as known to patentable (or old to new, or some combination of descriptors). The score indicating closer to slide bar old or known denotes that the user inputted invention when mapped against the prior art shares significant similarities with the invention in terms of structure, function, or application. Further, the claims of the prior art may cover much of the same territory as the invention. Furthermore, the prior art may be in the same field or a closely related field as the invention. Yet, preferably the slide bar closer to old denotes that the differences between the prior art and the invention are minor and might be considered obvious by someone skilled in the field. The mapping can indicate what features are shown / not shown and present a graphical display of what features are shown versus not shown. This mapping can be used to determine the score based on the number of features that are shown. For example, if all the features are not shown or some are not shown and others only partially shown, it can display the indicator toward new or patentable. If all the features are known the graphical indicator can display as old or known.

[0106] In an embodiment, the score indicating closer to slide bar new or patentable denotes that the user inputted invention when mapped against the prior art shares differences from the invention in terms of structure, function, or application. The claims of the prior art may not overlap significantly with those of the invention. Further, the prior art is in a different or tangentially related field from the invention. Yet, preferably the slide bar closer to new or patentable denotes that the differences between the prior art and the invention are substantial and non-obvious to someoneskilled in the field. Accordingly, the slide bar indicating the old to new guides the end user in assessing the patentability of the user inputted invention.Example Machine and Computer readable Medium

[0107] FIG. 8 is a block diagram of machine in the example form of a computer system 300 within which instructions for causing the machine to perform any one or more of the methodologies discussed herein may be executed. In alternative embodiments, the machine operates as a standalone device or may be connected (e.g., networked) to other machines.

[0108] In a networked deployment, the machine may operate in the capacity of a server or a client machine in server-client network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine may be a personal computer (PC), a tablet PC, a set- top box (STB), a PDA, a cellular telephone, a web appliance, a network router, switch or bridge, or any machine capable of executing instructions (sequential or otherwise) that specify actions to be taken by that machine. Further, while only a single machine is illustrated, the term “machine” shall also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein.

[0109] In accordance with the present disclosure a computer readable medium with instructions for evaluating a generated technical concept(s) against prior art references is also disclosed. The example computer system 300 includes a processor 301 (e.g., a central processing unit (CPU), a graphics processing unit (GPU), and / or an Al processor), a main memory 302 and a static memory 303, which communicate with each other via a bus 312. The computer system 300 may further include a display unit 306 (e.g., a liquid crystal display (LCD) or a cathode ray tube (CRT)). The computer system 300 also includes an alphanumeric input device 307 (e.g., a keyboard), a user interface (UI) navigation or cursor control device 308 (e.g., a mouse), a disk drive unit 309, a signal generation device 311 (e.g., a speaker) and a network interface device 304 that is connected to a network 305.

[0110] The disk drive unit 309 includes a machine-readable medium 310 on which is stored one or more sets of data structures and instructions 313 (e.g., software) embodying or utilized by any one or more of the systems or methodologies or functions described herein. The instructions 313 may also reside, completely or at least partially, within the main memory 302 and / or within the processor 301 during execution thereof by the computer system 300, with the main memory 302 and the processor 301 also constituting machine-readable media.

[0111] While the machine-readable medium 310 is shown in an example embodiment to be a single medium, the term “machine-readable medium” may include a single medium or multiple media (e.g., a centralized or distributed database, and / or associated caches and servers) that store the one or more data structures or instructions 313. The term “machine-readable medium” shall also be taken to include any tangible medium that is capable of storing, encoding or carrying instructions for execution by the machine and that cause the machine to perform any one or more of the methodologies of the embodiments of the present disclosure, or that is capable of storing, encoding or carrying data structures utilized by or associated with such instructions. The machine-readable medium can store instructions and / or data in non-transitory manner. The term “machine-readable medium” shall accordingly be taken to include, but not be limited to, solid-state memories, and optical and magnetic media. Specific examples of machine-readable media include non-volatile memory, including by way of example semiconductor memory devices, e.g., Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), and flash memory devices; magnetic disks such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks.

