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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set
forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this
application is eligible for continued examination under 37 CFR 1.114, and the fee set
forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action
has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on March 30, 2026 has been entered.
Status of Claims
Claims 1, 6, 7, 8, 12, 13, 14, 15, 16, 17, 18, 19, and 20 have been amended. Claim 2 has been canceled. Claims 21 has been added. Claims 1 and 3-21 are pending and rejected in the application.
Arguments
Applicant Argues
Rejection under 35 USC §101 Claims 15-20 are rejected under 35 USC §101 for allegedly being directed to non-statutory subject matter. This rejection is traversed.
Strictly in an effort to expedite prosecution, Claims 15-20 are amended herein to recite that the medium is "non-transitory". A non-transitory medium cannot include a transitory signal. Accordingly, reconsideration and withdrawal of the rejection are requested.
Examiner Responds:
Applicant's 35 USC § 101 arguments have been considered and are persuasive for claims 15-20. Thus, the 35 USC § 101 rejection has been withdrawn.
Applicant Argues
These rejections are traversed. In rejecting Claim 1, the Office admits that the combination of Bodenstab and Kane has significant deficiencies with respect to Claim 1, including that the combination fails to describe or suggest a system that can determine a predetermined distance around the target embedding within vector space based on execution of a nearest neighbor algorithm, retrieve, via the RAG model, a subset of rows from among the plurality of rows in the table corresponding to a subset of embeddings among the plurality of embeddings that are within the predetermined distance around the target embedding within the vector space, and execute the tuned RAG model on the target record and the task to generate a predicted output with respect to the task. In an effort to cure these admitted deficiencies, the Office cites Buniatyan.
Examiner Responds:
Applicant's 35 USC § 103 arguments, noted above, with respect to claims 1 and 3-21 have been considered but are moot in view of the new ground(s) of rejection.
Claim Rejections – 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1 and 3-21 rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement.
Regarding claims 1, 8, and 15 the claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. The limitation "populate a limited-size context window of the AI model with the subset of rows in place of a global tabular dataset” and “execute the AI model with the populated context window on the target record and the task to generate a predicted output with respect to the task.” are not found in the specification. Thus, claims 1, 8, and 15 fails to comply with the written description requirement.
Claims 3-7 and 21 depends from rejected claim 1 respectively, comprise the same deficiencies as claim 1 directly or indirectly by dependence, and are therefore rejected on the same basis because none of the dependents add anything to otherwise overcome the rejection.
Claims 9-14 depends from rejected claim 8 respectively, comprise the same deficiencies as claim 8 directly or indirectly by dependence, and are therefore rejected on the same basis because none of the dependents add anything to otherwise overcome the rejection.
Claims 16-20 depends from rejected claim 15 respectively, comprise the same deficiencies as claim 15 directly or indirectly by dependence, and are therefore rejected on the same basis because none of the dependents add anything to otherwise overcome the rejection.
Regarding claim 21 the claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. The limitation " wherein the limited-size context window comprises a fixed capacity, and the processor is configured to select the subset of rows such that the subset of rows fit within the fixed capacity during a single execution of the AI model.” are not found in the specification. Thus, claim 21 fails to comply with the written description requirement.
Claims 1 and 3-21 rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the enablement requirement.
Regarding claims 1, 8, and 15 the claim(s) contains subject matter which was not described in the specification in such a way as to enable one skilled in the art to which it pertains, or with which it is most nearly connected, to make and/or use the invention. The limitation "populate a limited-size context window of the AI model with the subset of rows in place of a global tabular dataset” and “execute the AI model with the populated context window on the target record and the task to generate a predicted output with respect to the task.” are not found in the specification. Specifically, “populate a limited-size context window” is not found in the specification. Thus, claims 1, 8, and 15 fails to comply with the written description requirement.
Claims 3-7 and 21 depends from rejected claim 1 respectively, comprise the same deficiencies as claim 1 directly or indirectly by dependence, and are therefore rejected on the same basis because none of the dependents add anything to otherwise overcome the rejection.
Claims 9-14 depends from rejected claim 8 respectively, comprise the same deficiencies as claim 8 directly or indirectly by dependence, and are therefore rejected on the same basis because none of the dependents add anything to otherwise overcome the rejection.
Regarding claim 21 the claim(s) contains subject matter which was not described in the specification in such a way as to enable one skilled in the art to which it pertains, or with which it is most nearly connected, to make and/or use the invention. The limitation " wherein the limited-size context window comprises a fixed capacity, and the processor is configured to select the subset of rows such that the subset of rows fit within the fixed capacity during a single execution of the AI model.” are not found in the specification. Specifically, “limited-size context window” is not found in the specification. Thus, claim 21 fails to comply with the written description requirement.
