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 .
Status of Claims
This Non-Final Office Action is in response to the application filed 12/23/2024. Claim(s) 1-18, and 20 are pending.
Priority
Application 19/000,608 was filed on 12/23/2024, and is a continuation of Application 18/673,570 which was filed 05/24/2024 and has a provisional Application 63/593,163 filed 10/25/2023, and provisional Application 63/589,256 filed 10/10/2023.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claim(s) 1-20 rejected on the ground of nonstatutory double patenting as being unpatentable over claim(s) 1-8, 15, and 18 of U.S. Patent No. 12,217,271. Although the claims at issue are not identical, they are not patentably distinct from each other because the claims of the instant application are considered obvious over the claims disclosed in the patent. See chart below:
Instant Application 19/000,608
US Patent 12,217,271
Claim 1: An artificial intelligence ("Al") system, the system comprising: at least one processor operatively coupled to a memory; the at least one processor when executing configured to:
Claim 1: An artificial intelligence (‘AT’) system, the system comprising: at least one processor; a memory operatively coupled to the at least one processor; the at least one processor when executing configured to:
execute an interactive session with a plurality of respondents via a plurality of user interface displays that accept and tailor subsequent user interface displays dynamically during the interactive session based on artificial intelligent outputs returned during the interactive session;
execute an interactive session with a plurality of respondents via a plurality of user interface displays that accept and tailor subsequent user interface displays dynamically during the interactive session based on artificial intelligent outputs returned during the interactive session;
instantiate a first Al model trained on execution requirement inputs and trained to output text based questions and requests for validation data associated with at least some of the text based questions;
instantiate a second AI model trained on execution requirement inputs and trained to output text based questions and requests for validation data associated with at least some of the text based questions;
analyze a free text input received in displayed visual interface objects from the interactive session display
analyze the free text input retrieved results to the displayed visual interface objects from the interactive session display, the free text input associated with the respective execution targets
including respective questions or respective requests for validation data;
execution targets based on responses to the text based questions and responses to the request for validation data
instantiate a second Al model trained on, at least in part, complete free text responses and incomplete free text responses and trained to output identification of incomplete or partial responses;
instantiate a third AI model trained on, at least in part, complete free text responses and incomplete free text responses and trained to output identification of incomplete or partial responses;
automatically evaluate, using the second Al model, retrieved free text responses and automatically display supplemental visual interface objects in response to determining a user interface input for a respective free text response is incomplete or partially complete, some of the supplemental visual interface objects including at least text based questions and requests for validation data.
automatically evaluate, using a third AI model, the retrieved results free text responses and automatically generate and display supplemental visual interface objects in response to determining a user interface input for a respective free text response is incomplete or partially complete, some of the supplemental visual interface objects including at least text based questions and requests for validation data
2. The system of claim 1, wherein the at least one processor is configured to instantiate a third Al model, trained on regulatory information and custom policy information and trained to output a set of requirements associated with the regulatory information and custom client policy information.
Claim 1: instantiate a first AI model, trained on regulatory information and custom policy information and trained to output a set of requirements associated with the regulatory information and custom client policy information
3. The system of claim 2, wherein the at least one processor is configured to: evaluate, using the first Al model, a plurality of constraints defined by input regulatory information and input custom policy information to automatically identify and output a set of execution requirements for one or more targets.
Claim 1: evaluate, using the first AI model, a plurality of constraints defined by input regulatory information and input custom policy information to automatically identify and output a set of execution requirements for one or more targets
4. The system of claim 1, wherein the at least one processor is configured to tailor the interactive session and associated user interface displays based on a respective client location and the respective requirements associated with the interactive session.
Claim 1: tailor the interactive guided session and associated user interface displays based on a respective client location and the respective requirements associated with the interactive session
5. The system of claim 1, wherein the at least one processor is configured to generate, using a fourth Al model, an assessment responsive to completion of analysis of results for each of one or more execution targets and update a status associated with an execution evaluation, wherein the assessment includes analysis of the results generated from the displayed visual interface objects, supplemental visual interface objects, and any additional data source.
Claim 1: generate, using a fourth AI model, an assessment responsive to completion of analysis of the results for each of the execution targets and update a status associated with an execution evaluation, wherein the assessment includes analysis of the retrieved results generated from the displayed visual interface objects, supplemental visual interface objects, and any additional data source.