[0112] The instructions 313 may further be transmitted or received over a communications network 305 using a transmission medium. The instructions 313 may be transmitted using the network interface device 304 and any one of a number of well-known transfer protocols (e.g., HTTP). Examples of communication networks include a local area network (“LAN”), a wide area network (“WAN”), the Internet, mobile telephone networks, Plain Old Telephone (POTS) networks, and wireless data networks (e.g., WiFi and WiMax networks). The term “transmission medium” shall be taken to include any intangible medium that is capable of storing, encoding or carrying instructions for execution by the machine, and includes digital or analog communications signals or other intangible media to facilitate communication of such software.

[0113] In a further detailed embodiment, the computer readable medium instructions are disclosed. In accordance with the present disclosure, the computer readable medium instructions when implemented allows an end user to enter description of an invention or new technical concepts in which the user is seeking to evaluate the invention against a plurality of generated prior art references into a user interface. The descriptions in accordance with an embodiment includes title of the invention and description of the invention. The title can be a crisp description of the invention in less than fifteen words, however not limiting to fifteen words in various embodiments. In an example embodiment, a title can be described as ‘improved stereo speaker’.

[0114] Further, the description can be relating to details about an invention summarising the novel aspects of the invention. It can relate to functionality, performance or the like of a system or device or apparatus or hardware or software. This can include, but is not limited to, challenges or problems. In a further embodiment, the description of the invention can be descriptive in text or specific keywords of the solution or invention can be provided. The invention can also be described textually or through specific keywords that succinctly encapsulate the domain of interest. This includes descriptive terms that outline the scope, focus, and specific novel aspects or objectives within a particular technical field.

[0115] The computer readable medium in accordance with the present disclosure further includes an option of allowing the end user to submit the entered title and description of the invention via a designated submit button.

[0116] The computer readable medium comprising a processor and a memory including instructions, further processes the user provided description of the invention to identify similar art by mapping and / or filtering against a database(s) of publication materials. The mapping and / or filtering can include using vectors such as embeddings and cosine similarity to retrieve similar publication materials. In an embodiment the state of art identified the database(s) that include free and / or paid data sources that include publication materials such as patent information and non-patent literature.

[0117] The computer readable medium in accordance with the present disclosure is configured to include a processor and a memory with specific instructions to be performed by a machine or computer. The user inputs a title and description of the invention they are interested for evaluation against the prior art references. The computer readable medium processes this description to understand the novelty aspect and keywords. The computer readable medium then map and / or filters this information against a database of publication materials to identify similar prior art. This database can include patent databases containing information about existing patents; and non-patent literature containing scientific papers, articles, and other publications that are not patents.

[0118] The computer readable medium in some embodiments, searches through database(s) that can include free and / or paid data sources to ensure a comprehensive search. This ensures that the search is thorough and covers all possible similar and related prior art. The computer readable medium identifies the state of the art from the databases. This involves comparing the user-provided title and / or description with the contents of the databases to find matches or similar or relatedinformation of patents and / or scientific literature. In some embodiments, the searching is performed using vectors (such as embeddings) and cosine similarity. The searching can be done by structuring the vectors and using techniques to quickly map the embeddings. By leveraging free and / or paid data sources, and considering both patent and non-patent literature, the computer readable medium aims to provide a comprehensive view of the current state of the art, thereby mapping and assessing the invention patentability against the prior art references.

[0119] The computer readable medium in accordance with the present disclosure further processes to compare the user input title and description with the identified publication materials from the databases. In a specific embodiment the comparison includes mapping the invention or technical concepts based on the user description against the concepts present in the identified publication materials. The computer readable medium further retains the concepts that are already documented in the publication materials based on the description and reflects the same to the end user via a user interface.

[0120] The computer readable medium in an embodiment maps the technical concepts or inventions against the concepts or features present in the identified publication materials. This involves extracting key technical concepts and details from the publication materials identified as relevant prior art and comparing them to the user inputted description with the extracted concepts from the publication materials to find similarities and / or overlaps. During the comparison process, the computer readable medium identifies any overlaps or similarities between the user inputted description of the invention against those already documented in the publication materials. The process can also involve an initial search with keywords than a mapping to narrow down the results. As such, the mapping can be the second stage. In some embodiments, the embeddings can be structured in a way such that mapping embeddings can be performed. The computer readable medium in every embodiment specifically retains the concepts that are already documented, or otherwise ensures to reflect such publication materials or prior art references that are found to be similar to or the same as existing documented or patented concepts for further rating by the end user. After retaining such documented concepts, the computer readable medium presents those concepts, which are considered to be related or similar or closely related to the description of the invention, including both patent and non-patent literature.

