DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1, 7, and 8 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Specifically, it is unclear as to how “content to be inputted into a framework capable of being used in thinking about the target” assists the user in thinking about a target (i.e. matters subjected to decision making, matters to be analyzed, issues to be addressed for the solution, and themes for use in generating ideas, etc.). The claims appear to lack further limitations which describe what is being done with the generated content once it is inputted into the framework.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
As to independent claims 1, 7, and 8:
At Step 1:
The claims are directed to a “apparatus”, “method”, and “medium” and thus directed to a statutory category.
At Step 2A, Prong One:
The claims recite the following limitations directed to an abstract idea:
“thinking about the target” as drafted recites a mental process. One can mentally evaluate a target.
At Step 2A, Prong Two:
The claims recite the following additional elements:
That the apparatus, method, and medium are performed by a “An information processing apparatus comprising at least one processor”, “A computer-readable, non-transitory storage medium”, “a computer”, and “a generative model trained by performing machine learning” which is a high-level recitation of a generic computer components and represents mere instructions to apply on a computer as in MPEP 2106.05(f), which does not provide integration into a practical application.
“receiving an input of target-related information related to a target of thinking” is insignificant extra-solution activity. This limitation is recited as receiving data (i.e. mere data gathering). This does not provide integration into a practical application.
“generate, using the target-related information, content to be inputted into a framework capable of being used” is insignificant extra-solution activity. This limitation is recited as providing/presenting data. This does not provide integration into a practical application.
Viewing the additional limitations together and the claim as a whole, nothing provides integration into a practical application.
At Step 2B:
The conclusions for the mere implementation using a computer are carried over and do not provide significantly more.
With respect to the “receiving” identified as extra-solution activity in Step 2A Prong 2, when re-evaluated as Step 2B this limitation is well-understood, routine, and conventional and remains insignificant extra-solution activity. See MPEP 2106.05(d)(II) “i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network).” To the extent this is a request for “input” on records that is well-understood, routine and conventional. See MPEP 2106.05(d)(II) “iii. Electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225, 110 USPQ2d 1984 (2014) (creating and maintaining "shadow accounts"); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log).”
With respect to the “generating” identified as extra-solution activity in Step 2A Prong 2, when re-evaluated as Step 2B this limitation is well-understood, routine, and conventional and remains insignificant extra-solution activity. See MPEP 2106.05(d)(II) “iv. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93.”
With respect to the “generative model trained by performing machine learning” identified as extra-solution activity in Step 2A Prong 2, when re-evaluated as Step 2B this limitation is well-understood, routine, and conventional and remains insignificant extra-solution activity. Specifically, Applicant’s specification [0018]-[0019] merely mentions that The generative model may be any model that has been subjected to machine learning, a general- purpose model applicable to other applications, or may be a model specialized in generating content, or a model referred to
as so-called generative artificial intelligence (AI). There is nothing in the specification that states that the generative model is anything more than a well-understood, routine, and conventional machine learning model. The specification also fails to identify an improvement to machine learning technology, which would provide significantly more.
Looking at the claims as a whole does not change this conclusion and the claim is ineligible.
As to dependent claims 2-6:
At Step 1:
The claims are directed to a “apparatus”, “method”, and “medium” and thus directed to a statutory category.
At Step 2A, Prong One:
The claims recite the following limitations directed to an abstract idea:
“determines a candidate for the framework selected by the user from among the presented candidates for the framework as the framework in accordance with the target-related information” as drafted recites a mental process. One can mentally evaluate and judge whether a candidate among other candidates is better suited.
“determining the framework in accordance with the target-related information” as drafted recites a mental process. One can mentally evaluate and judge which framework best suits a target-related information.
At Step 2A, Prong Two:
The claims recite the following additional elements:
That the apparatus, method, and medium are performed by a “An information processing apparatus comprising at least one processor” and “a generative model trained by performing machine learning” which is a high-level recitation of a generic computer components and represents mere instructions to apply on a computer as in MPEP 2106.05(f), which does not provide integration into a practical application.
