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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 1/21/2026 has been entered.
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 1,3-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Claim 1 recites “A system…” therefore is a machine. Claim 18 recites “A method” therefore is a process. Claim 20 recites “One or more storage devices” therefore is a manufacture.
Step 2A Prong One: Claims 1, 18 and 20 recite limitations “provide” “generate” “present” “determine” “select” which are all steps that could be performed in the mind hence are mental processes. These limitations are processes that, under their broadest reasonable interpretation, covers performance of the limitation in the mind, but for the recitation of generic computer components. That is, other than reciting processor or a producer party, nothing in the claim element precludes the step from practically being performed in a human mind or with the aid of pen and paper. For example, “provide” in the context of this claim encompasses a user mentally, and with the aid of pen and paper writing the changes down on a sheet of paper and examine the list to identify the relevant ones
Step 2A Prong Two: The judicial exception is not integrated into a practical application. The claim recites the additional elements “a storage device” “one or more processors” this limitation amounts to data gathering which is considered to be insignificant extra solution activity (MPEP 2106.05(g); and this limitation is a mere generic response of collected and analyzed data which is considered to be insignificant extra solution activity (MPEP 2106.05(g).
The one or more hardware processors and one or more non-transitory computer-readable storage media in these steps are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. (see MPEP 2106.05(f)). The claim is directed to an abstract idea.
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The limitations “a storage device” “one or more processors” are recognized by the courts as well-understood, routine , and conventional activities when they are claimed in a merely generic manner
Claim 3 recites “the generative….” Which describes an AI model which does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claimed subject matter is recognized by the courts as well-understood, routine , and conventional activities when they are claimed in a merely generic manner.
Claim 4 recites “the one or more processors…” which recites a mental process as it is something that can be performed in the mind or with pencil and paper. The processors recited are generic computer components and do not amount to significantly more.
Claim 5 recites, “the one or more processors…” which recites a mental process as it is something that can be performed in the mind or with pencil and paper. The processors recited are generic computer components and do not amount to significantly more.
Claim 6 recites, “the one or more processors…” which recites a mental process as it is something that can be performed in the mind or with pencil and paper. The processors recited are generic computer components and do not amount to significantly more.
Claim 7 recites “the one or more processors….” Which recites using the mental process not integrating it into practical application and therefore does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The processors recited are generic computer components and do not amount to significantly more.
Claim 8 recites, “the one or more processors…” which recites a mental process as it is something that can be performed in the mind or with pencil and paper. The processors recited are generic computer components and do not amount to significantly more.
Claim 9 recites, “the one or more processors…” which recites a mental process as it is something that can be performed in the mind or with pencil and paper. The processors recited are generic computer components and do not amount to significantly more.
Claim 10 recites, “each of the set…” which recites a mental process as it is something that can be performed in the mind or with pencil and paper.
Claim 11 recites, “the one or more processors…” which recites a mental process as it is something that can be performed in the mind or with pencil and paper. The processors recited are generic computer components and do not amount to significantly more.
Claim 12 recites, “the one or more processors…” which recites a mental process as it is something that can be performed in the mind or with pencil and paper. The processors recited are generic computer components and do not amount to significantly more.
Claim 13 recites, “the one or more processors…” which recites a mental process as it is something that can be performed in the mind or with pencil and paper. The processors recited are generic computer components and do not amount to significantly more.
Claim 14 recites, “the one or more processors…” which recites a mental process as it is something that can be performed in the mind or with pencil and paper. The processors recited are generic computer components and do not amount to significantly more.
Claim 15 recites, “the one or more processors…” which recites a mental process as it is something that can be performed in the mind or with pencil and paper. The processors recited are generic computer components and do not amount to significantly more.
Claim 16 recites, “the one or more processors…” which recites a mental process as it is something that can be performed in the mind or with pencil and paper. The processors recited are generic computer components and do not amount to significantly more.
Claim 17 recites, “the one or more processors…” which recites a mental process as it is something that can be performed in the mind or with pencil and paper. The processors recited are generic computer components and do not amount to significantly more.
Claim 19 recites “the generative….” Which describes an AI model which does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claimed subject matter is recognized by the courts as well-understood, routine , and conventional activities when they are claimed in a merely generic manner.
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 1,3-20 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 pre-AIA the applicant regards as the invention.
Claim 1, 18 and 20 recites the use of artificial intelligence to generate the answer summary but does not go into detail regarding how estimated time and latency target are related to determining a subset of search results making the inventive concept indefinite. Given that the title of the application deals with generative AI examiner suggests adding more detail to clearly recite this concept.
