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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 4/1/26, 5/7/26, 1/21/26, and 9/19/25 was filed after the mailing date of the application on 9/15/2025. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitations uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are:
processing system is configured to in claim 1.
configured to … in claim 2-14.
Because these claim limitations are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have these limitations interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitations to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitations recites sufficient structure to perform the claimed function so as to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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 18 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 18, recites “the AI engine”, first there is no previous definition.
Claim 18 recites the limitation "The AI engine" in lines 5 and 6. There is insufficient antecedent basis for this limitation in the claim.
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 1-14 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to non-statutory subject matter. Independent claim 1 recites a system which the specification It is noted that the specification is silent to if the "recited hardware device is a statutory non-transitory hardware device.
Therefore, the system claims of 1 - 14 are software per se, leaving the product claim non-statutory. Furthermore, claim 1 recites a system claim that does not include hardware device, the specification does not lend itself to show that the system recite hardware device include a processor and memory to perform the recited operations. A processor and memory need to be positivity recited as components of the system (if supported by the spec).
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding claims 1, 15, and 18,
Step 1 Analysis: Claims 1, 15, and 18 are directed to a method, system and computer program, which falls within one of the four statutory categories.
Step 2A Prong 1 Analysis: Claims 1, 15, and 18 recites,
The limitations of:
“divide the set of data into one or more subsets of data” is a mental process which can be performed by the human mind. A human can divide data in subsets.
These limitations, as drafted, are processes that, under broadest reasonable interpretation, covers the performance of the limitation in the mind which falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A Prong 2 Analysis: Claims 1, 8, and 15 recites the additional elements:
“receive a set of data from a data source”, “transmit the one or more subsets of data to
the AI engine”, “transmit one or more queries to the AI engine to elicit search and identification of one or more responses based on a data set comprising the one or more subsets of data, wherein the one or more responses include a text-based response and a graphical response associated with the text-based response”, and “transmit the text-based response and the graphical response to a graphical user interface for presentation on a display of an electronic device comprising the graphical user interface”, “a system”, “a processing system”, “AI”, “a data source”, “graphical user interface”, display of an electronic device” and “ non-tangible computer readable medium”.
The limitations of “receiving” and “transmit” are an additional element and is insignificant extra-solution activity as retrieval/receiving of data (i.e. mere data gathering) such as 'obtaining information' as identified in MPEP 2106.05(g) and does not provide integration into a practical application. “a system”, “a processing system”, “AI”, “a data source”, “graphical user interface”, display of an electronic device” and “ non-tangible computer readable medium”, note that these recited additional elements are a high-level recitation of generic computer components to perform the mental process and applied on a computer as in MPEP 2106.05(f), which does not provide integration into a practical application.
Step 2B Analysis: the conclusions for the additional elements representing mere implementation using a computer are carried over and do not provide significantly more. With respect to the "receiving and transmit” limitation is identified as insignificant extra-solution activity above when re-evaluated this element is well-understood, routine, and conventional as evidenced by the court cases in 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); … 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);" and thus remains insignificant extra-solution activity that does not provide significantly more. Furthermore, the limitations “AI” are generally linking the use of the judicial exception to a particular technological environment or field of use, MPEP 2106.05(h). Lastly the recitation of “a system”, “a processing system”, “AI”, “a data source”, “graphical user interface”, display of an electronic device” and “ non-tangible computer readable medium” are recitation of generic computer components to perform the mental process and applied on a computer as in MPEP 2106.05(f).
Claims 2-4, 7, 10-14, 16 and 19, recite limitations that are additional elements of using a computer as a tool to perform the recited step amount to no more than mere instructions to apply the abstract idea using generic computer component.
Claims 5-6, 8-9, 17, and 20, recites limitations abstract ideas previously identified in the independent claims, that are mental process which can be performed by the human mind.
Claims 6, 8, 17, and 20 recited some limitation that additional elements such as “transmit…” is identified as insignificant extra-solution activity above when re-evaluated this element is well-understood, routine, and conventional as evidenced by the court cases in 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); … 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);" and thus remains insignificant extra-solution activity that does not provide significantly more.
Therefore, the claims as a whole does not change this conclusion and the claims are ineligible.
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 (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 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, 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) 1-10 are rejected under 35 U.S.C. 103 as being unpatentable over Hurwitz et al. (US Pub. 2024/0311404) (Eff filing date of app: 9/4/2023) (Hereinafter Hurwitz) in view of Jain et al. (US Pub. 2024/0256582) (Eff filing date of app: 6/28/2023) (Hereinafter Jain).
As to claims 1, 15, and 18, Hurwitz teaches a system, comprising:
a processing system comprising an artificial intelligence (AI) engine (see p. 53, “FIG. 1A illustrates a system 100 for providing natural language based conversational AI consistent with some embodiments of this disclosure. In system 100, users and external services interact with a conversational query-response platform (CQRP) 110 using user devices”), wherein the
processing system is configured to:
receive a set of data from a data source (see p. 59, “CQRP 110 may include an analytics service 122. Analytics service 122 uses the extracted user intent, context, and time period from natural language service 118 to provide the required data that will be needed to create the response to the user query.”);
transmit one or more queries to the AI engine to elicit search and identification of one or more responses based on a data set comprising the one or more subsets of data, wherein the one or more responses include a text-based response and a graphical response associated with the text-based response (see p. 59-60, “analytics service 122 will retrieve the list of stocks in the user portfolio, obtain real-time price information and perform the necessary calculations such as the asset allocation over the indicated timeframe to provide an analytics result. Analytics service 122 may retrieve data from external systems 150-1 . . . 150-n via external services interface 128. For example, real-time stock price information may be retrieved from external systems 150.