“presenting the framework with the generated content inputted” is insignificant extra-solution activity. This limitation is recited as providing/presenting data. This does not provide integration into a practical application.
“generate content to be inputted into the framework determined in the framework determination process” is insignificant extra-solution activity. This limitation is recited as providing/presenting data. This does not provide integration into a practical application.
“generates a prompt for instructing to provide one or more candidates for the framework in accordance with the target-related information” is insignificant extra-solution activity. This limitation is recited as providing/presenting data. This does not provide integration into a practical application.
“presents, to a user of the information processing apparatus, the one or more candidates provided in response to the input of the prompt into a trained language model” is insignificant extra-solution activity. This limitation is recited as providing/presenting data. This does not provide integration into a practical application.
“presents the framework with the content inputted in a presentation mode that is in accordance with an attribute of a subject to whom the framework is presented” is insignificant extra-solution activity. This limitation is recited as providing/presenting data. This does not provide integration into a practical application.
“generates, using the target- related information, a prompt for instructing the generative model to generate content, and inputs the prompt into the generative model, to cause the generative model to generate the content” is insignificant extra-solution activity. This limitation is recited as providing/presenting data. This does not provide integration into a practical application.
Viewing the additional limitations together and the claim as a whole, nothing provides integration into a practical application.
At Step 2B:
The conclusions for the mere implementation using a computer are carried over and do not provide significantly more.
With respect to the “presenting” identified as extra-solution activity in Step 2A Prong 2, when re-evaluated as Step 2B this limitation is well-understood, routine, and conventional and remains insignificant extra-solution activity. See MPEP 2106.05(d)(II) “i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network).” To the extent this is a request for “input” on records that is well-understood, routine and conventional. See MPEP 2106.05(d)(II) “iii. Electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225, 110 USPQ2d 1984 (2014) (creating and maintaining "shadow accounts"); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log).”
With respect to the “generating” identified as extra-solution activity in Step 2A Prong 2, when re-evaluated as Step 2B this limitation is well-understood, routine, and conventional and remains insignificant extra-solution activity. See MPEP 2106.05(d)(II) “iv. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93.”
With respect to the “generative model to cause the generative model to generate the content” identified as extra-solution activity in Step 2A Prong 2, when re-evaluated as Step 2B this limitation is well-understood, routine, and conventional and remains insignificant extra-solution activity. Specifically, Applicant’s specification [0018]-[0019] merely mentions that The generative model may be any model that has been subjected to machine learning, a general- purpose model applicable to other applications, or may be a model specialized in generating content, or a model referred to as so-called generative artificial intelligence (AI). There is nothing in the specification that states that the generative model is anything more than a well-understood, routine, and conventional machine learning model. The specification also fails to identify an improvement to machine learning technology, which would provide significantly more.
Looking at the claims as a whole does not change this conclusion and the claim is ineligible.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-8 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Heidenreich et al (US 7962430 B1).
As to claims 1, 7, and 8, Heidenreich teaches A thinking support method comprising:
a reception process of receiving an input of target-related information related to a target of thinking, the process being carried out by at least one processor (Heidenrich column 11, lines 58-60 discloses inputting or defining an issue, question or problem and its descriptors (i.e. input of target-related information), with subsequent focus on developing data 46 and information constructs 42 and analysis constructs 44. Heidenrich in column 12, lines 46-50 discloses constructing meaning about the problem, issue, topic or area of interest, and/or adding the user's own thinking, which may include the user's creative thoughts, theories, conclusions, and/or perspectives or other similar items. Processing is defined in column 13, line 62 through column 14, line 18); and
a generation control process of causing a generative model trained by performing machine learning to generate, using the target-related information, content to be inputted into a framework capable of being used in thinking about the target, the process being carried out by the at least one processor (Heidenrich column 13, lines 40-43 discloses the ITKC (i.e. generative model) that the user develops is an ongoing (i.e. learned) detailed and high level, highly related construction that encapsulates their thinking and knowledge work and can therefore be tracked (i.e. learned) and used as the basis for guidance (i.e. framework). Heidenrich column 13, lines 34-43 discloses a linkage manager 600 or like module which updates linkages among and between the components of the integrated construct and groups of components, in some cases automatically and in other cases in response to user actions; ; (vi) an update manager 700 or like module which updates the content and structure of the integrated construct in response to user actions; and (vii) the content of the integrated construct and its associated structure or formats, stored in a suitable form of data storage and retrieval mechanisms 800. Finally, Heidenrich column 29, line 26 through column 33, line 33 discloses guiding (i.e. frameworking) the thinking and knowledge activities for a user to develop their thinking about an arbitrary problem through evaluating the user's actions and progress, and determining suggestions based on the archetype structure and archetype process. The Process Manager acts as an expert system component of the present invention, orchestrating a dialogue and providing suggestions to the user about the generalized inquiry project and problem solving process.).