[0121] In one embodiment, the database of publication materials may include published patents, granted patents, expired patents, withdrawn patents, abandoned patents and / or non-patent literature.

[0122] In an embodiment, the evaluation of the new technical concepts or invention is implemented by an artificial intelligence such as an LLM is trained on a diverse corpus of patents and scientific publications. In every embodiment, the invention to be evaluated in accordance with the computer readable medium against what has been already existing in the state of art. The computer readable medium can use, in some embodiments, Natural Language processing to interpret the user provided inputs to evaluate against the prior art references. The generative artificial intelligence may be any one of but not limited to neural networks, SVMs, GANs or Rule-based systems. It can also include retrieval-augmented generation in the process of optimizing the large language model.

[0123] In some embodiments of the present disclosure, the computer readable medium receives the title and description of the invention or new technical concept, and the computer readable medium first processes this input to make it usable for further analysis. Natural Language Processing (NLP) techniques like tokenization, stemming, and lemmatization are used to break down and understand text. Alternatively, embedding techniques (like word2vec, GloVe, or BERT) convert words or sentences into numerical vectors that capture semantic meaning. Using the model prediction, the extracted features, the Al modelled system makes predictions based on the task it was trained to perform. The computer readable medium might combine multiple predictions or use additional logic to make a final decision and simple decision-making based on predefined rules. Combining predictions from multiple models to improve accuracy. Output generation finally, the Al system generates an output based on the predictions and decisions made.

[0124] In a further embodiment the computer readable medium used an LLM to display both prior art references from the database and internally submitted inventions that are from an internal database within the organization. In a specific embodiment, the internal database includes previously submitted inventions that are unpublished.

[0125] In a further detailed embodiment, the computer readable medium starts from the identified publication materials, evaluating the invention using vectors and / or natural language processing (NLP) techniques, identifying key phrases, keywords / phrases, features, methodologies, and innovations described. The computer readable medium generates evaluated the new technical concepts or invention based on the user's description, using algorithms designed to assess the novelty and non-obviousness of the user inputted innovative ideas within the specified technical area or description. These identified publication materials are then mapped against the inventions from to identify any similarities or matches. The computer readable medium further retains any publicationmaterials that match or closely resemble those found in the prior art, ensuring that the invention is accurately being evaluated to assess the inventions novelty and non-obviousness. Accordingly, the computer readable medium displays retained publication materials to the user, potentially with additional information regarding the prior art references thus generated.

[0126] In some embodiments, the computer readable medium also retrieves results from multiple databases, including those in non-English languages. The computer queries multiple databases based on the provided input, which may include USPTO, EPO, WIPO, Google Scholar, IEEE Xplore and non-English databases that contain similar prior art in languages other than English. For any database that is in a non-English language different from the user's input, the system automatically detects the language of the identified documents. Machine translation, such as AI- based machine translation, are then used to translate the non-English documents into the user's preferred language, e.g., English. This can involve both text-based translation and, in some cases, Optical Character Recognition (OCR) for images, scanned patents, or other documents that are not in a machine-readable format. Translation models such as those powered by Transformer-based architectures (e.g., Google’s Neural Machine Translation, DeepL, etc.) may be used to ensure high- quality translations.

[0127] The computer readable medium can alternatively instruct the trained generative artificial intelligence to determine the patentability of the user inputted invention against the pending and granted patents in force. In yet another embodiment, the computer readable medium also instructs the trained generative artificial intelligence to display prior art references from patents are no more legally in force. In a further embodiment, the system also instructs the trained generative artificial intelligence to display prior art references from non-patent literature.

[0128] The plurality of prior art references is generated and evaluated against the inputted description by leveraging trained generative artificial intelligence are presented to the user via a web page or software application display of the computer readable medium. The generated prior art references are displayed separately in a plurality of segments for example not limited three in number, of the web page or a software application with both auto-generated rating and user feedback facilities. A plurality of graphical indicators can be used with every generated prior art reference for allowing the end user to rate the generated prior art references based on its practicality and desirability (or any other review metric).