Dependent claims are rejected for depending off independent claims.
Claim Rejections - 35 USC § 103
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 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 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.
Claim(s) 1, 8, 9, 11, 18, 20 are/is rejected under 35 U.S.C. 103 as being unpatentable over Patrick Lewis et al. "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks, chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://arxiv.org/pdf/2005.11401v4 4/12/2021 hereinafter referenced as Lewis, in view of Kayyoor et al. US10311087 in view of Iwayama et al. US2009/0249652 in view of Engel et al. US2023/0237107
Regarding claim 1, Lewis teaches: one or more answer summaries of a set of search results associated with one or more search queries; and (Lewis see pages 1-5, 7 a query or input for search to find documents)
for generating an answer summary for a search query;
Select of the set of search results for generating an answer summary
for a generative intelligence model
select search results for generating the answer summary
provide, by the one or more processors, to a generative artificial intelligence model, the set of search results (Lewis see pages 1-5, 7, 17 RAG to produce search results and generating output of top K documents and choosing specific documents to produce an answer and generating output as presented in table 3)
generate the answer summary using the generative artificial intelligence model, based on the provided subset of the set of search results; and (Lewis see pages 1-5, 7 document results given to RAG model to produce output or answer in QA format based on given documents)
present, by the one or more processors, the generated answer summary, wherein the answer summary summarizes information in the set of search results (Lewis see pages 1-7, 17 system using CPU and generating output as presented in table 3 such that documents used for the answer may not contain answer verbatim but still contribute the generation of answer or using only titles of documents or chunks of documents)
Lewis does not teach: a storage device configured to store
one or more processors in communication with the storage device configured to:
Determine a latency target
Select a subset of the set of search results wherein to select the subset, the one or more processors are configured to:
determine an estimated time to generate the answer summary for the search query
using the subset of the set of search results, and
select the subset of search results in response to determining that the estimated time satisfies the latency target
subset of the set of search results
However, Kayyoor teaches: a storage device configured to store
one or more processors in communication with the storage device configured to: (Kayyoor see col. 10 lines 10-67 col. 11 lines 1-39 processor in computing system with communication between processor and other system elements and communication between computing system and storage device)
Determine a latency target
select search results in response to determining that the estimated time satisfies the latency target (Kayyoor see col. 6 lines 12-26 col. 10 lines 10-67 processor in computing system, search with selected results based on latency)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of retrieval augmented generation as taught by Lewis to include latency as taught by Kayyoor for the predictable result of more efficiently organizing and managing data.
Lewis does not distinctly disclose: Select a subset of the set of search results wherein to select the subset, the one or more processors are configured to:
determine an estimated time to generate the answer summary for the search query using the subset of the set of search results, and
select the subset of search results
subset of the set of search results
However, Iwayama teaches: determine an estimated time to generate the answer summary for the search query (Iwayama see paragraph 0008 0070 0098 estimating search speed and retrieving an estimated value of number of documents based on predicted search speed)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of retrieval augmented generation as taught by Lewis to include search speed based results as taught by Iwayama for the predictable result of more efficiently organizing and managing data.
Lewis does not teach: Select a subset of the set of search results wherein to select the subset, the one or more processors are configured to:
using the subset of the set of search results, and
select the subset of search results
subset of the set of search results
Engel teaches: Select a subset of the set of search results wherein to select the subset, the one or more processors are configured to:
using the subset of the set of search results, and
select the subset of search results
subset of the set of search results (Engel see paragraph 0037 0061, processor, request reduced search results leading to collection of search results being a subset of the search results received from plurality of shards)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of retrieval augmented generation as taught by Lewis to include search results associated with latency as taught by Engel for the predictable result of more efficiently organizing and managing data.
Regarding claim 8, Lewis as modified further teaches: the one or more processors are configured to input the subset of the set of search results and a text directive to generate the answer summary to a generative artificial intelligence model. (Lewis see pages 1-5, 7 a query or input for search to find documents, document results given to RAG model to produce output or answer in QA format based on given documents)
Regarding claim 9, Lewis as modified further teaches: the one or more processors are configured to input the subset of the set of search results and a text directive to reference one or more search results that were used to generate the answer summary to a generative artificial intelligence model. (Lewis see pages 1-5, 7 a query or input for search to find documents, document results given to RAG model to produce output or answer in QA format based on given documents)
Regarding claim 11, Lewis as modified further teaches: the one or more processors are configured to determine one or more latency characteristics for generating the answer summary and determine a number of search results comprising the subset of the set of search results based on the one or more latency characteristics (Engel see paragraph 0058 0062 0077 reducing search result numbers based on latency)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of retrieval augmented generation as taught by Lewis to include search results associated with latency as taught by Engel for the predictable result of more efficiently organizing and managing data.