6. The system of claim 1, wherein the at least one processor is configured to select and execute a respective instance of the first artificial intelligent ("Al") model trained on a plurality of constraints and linked information requirements responsive to definition of a set of execution requirements.
Claim 2: The system of claim 1, wherein the at least one processor is configured to select and execute a respective instance of the second artificial intelligent ("Al") model trained on a plurality of constraints and linked information requirements responsive to definition of the set of execution requirements.
7. The system of claim 6, wherein the first Al model accepts the set of execution requirements as input during training and generates natural language processing ("NLP") text outputs during prediction, the NLP outputs configured to solicit information to verify execution requirements and any of the plurality constraints and linked information requirements.
Claim 3: The system of claim 2, wherein the second Al model accepts the set of execution requirements as input during training and generates natural language processing ("NLP") text outputs during prediction, the NLP outputs configured to solicit information to verify execution requirements and any of the plurality constraints and linked information requirements.
8. The system of claim 7, wherein the at least one processor or the first Al model is further configured to tailor the NLP text outputs to a plurality of execution targets and present the NLP text outputs as at least part of a visual interface object.
Claim 4: The system of claim 3, wherein the at least one processor or second Al model is further configured to tailor the NLP text outputs to a plurality of execution targets and present the NLP text outputs as at least part of the visual interface object.
9. The system of claim 7, wherein the first Al model is configured to accept specification of an execution target and generate the NLP text outputs tailored to the execution target.
Claim 5: The system of claim 3, wherein the second Al model is configured to accept specification of an execution target and generate the NLP text outputs tailored to the execution target.
10. The system of claim 1, wherein the at least one processor is configured to execute a second Al model trained on answers to information requests and labeled responses.
Claim 6: The system of claim 1, wherein the at least one processor is configured to execute a third Al model trained on answers to information requests and labeled responses.
11. The system of claim 10, wherein the labeled responses include complete responses and incomplete responses.
Claim 7: The system of claim 6, wherein the labeled responses included complete responses and incomplete responses.
12. The system of claim 11, wherein the second Al model is configured to accept respondent answers to information requests and predict an output evaluation of complete or incomplete.
Claim 8: The system of claim 6, wherein the third Al model is configured to accept respondent answers to information requests and predict an output evaluation of complete or incomplete.
13. A computer implemented method for executing an interactive session using an artificial intelligence ("Al") model, the method comprising:
Claim 15: A computer implementation method for managing an artificial intelligence ("Al") system, the method comprising: executing, by at least one processor, an interactive session
executing, by at least one processor, an interactive session with a plurality of respondents via a plurality of user interface displays that accept and tailor subsequent user interface displays dynamically during the interactive session based on artificial intelligent outputs returned during the interactive session;
Claim 15: executing, by at least one processor, an interactive session with a plurality of respondents via a plurality of user interface displays that accept and tailor subsequent user interface displays dynamically during the interactive session based on artificial intelligent outputs returned during the interactive session;
instantiating, by the at least one processor, a first Al model trained on execution requirement inputs and trained to output text based questions and requests for validation data associated with at least some of the text based questions;
Claim 15: instantiating a second Al model trained on execution requirement inputs and trained to output text based questions and requests for validation data associated with at least some of the text based questions;
analyzing, by the at least one processor, a free text input received in displayed visual interface objects from the interactive session display
Claim 15: analyzing, by the at least one processor, the free text input to the displayed visual interface objects from the interactive session display, the free text input associated with the respective execution targets,
including respective questions or respective requests for validation data;
Claim 15: execution targets based on responses to the text based questions and responses
instantiating, by the at least one processor, a second Al model trained on, at least in part, complete free text responses and incomplete free text responses and trained to output identification of incomplete or partial responses;
Claim 15: instantiate a third Al model trained on, at least in part, complete free text responses and incomplete free text responses and trained to output identification of incomplete or partial responses;
and automatically evaluating, by the at least one processor, retrieved free text responses and automatically displaying supplemental visual interface objects in response to determining a user interface input for a respective free text response is incomplete or partially complete, some of the supplemental visual interface objects including at least text based questions and requests for validation data.
Claim 15: automatically evaluating, using the third Al model executed by the at least one processor, the free text input and automatically generating and displaying supplemental visual interface objects in response to determining a user interface input for a respective free text response is incomplete or partially complete, some of the supplemental visual interface objects including at least text based questions and requests for validation data
14. The method of claim 13, wherein the method comprises instantiating a third Al model, trained on regulatory information and custom policy information and trained to output a set of requirements associated with the regulatory information and custom client policy information.