[0129] In an example embodiment, the user interface of the computer readable medium displays a most relevant figure and a summary of the prior art reference using generative artificial intelligence. In some embodiments the figure may be optionally displayed.

[0130] The user interface displays a patentability score of the invention based on a mapping of the prior art references to the description of the invention represented as old to new or known to patentable or some combination of descriptors. The score indicating closer to slide bar old or known denotes that the user inputted invention when mapped against the prior art shares significant similarities with the invention in terms of structure, function, or application. Further, the claims of the prior art may cover much of the same territory as the invention. Furthermore, the prior art may be in the same field or a closely related field as the invention. Yet, preferably the slide bar closer to old denotes that the differences between the prior art and the invention are minor and might be considered obvious by someone skilled in the field. The mapping can indicate what features are shown / not shown and present a graphical display of what features are shown versus not shown. This mapping can be used to determine the score based on the number of features that are shown. For example, if all the features are not shown or some are not shown and others only partially shown, it can display the indicator toward new or patentable. If all the features are known the graphical indicator can display as old or known.

[0131] In an embodiment, the score indicating closer to slide bar new or patentable denotes that the user inputted invention when mapped against the prior art shares differences from the invention in terms of structure, function, or application. The claims of the prior art may not overlap significantly with those of the invention. Further, the prior art is in a different or tangentially related field from the invention. Yet, preferably the slide bar closer to new denotes that the differences between the prior art and the invention are substantial and non-obvious to someone skilled in the field. Accordingly, the slide bar indicating the old to new guides the end user in assessing the patentability of the user inputted invention.

[0132] The user can in some embodiments, further refine the results by evaluating the generated prior art based on the similarity with the user inputted invention. In an example embodiment, the slide bar indicates an option allowing the user to rate the prior art as different or same. In some embodiments the user may evaluate the resulted or generated prior art as different or same using the slide bar based on elements and features of the invention and compare these elements against the prior art generated. The end user may determine if the prior art includes all the features of the invention or technical concept, in the same manner and combination and verify if the purposeand function of the prior art match those of the invention. Further, the end user may also check if the claims made in the prior art reference cover the same scope as the invention.

[0133] Accordingly, the end user may rate the prior art as different using the slide bar if the prior art lacks key elements or includes additional features that significantly change its purpose and function compared to the invention, it is considered different. Further, the end user may rate the prior art as same using the slide bar if the prior art does not lack key elements or does not include substantial distinct features that significantly change its purpose and function compared to the proposed idea, it is considered same.

[0134] Further additionally, in some embodiments, the user may also be provided with a prompt box allowing the end user to effectively describe the features that are distinct in the invention when compared to the generated prior art. The prompt box has been specifically configured for the end user to input further instructions to refine the generated prior art. In an embodiment the prompt boxes allow the user to provide real-time feedback and thus allowing refinement of results displayed. The end users can provide additional instructions or keywords in the prompt box, allowing the system to instantly refine and update the results based on this new input. Further, the end users can engage in an iterative process, gradually refining their prior art displayed until they achieve the desired results. Upon inputting such text, the computer readable medium will further refine the results based in the indicator and prompt text inputted. This allows the end user to assess the patentability of the invention based on a second set of prior art references that are gathered from a search of the database in response to the at least one rating.

[0135] Further in an embodiment, the computer readable medium can generate a first prior art including a set of first graphical indicators for presenting the difference or closeness of the first generated prior art. It also configured to further include a prompt box. The prompt box has been specifically configured for the end user to input further instructions to refine the generated prior art in some embodiments. In multiple embodiments, different graphical indicators can be used to receive feedback from the user. For example, a sliding bar, a set of circles, a set of stars, or any other feedback graphical indicator can be used.

[0136] In some embodiments of the present disclosure the computer readable medium is configured to display a plurality of prior art references with or without graphical indicators, not limited to a first and a second prior art references. All plurality set of prior art references generated are provided with indicators for presenting the different to same, close to far and other feedbackfacilities. In an alternate embodiment, the generated plurality set of prior art references may be void of graphical indicators.