Regarding claims 18 and 20, note the rejection of claim(s) 1. The instant claims recite substantially same limitations as the above-rejected claims and are therefore rejected under same prior-art teachings.
Claim(s) 3, 19 are/is rejected under 35 U.S.C. 103 as being unpatentable over Patrick Lewis et al. "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks, chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://arxiv.org/pdf/2005.11401v4 4/12/2021 hereinafter referenced as Lewis, in view of Kayyoor et al. US10311087 in view of Iwayama et al. US2009/0249652 in view of Engel et al. US2023/0237107 in view of Lester et al. US2023/0325725
Regarding claim 3, Lewis does not teach: the generative artificial intelligence model comprises a generative pre-trained transformer model.
However, Lester teaches: the generative artificial intelligence model comprises a generative pre-trained transformer model. (Lester see paragraph 0010 0041 pre trained machine learning model include generative pre-trained transformer model)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of retrieval augmented generation as taught by Lewis to include a transformer model as taught by Lester for the predictable result of more efficiently organizing and managing data.
Regarding claim 19, see rejection of claim 3
Claim(s) 4 are/is rejected under 35 U.S.C. 103 as being unpatentable over Patrick Lewis et al. "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks, chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://arxiv.org/pdf/2005.11401v4 4/12/2021 hereinafter referenced as Lewis, in view of Kayyoor et al. US10311087 in view of Iwayama et al. US2009/0249652 in view of Engel et al. US2023/0237107 in view of Parikh et al. US2010/0281029
Regarding claim 4, Lewis does not teach: the one or more processors are configured to detect that at least a threshold number of users have submitted a semantically similar search query to one or more search queries and detect that the answer summary for the set of search results should be generated in response to detection that at least the threshold number of users have submitted the semantically similar search query to the one or more search queries
However, Parikh teaches: the one or more processors are configured to detect that at least a threshold number of users have submitted a semantically similar search query to one or more search queries and detect that the answer summary for the set of search results should be generated in response to detection that at least the threshold number of users have submitted the semantically similar search query to the one or more search queries (Parikh see paragraph 0060 number of users greater than a threshold issuing queries to determine semantic similarity among queries)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of retrieval augmented generation as taught by Lewis to include a semantic similarity in queries as taught by Parikh for the predictable result of more efficiently organizing and managing data.
Claim(s) 5 are/is rejected under 35 U.S.C. 103 as being unpatentable over Patrick Lewis et al. "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks, chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://arxiv.org/pdf/2005.11401v4 4/12/2021 hereinafter referenced as Lewis, in view of Kayyoor et al. US10311087 in view of Iwayama et al. US2009/0249652 in view of Engel et al. US2023/0237107 in view of Bai et al. US2013/0226935
Regarding claim 5, Lewis does not teach: the one or more processors are configured to determine a location within a document and identify the one or more search queries based on the location within the document
However, Bai teaches: the one or more processors are configured to determine a location within a document and identify the one or more search queries based on the location within the document. (Bai see paragraph 0059 predetermined search queries based on location of text in the document)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of retrieval augmented generation as taught by Lewis to include locations in texts as taught by Bai for the predictable result of more efficiently organizing and managing data.
Claim(s) 6 are/is rejected under 35 U.S.C. 103 as being unpatentable over Patrick Lewis et al. "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks, chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://arxiv.org/pdf/2005.11401v4 4/12/2021 hereinafter referenced as Lewis, in view of Kayyoor et al. US10311087 in view of Iwayama et al. US2009/0249652 in view of Engel et al. US2023/0237107 in view of Yi et al. US2018/0365318
Regarding claim 6, Lewis does not teach: the one or more processors are configured to determine a maximum snippet size for the set of search results based on the one or more latency characteristics for generating the answer summary and determine the subset of the set of search results based on the maximum snippet size
However, Yi teaches: the one or more processors are configured to determine a maximum snippet size for the set of search results based on the one or more latency characteristics for generating the answer summary and determine the subset of the set of search results based on the maximum snippet size. (Yi see paragraph 0042 search results snippets extracted after document ranking based on latency)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of retrieval augmented generation as taught by Lewis to include associating latency and snippets as taught by Yi for the predictable result of more efficiently organizing and managing data.