Claim 15: instantiating a first Al model, trained on regulatory information and custom policy information, and trained to output a set of requirements associated with the regulatory information and custom client policy information;
15. The method of claim 14, wherein the method comprises: evaluating, by the at least one processor, using the first Al model, a plurality of constraints defined by input regulatory information and input custom policy information to automatically identify and output a set of execution requirements for one or more targets.
Claim 15: evaluating, using the first Al model executed by the at least one processor, a plurality of constraints defined by input regulatory information and input custom policy information to automatically identify and output a set of execution requirements for one or more targets;
16. The method of claim 13, wherein the method comprises tailoring the interactive session and associated user interface displays based on a respective client location and the respective requirements associated with the interactive session.
Claim 15: tailoring, by the at least one processor, the interactive guided session and associated user interface displays based on a respective client location and the respective requirements associated with the interactive session;
17. The method of claim 13, wherein the method comprises generating, using a fourth Al model, an assessment responsive to completion of analysis of results for a plurality of execution targets and updating a status associated with an execution evaluation, wherein the assessment includes analyzing the results generated from the displayed visual interface objects, supplemental visual interface objects, and any additional data source.
Claim 15: generating, using a fourth Al model executed by the at least one processor, an assessment responsive to completion of analysis of the results for each of the execution targets and update a status associated with an execution evaluation, wherein the assessment includes analysis of the retrieved results generated from the displayed visual interface objects, supplemental visual interface objects, and any additional data source
18. The method of claim 13, wherein the method comprises tailoring natural language processing ("NLP") text outputs to a plurality of execution targets and presenting the NLP text outputs as at least part of the visual interface object.
Claim 18: The method of claim 17, wherein the method comprising tailoring the NLP text outputs to a plurality of execution targets and presenting the NLP text outputs as at least part of the visual interface object
20. The method of claim 19, wherein the method comprising accepting respondent answers to information requests and predicting an output evaluation of complete or incomplete.
Claim 8: The system of claim 6, wherein the third Al model is configured to accept respondent answers to information requests and predict an output evaluation of complete or incomplete.
Claim Objections
Claim(s) 7 is objected to because of the following informalities: "plurality constraints", should be "plurality of constraints". Appropriate correction is required.
Claim(s) 8 objected to because of the following informalities: " Appropriate correction is required.
Claim(s) 10 objected to because of the following informalities: " Appropriate correction is required.
Claim(s) 20 is objected to because of the following informalities: Claim 19 is missing, and claim 20 should be listed as claim 19. Appropriate correction is required.
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.
Claim(s) 20 is 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.
Claim 20 recites the limitation " The method of claim 19". There is insufficient antecedent basis for this limitation in the claim, as claim 19 does not exist.
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 1-18, and 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claims 1-18, and 20 are directed to a system, method, or product which are/is one of the statutory categories of invention. (Step 1: YES).
Claims 1, and 13 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites a method and computing device for managing data during sessions and displaying information. For Claims 1 and 13 the limitations of (Claim 1 being representative):
[…]:
execute an interactive session with a plurality of respondents via a plurality of […] displays that accept and tailor subsequent […] displays dynamically during the interactive session based on […] outputs returned during the interactive session;
instantiate a first […] model trained on execution requirement inputs and trained to output text based questions and requests for validation data associated with at least some of the text based questions;
analyze a free text input received in displayed visual […] objects from the interactive session display including respective questions or respective requests for validation data;
instantiate a second […] model trained on, at least in part, complete free text responses and incomplete free text responses and trained to output identification of incomplete or partial responses;
automatically evaluate, using the second […] model, retrieved free text responses and automatically display supplemental visual […] objects in response to determining a user […] input for a respective free text response is incomplete or partially complete, some of the supplemental visual […] objects including at least text based questions and requests for validation data.
The above limitations have a scope that includes a process that is used to determine if responses are complete or partially incomplete in regards to requesting validation data. This is construed as reciting a legal interaction that determines compliance on whether or not a response meets a compliance threshold of being complete or partially complete. The claim is simply receiving data and processing the data to determine if a free text response is complete or partially complete, and displaying the result. This qualifies as a certain method of organizing human activities type of abstract idea.