[0137] The plurality of generated prior arts references can further be modified based on the rating provided for its distinct features, different or same and close or far, and chatbot facility. The web browser displaying the set of results can be changed in real time obtain more refined updated set of results. The generated set of prior art references in an embodiment can further be made comprehensive in nature by using the prompt boxes. The prompt boxes, enable the user to provide text based on different options which further allow the user to further instruct the computer readable medium to display the second set of updated results based on rating and prompt instructions.

[0138] In an embodiment the prompt boxes allow the user to provide real-time feedback and thus allowing refinement of results displayed. The end users can provide additional instructions or keywords in the prompt box, allowing the computer readable medium to instantly refine and update the results based on this new input. Further, the end users can engage in an iterative process, gradually refining their search criteria until they achieve the desired set of updated prior art references.

[0139] The computer readable medium, in accordance with the present disclosure is made user friendly and more flexible allowing the users gain more control over the searching, refinement and evaluation of the invention, specifying exactly what they want to see. This is particularly useful as the user can tailor the results to their specific needs, adding constraints or preferences directly by rating the prior references and inputting instructions into the prompt box.

[0140] The prompt boxes aid in increasing efficiency of the computer readable medium. By refining results in real-time, users save time they would otherwise spend navigating through not so relevant set of results, which are not desirable by the end user. The computer readable medium in accordance with the present disclosure, can retain wanted and most similar prior art references, presenting a more focused and similar set of results to be generated, displayed and thereby evaluated. The prompt box makes the search process more interactive and engaging, encouraging users to experiment with different instructions. By implementing the additional prompt box in the web browser provides a powerful tool for users to refine and customize search results in real-time, leading to more efficient, relevant, and satisfying search experiences.

[0141] Further FIG. 9 illustrates a network component according to an example embodiment. The computer network system 400 includes patent management system and user device or userdevice 405 communicatively coupled via network 404. In an embodiment, patent management system includes server 401 , publication (e.g., patent) server 402, and database management server 403, which may be used to manage at least operations database and file server. Patent management system including the server 401 may be implemented as a distributed system; for example, one or more elements of the patent management system may be located across a wide-area network (WAN) from other elements of patent management system. As another example, a server (e.g., web server, file server, database management server) may represent a group of two or more servers, cooperating with each other, provided by way of a pooled, distributed, or redundant computing model. Network 404, may include local-area networks (LAN), wide-area networks (WAN), wireless networks (e.g., cellular network), the Public Switched Telephone Network (PSTN) network, ad hoc networks, personal area networks (e.g., Bluetooth) or other combinations or permutations of network protocols and network types. The network 404 may include a single local area network (LAN) or wide-area network (WAN), or combinations of LAN's or WAN's, such as the Internet. The various devices / systems coupled to network 404 may be coupled to network 404 via one or more wired or wireless connections.

[0142] Server 401, may communicate with file server to publish or serve files stored on file server. Server 401 may also communicate or interface with the publication server 402 to enable web-based or software applications and presentation of information. For example, publication server 402 may consist of scripts, patent applications, scientific publications, or library files that provide primary or auxiliary functionality to server 401 (e.g., multimedia, file transfer, or dynamic interface functions). Applications may include code, which when executed by one or more processors, run the tools of patent management system. In addition, publication server 402 may also provide some or the entire interface for server 401 to communicate with one or more of the other servers in patent management system (e.g., database management server).

[0143] The server 401, either alone or in conjunction with one or more other computers in patent management system, may provide a user-interface to user terminal or user device 405 for interacting with the tools of patent management system stored in publication server 402. The userinterface may be implemented using a variety of programming languages or programming methods, such as HTML (HyperText Markup Language), VBScript (Visual Basic® Scripting Edition), JavaScript™, XML® (Extensible Markup Language), XST™ (Extensible Stylesheet Language Transformations), AJAX (Asynchronous JavaScript and XML), Java™, JFC (Java™ Foundation Classes), and Swing Application Programming Interface for Java™).