Claim Rejections – 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 2, 3, 4, 7, 8, 9, 10, 11, 14, 15, 16, 17, 18, and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Bodenstab et al. U.S. Patent Publication (2025/0291780; hereinafter: Bodenstab) in view of Merrick et al. U.S. Patent Publication (2025/0045634; hereinafter: Merrick) and further in view of Lee et al. U.S. Patent Publication (2025/0080583; hereinafter: Lee)
Claims 1, 8, and 15
As to claims 1, 8, and 15, Bodenstab discloses an apparatus, comprising:
a memory (paragraph[0022], the reference describes using a retrieval augmented generation model.); and
a processor coupled to the memory, the processor configured to (paragraph[0056], the reference describes using one or more processors.):
store a table comprising a plurality of rows (paragraph[0012], the reference describes a flowsheets containing table and rows.);
receive a target record of a task (paragraph[0033], the reference describes the RAG model receiving records.);
Bodenstab does not appear to explicitly disclose
covert the target record into a target embedding and convert the plurality of rows into a plurality of embeddings, in vector space;
determine a distance around the target embedding within vector space based on execution of a nearest neighbor algorithm;
retrieve, via an artificial intelligence (AI) model, a subset of rows from the table corresponding to embeddings that are within the distance around the target embedding within the vector space;
populate a limited-size context window of the AI model with the subset of rows in place of a global tabular dataset; and
execute the AI model with the populated context window on the target record and the task to generate a predicted output with respect to the task.
However, Merrick discloses covert the target record into a target embedding and convert the plurality of rows into a plurality of embeddings, in vector space (paragraph[0023]-paragraph[0024], the reference describes a transforming row data.);
determine a distance around the target embedding within vector space based on execution of a nearest neighbor algorithm (paragraph[0085], the reference describes using nearest neighbor to determine the distance of the embeddings.);
retrieve, via an artificial intelligence (AI) model, a subset of rows from the table corresponding to embeddings that are within the distance around the target embedding within the vector space (paragraph[0086], the reference describes determining a set of rows from a table to gather based on the distances that satisfy a threshold.). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to a person having ordinary skill in the art to which said subject matter pertains to have modified the teachings of Bodenstab with the teachings of Merrick to determine the distance of embeddings which would result in the claim invention. The skilled artisan would have been motivated to improve the teachings of Bodenstab with the teachings of Merrick to efficiently generate a mathematical representation of data table rows that capture semantic similarities and difference between data table rows (Merrick: paragraph[0017]).
The combination of Bodenstab and Merrick do not appear to explicit disclose
populate a limited-size context window of the AI model with the subset of rows in place of a global tabular dataset; and
execute the AI model with the populated context window on the target record and the task to generate a predicted output with respect to the task.
However, Lee discloses populate a limited-size context window of the AI model with the subset of rows in place of a global tabular dataset (paragraph[0072], the reference describe generating partitions of data to be implemented in a limited size memory (i.e., limit-size context window, as claimed) of a model.); and
execute the AI model with the populated context window on the target record and the task to generate a predicted output with respect to the task (paragraph[0070]-paragraph[0072], the references describes using the data to predict a next token). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to a person having ordinary skill in the art to which said subject matter pertains to have modified the teachings of Bodenstab with the teachings of Merrick and Lee to determine partition of data to be implemented a limited size memory which would result in the claim invention. The skilled artisan would have been motivated to improve the teachings of Bodenstab with the teachings of Merrick and Lee to efficiently improve the computing tool operations for balancing regular expression groups (Lee: paragraph[0002]).
Claims 9 and 16
As to claims 9 and 16, the combination of Bodenstab, Merrick, and Lee discloses all the elements in claim 1, as noted above, and Bodenstab further disclose wherein the plurality of rows comprise data from a plurality of columns of the table (paragraph[0012], the reference describes using plurality of rows.).
Claims 3, 10, and 17
As to claims 3, 10, and 17, the combination of Bodenstab, Merrick, and Lee discloses all the elements in claim 1, as noted above, and Merrick further disclose wherein the processor is configured to transform content values in the plurality of rows to generate the plurality of embedding, respectively, and transform a corresponding set of content values of the target record to generate a target vector of the target record (paragraph[0025], the reference describes the transformer that encodes data.).