As to claim 2, Heidenrich teaches a presentation process of presenting the framework with the generated content inputted (Heidenrich in column 29, line 26 through column 33, line 33 discloses visual depiction of the archetype project structure (representing content, structure, relationships, and thinking and working process) and the more detailed thinking modes or views provided by the present invention provide ongoing guidance and feedback to the user regarding the portions of thinking process they have done and should consider doing (i.e. presenting framework based on inputted issue, question or problem and its descriptors).).
As to claim 3, Heidenrich teaches a framework determination process of determining the framework in accordance with the target-related information, and in the generation control process, the at least one processor causes the generative model to generate content to be inputted into the framework determined in the framework determination process (Heidenrich column 13, lines 40-43 discloses the ITKC (i.e. generative model) that the user develops is an ongoing (i.e. learned) detailed and high level, highly related construction that encapsulates their thinking and knowledge work and can therefore be tracked (i.e. learned) and used as the basis for guidance (i.e. framework). Heidenrich column 13, lines 34-43 discloses a linkage manager 600 or like module which updates linkages among and between the components of the integrated construct and groups of components, in some cases automatically and in other cases in response to user actions; ; (vi) an update manager 700 or like module which updates the content and structure of the integrated construct in response to user actions; and (vii) the content of the integrated construct and its associated structure or formats, stored in a suitable form of data storage and retrieval mechanisms 800. Finally, Heidenrich column 29, line 26 through column 33, line 33 discloses guiding (i.e. frameworking) the thinking and knowledge activities for a user to develop their thinking about an arbitrary problem through evaluating the user's actions and progress, and determining suggestions based on the archetype structure and archetype process. The Process Manager acts as an expert system component of the present invention, orchestrating a dialogue and providing suggestions to the user about the generalized inquiry project and problem solving process.).
As to claim 4, Heidenrich teaches the framework determination process, the at least one processor generates a prompt for instructing to provide one or more candidates for the framework in accordance with the target-related information, presents, to a user of the information processing apparatus, the one or more candidates provided in response to the input of the prompt into a trained language model, and determines a candidate for the framework selected by the user from among the presented candidates for the framework as the framework in accordance with the target-related information (Heidenrich in column 29, line 26 through column 33, line 33 discloses visual depiction of the archetype project structure (representing content, structure, relationships, and thinking and working process) and the more detailed thinking modes or views provided by the present invention provide ongoing guidance and feedback to the user regarding the portions of thinking process they have done and should consider doing (i.e. presenting framework based on inputted issue, question or problem and its descriptors). Heidenrich also discloses providing of thinking and working prompts or suggestions that are related to the specific portion of work being conducted by the user. The process manager suggestor may evaluate the user event history. For example, if most user events have been occurring in the research and data gathering regions of the system, or if the user has focused primarily on a topic by topic view and has not yet looked at the meaning that has been developing, the present invention may suggest the user "go to" the complementary or so far little used views or regions next. In one embodiment of the invention, the process manager provides a user such as a teacher with the ability to set parameters for how much emphasis the student should place on different thinking and knowledge activities and views, or how much time is to be spent accordingly, as discussed elsewhere herein. The Process Manager acts as an expert system component of the present invention, orchestrating a dialogue and providing suggestions (i.e. prompts) to the user about the generalized inquiry project and problem solving process).