[0144] User terminal or user device 405 may be a personal computer or mobile device. In an embodiment, user device 405 includes a program to interface with patent management system. The program may include commercial software, custom software, open source software, freeware, shareware, or other types of software packages. In an embodiment, the client program includes a thin client designed to provide query and data manipulation tools for a user of user device 405. The program may interact with a server program hosted by, for example, publication server 402. Additionally, the program may interface with database management server 403.

[0145] The inventors of the present disclosure have optimised the system and methods to evaluate unique technical concepts or technical concepts or inventions against a plurality of prior art references, using artificial intelligence. The embodiments in accordance with every aspect of the disclosure have automated the complex process of evaluating the novel concepts by saving time and resources. The system(s) developed by the inventors specifically, evaluate and assess the patentability of new technical concepts or inventions against the generated set of plurality of prior art references.

[0146] Please note that embodiments of the present disclosure are described in detail with reference to the accompanying Figures. Like elements in the various figures may be denoted by like reference numerals for consistency. Further, in the following detailed description of embodiments of the present disclosure, numerous specific details are set forth in order to provide a more thorough understanding of the claimed subject matter. However, it will be apparent to one of ordinary skill in the art that the embodiments disclosed herein may be practiced without these specific details. In other instances, well-known features have not been described in detail to avoid unnecessarily complicating the description. Additionally, it will be apparent to one of ordinary skill in the art that the scale of the elements presented in the accompanying Figures may vary without departing from the scope of the present disclosure.

[0147] As used herein the phrase “technical concept” or “invention” or “engineering principle” or “unique concept” or “novel ideas” or “new ideas” or “new technical concept” can be used interchangeably, refers to an innovative idea or approach that represents a departure from existing methods or technologies. Specifically, it may be referred as a novel idea or methodology within engineering that introduces a distinct approach to solving a problem or achieving a specific goal. It typically integrates cutting-edge principles, technologies, or interdisciplinary insights to create innovative solutions that surpass traditional methods in efficiency, effectiveness, or scope.Such concepts not only address current challenges but also inspire future developments and applications across various industries and disciplines.

[0148] As used herein the phrase “technical area” or “description input” or “description” can be used interchangeably, refer to solutions that are developed or under progress for development in addressing existing problems. This encompasses areas where current methods or technologies are inadequate, offering scope for improvement and innovation with certain novel aspects.

[0149] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, for example, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “contains”, “containing”, “includes”, “including,” “comprises”, and / or “comprising,” and variations thereof, when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0150] Terms of orientation are used herein merely for purposes of convention and referencing and are not to be construed as limiting. However, it is recognized these terms could be used with reference to an operator or user. Accordingly, no limitations are implied or to be inferred. In addition, the use of ordinal numbers (e.g., first, second, third, etc.) is for distinction and not counting. For example, the use of “third” does not imply there must be a corresponding “first” or “second.” Also, if used herein, the terms “coupled” or “coupled to” or “connected” or “connected to” or “attached” or “attached to” may indicate establishing either a direct or indirect connection, and is not limited to either unless expressly referenced as such.

[0151] The words and phrases used herein should be understood and interpreted to have a meaning consistent with the understanding of those words and phrases by those skilled in the relevant art. No special definition of a term or phrase, i.e., a definition that is different from the ordinary and customary meaning as understood by those skilled in the art, is intended to be implied by consistent usage of the term or phrase herein. To the extent that a term or phrase is intended to have a special meaning, i.e., a meaning other than the broadest meaning understood by skilled artisans, such a special or clarifying definition will be expressly set forth in the specification in a definitional manner that provides the special or clarifying definition for the term or phrase. It must also be noted that, asused in the specification and the appended claims, the singular forms "a," "an," and "the" include plural references unless otherwise specified.

[0152] For example, the following discussion contains a non-exhaustive list of definitions of several specific terms used in this disclosure (other terms may be defined or clarified in a definitional manner elsewhere herein). These definitions are intended to clarify the meanings of the terms used herein. It is believed that the terms are used in a manner consistent with their ordinary meaning, but the definitions are nonetheless specified here for clarity.