Claim(s) 7 are/is rejected under 35 U.S.C. 103 as being unpatentable over Patrick Lewis et al. "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks, chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://arxiv.org/pdf/2005.11401v4 4/12/2021 hereinafter referenced as Lewis, in view of Kayyoor et al. US10311087 in view of Iwayama et al. US2009/0249652 in view of Engel et al. US2023/0237107 in view of Goel et al. US2016/0275197
Regarding claim 7, Lewis does not teach: the one or more processors are configured to cause the answer summary to be displayed
However, Goel teaches: the one or more processors are configured to cause the answer summary to be displayed. (Goel see paragraph 0106 0199 displaying filename in answer summary)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of retrieval augmented generation as taught by Lewis to include displaying in answer summary as taught by Goel for the predictable result of more efficiently organizing and managing data.
Claim(s) 10 are/is rejected under 35 U.S.C. 103 as being unpatentable over Patrick Lewis et al. "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks, chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://arxiv.org/pdf/2005.11401v4 4/12/2021 hereinafter referenced as Lewis, in view of Kayyoor et al. US10311087 in view of Iwayama et al. US2009/0249652 in view of Engel et al. US2023/0237107 in view of Gentilcore et al. US2022/0261492
Regarding claim 10, Lewis does not teach: each of the set of search results comprises an electronic document that was verified by a document owner.
However, Gentilcore teaches: each of the set of search results comprises an electronic document that was verified by a document owner. (Gentilcore see paragraph 0027 0031 search results documents to be verified by owner)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of retrieval augmented generation as taught by Lewis to include owner verified results as taught by Gentilcore for the predictable result of more efficiently organizing and managing data.
Claim(s) 12, and 13 are/is rejected under 35 U.S.C. 103 as being unpatentable over Patrick Lewis et al. "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks, chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://arxiv.org/pdf/2005.11401v4 4/12/2021 hereinafter referenced as Lewis, in view of Kayyoor et al. US10311087 in view of Iwayama et al. US2009/0249652 in view of Engel et al. US2023/0237107 in view of Busch et al. US2015/0227624
Regarding claim 12, Lewis does not teach: the one or more processors are configured to determine an amount of time to generate the answer summary and determine a number of search results comprising the subset of the set of search results based on the amount of time to generate the answer summary.
However, Busch teaches: the one or more processors are configured to determine an amount of time to generate the answer summary and determine a number of search results comprising the subset of the set of search results based on the amount of time to generate the answer summary. (Busch see paragraph 0233 determining search time latency associated with search term)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of retrieval augmented generation as taught by Lewis to include determining search time latency as taught by Busch for the predictable result of more efficiently organizing and managing data.
Regarding claim 13, Lewis does not teach: the one or more processors are configured to determine an amount of time to generate the answer summary and determine a total amount of text for the subset of the set of search results based on the amount of time to generate the answer summary.
However, Busch teaches: the one or more processors are configured to determine an amount of time to generate the answer summary and determine a total amount of text for the subset of the set of search results based on the amount of time to generate the answer summary. (Busch see paragraph 0233 determining search time latency associated with search term)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of retrieval augmented generation as taught by Lewis to include determining search time latency as taught by Busch for the predictable result of more efficiently organizing and managing data.
Claim(s) 14 and 15 are/is rejected under 35 U.S.C. 103 as being unpatentable over Patrick Lewis et al. "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks, chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://arxiv.org/pdf/2005.11401v4 4/12/2021 hereinafter referenced as Lewis, in view of Kayyoor et al. US10311087 in view of Iwayama et al. US2009/0249652 in view of Engel et al. US2023/0237107 in view of Haveliwala US2014/0089298
Regarding claim 14, Lewis does not teach: the one or more processors are configured to detect that an amount of time to generate the answer summary is greater than a threshold amount of time and generate the answer summary in a background process while the subset of the set of search results is displayed
However, Haveliwala teaches: the one or more processors are configured to detect that an amount of time to generate the answer summary is greater than a threshold amount of time and generate the answer summary in a background process while the subset of the set of search results is displayed. (Haveliwala see paragraphs 0008 0009 displayed search result with pointer hovering over result snippet exceeding a threshold value of time determining user preference)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of retrieval augmented generation as taught by Lewis to include search result determining user preference as taught by Haveliwala for the predictable result of more efficiently organizing and managing data.