As to claim 5, Heidenrich teaches the presentation process, the at least one processor presents the framework with the content inputted in a presentation mode that is in accordance with an attribute of a subject to whom the framework is presented (Heidenrich in column 29, line 26 through column 33, line 33 discloses visual depiction of the archetype project structure (representing content, structure, relationships, and thinking and working process) and the more detailed thinking modes or views provided by the present invention provide ongoing guidance and feedback to the user regarding the portions of thinking process they have done and should consider doing (i.e. presenting framework based on inputted issue, question or problem and its descriptors).).
As to claim 6, Heidenrich teaches the generation control process, the at least one processor generates, using the target- related information, a prompt for instructing the generative model to generate content, and inputs the prompt into the generative model, to cause the generative model to generate the content (Heidenrich column 13, lines 40-43 discloses the ITKC (i.e. generative model) that the user develops is an ongoing (i.e. learned) detailed and high level, highly related construction that encapsulates their thinking and knowledge work and can therefore be tracked (i.e. learned) and used as the basis for guidance (i.e. framework). Heidenrich column 13, lines 34-43 discloses a linkage manager 600 or like module which updates linkages among and between the components of the integrated construct and groups of components, in some cases automatically and in other cases in response to user actions; ; (vi) an update manager 700 or like module which updates the content and structure of the integrated construct in response to user actions; and (vii) the content of the integrated construct and its associated structure or formats, stored in a suitable form of data storage and retrieval mechanisms 800. Finally, Heidenrich column 29, line 26 through column 33, line 33 discloses guiding (i.e. frameworking) the thinking and knowledge activities for a user to develop their thinking about an arbitrary problem through evaluating the user's actions and progress, and determining suggestions based on the archetype structure and archetype process. The Process Manager acts as an expert system component of the present invention, orchestrating a dialogue and providing suggestions to the user about the generalized inquiry project and problem solving process.).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
WATANABE (US 20220284329 A1) - A non-transitory computer-readable recording medium stores a program for causing a computer to execute a process, the process includes calculating a contribution degree of each of a plurality of pieces of data each including a plurality of variables, with respect to a prediction result that is output by a machine-learning model in response to input of the plurality of pieces of data, by using an explanatory model generated based on the prediction result and the plurality of pieces of data, selecting a specific variable from among the plurality of variables, determining specific data among the plurality of pieces of data based on a value of the specific variable of each of the plurality of pieces of data and the contribution degree of each of the plurality of pieces of data, and outputting the specific data as explanatory information of the prediction result.
Heidenreich et al (US 8712946 B1) - Embodiments of the invention provide system and methods for new approaches for facilitating the development of and transferring of user thinking and understanding about an arbitrary problem, in some embodiments through creating new interactive forms of thinking and knowledge constructs as enhanced interactive and/or visually appealing presentational and working forms. Some embodiments involve the development of an interactive construct by one or more users for use by one or more other users (as in educational or professional development situations, for example). Some embodiments include the interfacing with, receiving input from, or enabling output to other systems, processor or device enabled methods, devices, objects, controllers, or other items.
Higgins et al (US 7730009 B1) - A system and methods for enhanced search are enabled by archetypes that improve the relevancy of the search arguments utilized, as well as the search results received, in response to a query. The system in preferred embodiments applies archetypes to several points within the total search process. The system receives and evaluates a query, and in response to that query may generate additional suggested areas for investigation, as embodied in additional queries, knowledge constructs, or other data items. The system generates additional search arguments, which may be multiple, and may relate the search arguments in a search structure. The system in some embodiments applies archetypes to improve filtering, ranking or otherwise prioritizing search results. The system in some embodiments applies archetypes to format search results. The system may be used in conjunction with a system to facilitate user thinking about an arbitrary problem.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JARED M BIBBEE whose telephone number is (571)270-1054. The examiner can normally be reached Monday-Thursday 8AM-6PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, APU MOFIZ can be reached at 5712724080. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JARED M BIBBEE/ Primary Examiner, Art Unit 2161