Additionally, the claimed use of the data and the claimed determinations can be practically performed by a human being mentally where a user is reading incoming data including free text responses to questions, determining if the responses are incomplete or partially complete, and visually marking the result. A human being can perform those actions mentally. The claimed receipt of the data and the use of the data to make the claimed determinations can be easily performed by a person who is reading data and mentally making the claimed determinations. The types of identified abstract ideas are considered together as a single abstract idea for analysis purposes. Accordingly, Claims 1, and 13 recite an abstract idea. (Step 2A- Prong 1: YES. The claims recite an abstract idea).
This judicial exception is not integrated into a practical application. Claims 1 and 13 recites the additional elements of a processor (Claims 1 and 13), memory (Claim 1), user interface (Claims 1 and 13), first and second artificial intelligence model (Claims 1 and 13), that implements the identified abstract idea. These additional elements are not described by the applicant and are recited at a high-level of generality (i.e., one or more generic computers performing a generic computer functions) such that it amounts no more than mere instructions to apply the exception using a generic computer components. Accordingly, even in combination these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Claims 1, and 13 are directed to an abstract idea. (Step 2A-Prong 2: NO: the additional claimed elements are not integrated into a practical application).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of a processor (Claims 1 and 13), memory (Claim 1), user interface (Claims 1 and 13), first and second artificial intelligence model (Claims 1 and 13) to perform the noted steps amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept (“significantly more”). Accordingly, even in combination, these additional elements do not provide significantly more. As such claims 1 and 13 are not patent eligible. (Step 2B: NO. The claims do not provide significantly more).
Dependent Claims 2-12, 14-18 and 20 are similarly rejected because they either further define/narrow the abstract idea of independent claims 1, and 13 as discussed above. Claim(s) 2 and 14 merely describe(s) a third model outputting a set of requirements associated with regulatory information and custom client policy information. Claim(s) 3 and 15 merely describe(s) evaluating a plurality of constraints defined by regulatory information and custom policy information and identifying a set of execution requirements for one or more targets. Claim(s) 4 and 16 merely describe(s) tailoring the interactive session and user display based on a client location and respective requirements associated with the interactive session. Claim(s) 5 and 17 merely describe(s) generating an assessment responsive to completion of analysis of results for each of one or more execution targets and updating a status associated with an execution evaluation, wherein the assessment includes analysis of the results generated from the displayed object, supplemental visual interface objects, and any additional data source. Claim(s) 6 merely describe(s) selecting and executing a respective instance of the first model trained on a plurality of constraints and linked information requirements responsive to definition of a set of execution requirements. Claim(s) 7 merely describe(s) the first model accepting the set of execution requirements as input and generating text output during prediction to solicit information to verify execution requirements and any of the plurality of constraints and linked information requirements. Claim(s) 8 and 18 merely describe(s) tailoring the output to a plurality of execution targets and representing the text outputs as part of a visual interface object. Claim(s) 9 merely describe(s) the first model accepting specification of an execution target and generating the text outputs tailored to the execution target. Claim(s) 10 merely describe(s) executing a second model trained on answers to information requests and labeled responses. Claim(s) 11 merely describe(s) the labeled responses including complete and incomplete responses. Claim(s) 12 and 20 merely describe(s) the second model configured to accept response answers to information requests and predict output evaluation of complete or incomplete. Therefore claims 2-12, 14-18, and 20 are considered patent ineligible for the reasons given above.
Dependent Claim(s) 2, 5, 7, 8, 9, 14, 17, and 18 recite limitations that further define the abstract idea noted in independent claims 1, and 13. In addition, it recites the additional elements of a third Al model, fourth AI model, and natural language processing. The third Al model, fourth AI model, and natural language processing are recited at a high level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computing component. Even in combination, these additional elements do not integrate the abstract idea into a practical application and do not amount to significantly more than the abstract idea itself.
Claims 2-4, 6-7, and 14-18 include the additional elements of a processor, first Al model, user interface, and second AI model. The processor, first Al model, user interface, and second AI model are analyzed in the same manner as the processor, first Al model, user interface, and second AI model in the independent claim and do not provide a practical application or significantly more for the same reasons above. Therefore claims 2-12, 14-18 and 20 are considered patent ineligible for the reasons given above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Costas (US20180053128A1)
Chowdhury (US20220222440A1)
Ramaswamy (IN201741013646A)
Snyder (US20200175110A1)
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/E.M.K./Examiner, Art Unit 3626
/JESSICA LEMIEUX/Supervisory Patent Examiner, Art Unit 3626