Regarding claim 15, Lewis as modified further teaches: using a generative artificial intelligence model (Lewis see pages 1-5, 7 document results given to RAG model to produce output or answer in QA format based on given documents)
Lewis does not teach: the one or more processors are configured to detect that an amount of time to generate the answer summary is greater than a threshold amount of time and generate the answer summary while the subset of the set of search results is displayed.
However, Haveliwala teaches: the one or more processors are configured to detect that an amount of time to generate the answer summary is greater than a threshold amount of time and generate the answer summary while the subset of the set of search results is displayed. (Haveliwala see paragraphs 0008 0009 displayed search result with pointer hovering over result snippet exceeding a threshold value of time determining user preference)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of retrieval augmented generation as taught by Lewis to include search result determining user preference as taught by Haveliwala for the predictable result of more efficiently organizing and managing data.
Claim(s) 16 are/is rejected under 35 U.S.C. 103 as being unpatentable over Patrick Lewis et al. "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks, chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://arxiv.org/pdf/2005.11401v4 4/12/2021 hereinafter referenced as Lewis, in view of Kayyoor et al. US10311087 in view of Iwayama et al. US2009/0249652 in view of Engel et al. US2023/0237107 in view of Mohammed et al. US2023/0315999
Regarding claim 16, Lewis does not teach: the one or more processors are configured to detect a triggering condition and perform a search for the search query using user permissions based on a number of end users that submitted search queries that are semantically similar to the search query.
However, Mohammed teaches: the one or more processors are configured to detect a triggering condition and perform a search for the search query using user permissions based on a number of end users that submitted search queries that are semantically similar to the search query. (Mohammed see paragraph 0051 0143- 0147 trigger invoked upon receipt of threshold number of unrecognized queries to be clustered with semantically similar queries to determine intent and execute user query based on clustered intent)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of retrieval augmented generation as taught by Lewis to include clustering semantically similar queries as taught by Mohammed for the predictable result of more efficiently organizing and managing data.
Claim(s) 17 are/is rejected under 35 U.S.C. 103 as being unpatentable over Patrick Lewis et al. "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks, chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://arxiv.org/pdf/2005.11401v4 4/12/2021 hereinafter referenced as Lewis, in view of Kayyoor et al. US10311087 in view of Iwayama et al. US2009/0249652 in view of Engel et al. US2023/0237107 in view of Cohen et al. US2015/0169750
Regarding claim 17, Lewis does not teach: the one or more processors are configured to generate the answer summary using a first set of documents and generate a second answer summary in the background using a second set of documents that is larger than the first set of documents.
However, Cohen teaches: the one or more processors are configured to generate the answer summary using a first set of documents and generate a second answer summary in the background using a second set of documents that is larger than the first set of documents. (Cohen see paragraph 0022 first answer box based on one search result second answer box based on two search results)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of retrieval augmented generation as taught by Lewis to include multiple answer boxes as taught by Cohen for the predictable result of more efficiently organizing and managing data.
Response to arguments
Applicant’s argument: New amendments overcome abstract idea 101 rejections
Examiner’s response: Applicant’s argument is considered but is not persuasive. The details in the independent claims are lacking with specific description and details to make applicant’s argument persuasive. The claims do not explain how the AI is used nor does it explain how the latency affects the search results being selected which lends itself susceptible to being a mental process. Examiner believes there may be a point to applicant’s argument but the claim itself requires more detail to overcome the 101 rejection. Therefore applicant’s argument is not persuasive.
Applicant’s argument: New amendments overcome 112 rejection
Examiner’s response: Applicant’s argument is considered but is not persuasive. Amendments do address previous 112 rejections to an extent and are helpful to move forward prosecution but does not resolve all of the 112 issues.
Applicant’s argument: New amendments overcome 103 rejection
Examiner’s response: Applicant’s argument is not persuasive. Newly amended subject matter deals with selecting a subset of results for generating answer summary. Lewis and Engel teach this concept as Engel only uses a subset of search results and Lewis uses RAG to select the top-k document and produce an answer by using these top documents. Combined these references teaches the newly amended subject matter.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALLEN S LIN whose telephone number is (571)270-0612. The examiner can normally be reached on M-F 9-5.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kavita Stanley can be reached on (571)272-8352. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ALLEN S LIN/Primary Examiner, Art Unit 2153
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