[0153] As used in this specification and the claims, the terms “comprising,” “containing,” or “including” mean that at least the named compound, element, material, particle, or method step is present in the composition, the article, or the method, but does not exclude the presence of other compounds, elements, materials, particles, or method steps even if the other such compounds, elements, materials, particles, or method steps have the same function as that which is named, unless expressly excluded in the claims. It is also to be understood that the mention of one or more method steps does not preclude the presence of additional method steps before or after the combined recited steps or intervening method steps between those steps expressly identified.

[0154] Moreover, it is also to be understood that the lettering of process steps or ingredients is for identifying discrete activities or ingredients and the recited lettering can be arranged in any sequence, unless expressly indicated.

[0155] For the purpose of the present description and of the claims which follow, except where otherwise indicated, numbers expressing amounts, quantities, percentages, and so forth, are to be understood as being modified by the term “about”. Also, ranges include any combination of the maximum and minimum points disclosed and include any intermediate ranges therein, which may or may not be specifically enumerated herein.

[0156] While the disclosure has described several exemplary embodiments, it will be understood by those skilled in the art that various changes can be made, and equivalents can be substituted for elements thereof, without departing from the spirit and scope of the invention. In addition, many modifications will be appreciated by those skilled in the art to adapt a particular instrument, situation, or material to embodiments of the disclosure without departing from the essential scope thereof. Therefore, it is intended that the invention not be limited to the particular embodiments disclosed, or to the best mode contemplated for carrying out this invention, but that the invention will include all embodiments falling within the scope of the appended claims.Moreover, reference in the appended claims to an apparatus or system or a component of an apparatus or system being adapted to, arranged to, capable of, configured to, enabled to, operable to, or operative to perform a particular function encompasses that apparatus, system, or component, whether or not it or that particular function is activated, turned on, or unlocked, as long as that apparatus, system, or component is so adapted, arranged, capable, configured, enabled, operable, or operative.Example Embodiments

[0157] 1) A system for evaluating an invention against prior art references comprising: at least one processor; and a memory including instructions that, when executed by the at least one processor, cause the at least one processor to: receive a description of the invention in a user interface; display in the user interface a set of prior art references that are gathered from a search of a database of publication materials that in response to the description are most similar; receive in the user interface at least one feedback of differences of at least one of the prior art references; and display in the user interface a second set of prior art references that are gathered from a search of the database in response to the at least one feedback.

[0158] The above system of 1, further comprising displaying in the user interface a patentability score of the invention based on a mapping of the prior art references to the description of the invention. Further, wherein the patentability score of the invention against the prior art references indicates novelty of the invention.

[0159] The system of 1, further comprising displaying both prior art references from the database and internally submitted inventions that are from an internal database within an organization, wherein the internal database includes previously submitted inventions that are unpublished. The system of 1, further comprising displaying in the user interface using generative artificial intelligence a most relevant figure and a summary of the prior art references. Further, wherein the summary of the prior art references is generated based in part on the description of the invention.

[0160] The system of 1, wherein the at least one feedback includes receiving in the user interface at least one description of what is different for at least one of the prior art references, and wherein the displaying the second set of prior art references are gathered in response to at least one rating and the at least one description of what is different.

[0161] 2) A system for evaluating an invention against prior art references comprising: at least one processor; and a memory including instructions that, when executed by the at least one processor, cause the at least one processor to: receive a description of the invention; provide a plurality of prior art publications that are gathered from a search of a database of publication materials that in response to the description are most similar; and provide a patentability score of the invention.

[0162] 3) The system of 2, wherein the receive a description, provide a plurality, and provide a patentability score are on a user interface.

[0163] 4) The system of 2, wherein the receive a description is received from another system and the patentability score is provided in a report.

[0164] 5) The system of 2, wherein the patentability score is provided by at least one of graphically and numerically.

[0165] 6) The system of 5, wherein the patentability score is based on a novelty indicator and an obviousness indicator, wherein the novelty indicator is based on a similarity of at least one prior art publication and the obviousness indicator is based on a similarity of a plurality of prior art publications.

[0166] 7) The system of 6, wherein the patentability score is further based on a determined number of unique elements in the description.

[0167] 8) The system of 7, wherein the determined number of unique elements are determined by converting text to embeddings and cosine similarity can be used for comparisons.