Claims 4, 11, and 18
As to claims 4, 11, and 18, the combination of Bodenstab, Merrick, and Lee discloses all the elements in claim 3, as noted above, and Merrick further disclose wherein the processor is configured to generate a predetermined radius around the target embedding within vector space based on execution of the nearest neighbor algorithm on the plurality of embeddings and the target embedding (paragraph[0085], the reference describes using a threshold (i.e., a predetermined radius, as claimed) around the nearest neighbor calculation of embedded data.).
Claims 7 and 14
As to claims 7 and 14, the combination of Bodenstab, Merrick, and Lee discloses all the elements in claim 3, as noted above, and Bodenstab further disclose wherein the AI model comprises a limited size memory, and the processor is configured to retrieve the subset of rows based on a size of the subset of rows being able to fit within the limited-size memory (paragraph[0027], the reference describes a feeding a portion of the data to the model.).
Claim 21
As to claim 21, the combination of Bodenstab, Merrick, and Lee discloses all the elements in claim 1, as noted above, and Merrick further disclose wherein the limited-size context window comprises a fixed capacity, and the processor is configured to select the subset of rows such that the subset of rows fit within the fixed capacity during a single execution of the AI model (paragraph[0086], the reference describes generating a set of rows to be processed by the model in one execution.).
Claims 5, 12, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Bodenstab et al. U.S. Patent Publication (2025/0291780; hereinafter: Bodenstab) in view of Merrick et al. U.S. Patent Publication (2025/0045634; hereinafter: Merrick) and further in view of Lee et al. U.S. Patent Publication (2025/0080583; hereinafter: Lee) and further in view of Mauer et al. U.S. Patent Publication (2022/0141263; hereinafter: Mauer)
Claims 5, 12, and 19
As to claims 5, 12, and 19, the combination of Bodenstab, Merrick, and Lee discloses all the elements in claim 1, as noted above, but do not appear to explicitly disclose wherein the processor is configured to determine distances between the plurality of embeddings and the target embedding based on execution of a dot product algorithm on the plurality of embeddings and the target embedding.
However, Mauer discloses wherein the processor is configured to determine distances between the plurality of embeddings and the target embedding based on execution of a dot product algorithm on the plurality of embeddings and the target embedding (paragraph[0018], the reference describes using dot product to determine distances.). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to a person having ordinary skill in the art to which said subject matter pertains to have modified the teachings of Bodenstab with the teachings of Merrick, Lee, and Mauer to use a dot product which would result in the claim invention. The skilled artisan would have been motivated to improve the teachings of Bodenstab with the teachings of Merrick, Lee, and Mauer to efficiently facilitate user discovery of communication platform features to the user without explicit prompting or request by the user (Mauer: paragraph[0009[).
Claims 6, 13, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Bodenstab et al. U.S. Patent Publication (2025/0291780; hereinafter: Bodenstab) in view of Merrick et al. U.S. Patent Publication (2025/0045634; hereinafter: Merrick) and further in view of Lee et al. U.S. Patent Publication (2025/0080583; hereinafter: Lee) and further in view of Bourdev U.S. Patent Publication (7,343,551; hereinafter: Bourdev)
Claims 6, 13, and 20
As to claims 6, 13, and 20, the combination of Bodenstab, Merrick, and Lee discloses all the elements in claim 1, as noted above, but do not appear to explicitly disclose wherein the processor is further configured to receive a request to execute the AI model on the target record via a software application, and display the predicted output via a graphical user interface (GUI) of the software application.
However, Bourdev discloses wherein the processor is further configured to receive a request to execute the AI model on the target record via a software application, and display the predicted output via a graphical user interface (GUI) of the software application (Column 9, lines 15-36, the reference describes display predicted values on a user interface.). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to a person having ordinary skill in the art to which said subject matter pertains to have modified the teachings of Bodenstab with the teachings of Merrick, Lee, and Bourdev to show predictions on an interface which would result in the claim invention. The skilled artisan would have been motivated to improve the teachings of Bodenstab with the teachings of Merrick, Lee, and Bourdev to efficiently predict values being selected from the proposed values based on the likelihood assessments (Bourdev: Column 2, lines 1-5).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DAWAUNE A CONYERS whose telephone number is (571)270-3552. The examiner can normally be reached on M-F 8:00am-4:30pm EST. EST.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ann J. Lo can be reached on (571) 272-9767. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DAWAUNE A CONYERS/Primary Examiner, Art Unit 2152 May 1, 2026
/DAWAUNE A CONYERS/Primary Examiner, Art Unit 2152 February 24, 2024
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