[0168] 9) The system of 6, wherein the patentability score is further based on robustness of the description including at least one of number of words, technical depth, and completeness.

[0169] 10) The system of 2, wherein the description is from an invention disclosure form.

[0170] 11) The system of 2, wherein the search uses a cosine similarity of embeddings to determine prior art publications to provide.

Claims

CLAIMSWhat is claimed is:

1. A system for evaluating an invention against prior art references comprising: at least one processor; and a memory including instructions that, when executed by the at least one processor, cause the at least one processor to: receive a description of the invention in a user interface; display in the user interface a set of prior art references that are gathered from a search of a database of publication materials that in response to the description are most similar; and display in the user interface a patentability score of the invention based on a mapping of the prior art references to the description of the invention.

2. The system of claim 1 , wherein the patentability score of the invention against the prior art references indicates novelty and non-obviousness of the invention.

3. The system of claim 1 , further comprising receiving in the user interface at least one feedback of the mapping of at least one of the prior art references; and display in the user interface a second set of prior art references that are gathered from a search of the database in response to the at least one feedback.

4. The system of claim 3, wherein the at least one feedback includes receiving in the user interface at least one description of what is different for at least one of the prior art references, and wherein the displaying the second set of prior art references are gathered in response to at least one rating and the at least one description of what is different.

5. The system of claim 1, further comprising displaying both prior art references from the database and internally submitted inventions that are from an internal database within an organization, wherein the internal database includes previously submitted inventions that are unpublished.

6. The system of claim 1, further comprising displaying in the user interface using artificial intelligence a most relevant figure and a summary of the prior art references.

7. The system of claim 6, wherein the summary of the prior art references is generated based on the description of the invention.

8. A method of evaluating an invention against prior art references comprising: receiving a description of the invention in a user interface; displaying in the user interface a set of prior art references that are gathered from a search of a database of publication materials that in response to the description are most similar; and displaying in the user interface a patentability score of the invention based on a mapping of the prior art references to the description of the invention.

9. The method of claim 8, wherein the patentability score of the invention against the prior art references indicates novelty and non-obviousness of the invention.

10. The method of claim 9, further comprising receiving in the user interface at least one feedback of a difference of at least one of the prior art references; and displaying in the user interface a second set of prior art references that are gathered from a search of the database in response to the at least one feedback.

11. The method of claim 8, wherein at least one feedback includes receiving in the user interface at least one description of what is different for at least one of the prior art references, and wherein the displaying the set of prior art references are gathered in response to at least one rating and the at least one description of what is different.

12. The method of claim 8, further comprising displaying both prior art references from the database and internally submitted inventions that are from an internal database within an organization, wherein the internal database includes previously submitted inventions that are unpublished.

13. The method of claim 8, further comprising displaying in the user interface using generative artificial intelligence a most relevant figure and a summary of the prior art references.

14. The method of claim 13, wherein the summary of the prior art references is generated based on the description of the invention.

15. A computer readable medium with instructions for evaluating an invention against prior art references comprising: receiving a description of the invention; displaying a set of prior art references that are gathered from a search of a database of publication materials that in response to the description are most similar; and displaying a patentability score of the invention based on a mapping of the prior art references to the description of the invention.

16. The computer readable medium of claim 15, wherein the patentability score of the invention against the prior art references indicates novelty and non-obviousness of the invention.

17. The computer readable medium of claim 16, further comprising receiving in a user interface at least one rating of a similarity of at least one of the prior art references; and displaying in the user interface a second set of prior art references that are gathered from a search of the database in response to the at least one rating.

18. The computer readable medium of claim 15, wherein at least one feedback includes receiving in a user interface at least one description of what is different for at least one of the prior art references, and wherein the displaying the set of prior art references are gathered in response to at least one rating and the at least one description of what is different.

19. The computer readable medium of claim 15, further comprising displaying both prior art references from the database and internally submitted inventions that are from an internal database within an organization, wherein the internal database includes previously submitted inventions that are unpublished.

20. The computer readable medium of claim 15, further comprising displaying in a user interface using generative artificial intelligence a most relevant figure and a summary of the prior art references.

21. The computer readable medium of claim 15, wherein a summary of the prior art references is generated based on the description of the invention.

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