[0060] CQRP 110 may include an infographic service 124. Infographic service 124 uses the analytics result of the analytics service 122 to generate engaging graphical representations”); and
transmit the text-based response and the graphical response to a graphical user interface for presentation on a display of an electronic device comprising the graphical user interface (see p. 57, “. Where users have not asked queries, AI playlist service 116 may generate queries, query playlists, and provide responses (using other components of CQRP 110 as required) and provides these to the user to thereby encourage usage of the system and educate the user about the range of queries that can be posed to CQRP 110. AI playlist service 116 may further analyze user data..” and p. 69, “FIGS. 2A-2C illustrate example graphical user interfaces for displaying a natural language conversational AI view consistent with some embodiments of this disclosure.”) and fig 2A).
Hurwitz does not expressly teach divide the set of data into one or more subsets of data; and transmit the one or more subsets of data to the AI engine.
Jain teaches search with generative artificial intelligent, see abstract, in which he teaches divide the set of data into one or more subsets of data (see claim 2, “the subset of the set of search results.”; and
transmit the one or more subsets of data to the AI engine (see p. 18, “In some embodiments, a search and knowledge management system may be used to identify the top ten documents for a particular search query and the inputted prompt to a machine learning model (e.g., a generative AI model) may include the top ten documents along with a text directive to reference a subset of the top ten documents that were used to generate the response.”).
It would have been obvious to a person having ordinary skill in the
art at the time the invention was made to have modified Hurwitz by the teaching of Jain, because divide the set of data into one or more subsets of data; and transmit the one or more subsets of data to the AI engine, would enable the method because, “One technical benefit of performing incremental crawls on a subset of documents within a data source that comprise frequently searched documents or documents that have a high rate of data deletions is that the load on the data source may be reduced and the number of application programming interface (API) calls to the data source may be reduced.”. See p. 39.
As to claims 2 and 16, Hurwitz as modified teaches wherein the processing system is further configured to receive a second set of data (see Jain, p. 41, “second set of index entries”).
As to claim 3, Hurwitz as modified teaches wherein the processing system is further
configured to receive the second set of data from a second data source as real-time acquired data (see Jain, p. 26, “In some embodiments, the permissions-aware search and knowledge management system may allow a user to search for content and resources across different workplace applications and data sources that are authorized to be viewed by the user…”).
As to claim 4, Hurwitz as modified teaches wherein the processing system is further
configured to receive the second set of data in parallel with receiving the set of data (see Jain, p. 23. “In some cases, when generating the summary of the set of search results, the number of reference documents passed to a generative AI model or included with the inputted prompt may be limited to a first number of documents (e.g., at most ten documents) in order to meet a required latency, and then in the background a second number of documents (e.g., at least 100 documents) greater than the first number of documents may be passed to the generative AI model or included with a second inputted prompt in order to generate a more comprehensive summary that is then stored within a database for future retrieval.”).
As to claim 5, Hurwitz as modified teaches wherein the processing system is further
configured to divide the second set of data into one or more second subsets of data in parallel with dividing the set of data into one or more subsets of data (see Jain p. 39, incremental subset of data, where it will be done to the first and all the subsequent data).
As to claims 6 and 17, Hurwitz as modified teaches wherein the processing system is
further configured to:
divide the second set of data into one or more second subsets of data (see Jain p. 39, incremental subset of data, where it will be done to the first and all the subsequent data);
transmit the one or more second subsets of data to the AI engine (see p. 18, “In some embodiments, a search and knowledge management system may be used to identify the top ten documents for a particular search query and the inputted prompt to a machine learning model (e.g., a generative AI model) may include the top ten documents along with a text directive to reference a subset of the top ten documents that were used to generate the response.”); and
elicit search and identification of the one or more responses based on the data set as additionally comprising the one or more second subsets of data (see abstract, search results).
As to claims 7 and 19, Hurwitz as modified teaches wherein the processing system is
further configured to receive an indication of a user input from the graphical user interface as a second query (see Jain. P. 2, user access search engine).
As to claims 8 and 20, Hurwitz as modified teaches wherein the AI engine of the
processing system is configured to:
search the data set and identify one or more second responses, wherein the one or more second responses include a second text-based response and a second graphical response associated with the second text-based response (see Hurwitz, fig. 3B, queries and responses); and
transmit the second text-based response and the second graphical response to the graphical user interface for presentation on the display (see Hurwitz, fig. 3B, queries and responses and p. 83-84).
As to claim 9, Hurwitz as modified teaches wherein the AI engine of the processing
system is configured to determine whether the second query overlaps with an additional query and generate one or more second responses related to the second query and the additional query as a guided response (see Jain, claim 4, similar search query).
As to claim 10, Hurwitz as modified teaches wherein the one or more responses
include an audio response or a video response, wherein the wherein the processing system is further configured to transmit the audio response or the video response to the graphical user interface for presentation on the display (see Hurwitz, p. 71, “responses that may be textual, graphical, audio or video”).
Claim(s) 11-14 are rejected under 35 U.S.C. 103 as being unpatentable over Hurwitz and Jain as applied to claims 1-10 above, and further in view of Siebel et al (US Pub 2024/0202221) (Eff filing date of app: 12/15/2023) (Hereinafter Siebel).
As to claim 11, Hurwitz as modified does not teach wherein the processing system is
further configured to transmit the one or more queries to the AI engine to elicit search and identification of at least one approach to prevent an incident at an asset located at a particular geolocation as the one or more responses.
Siebel teaches generative artificial intelligence enterprise search, see abstract, in
which he teaches wherein the processing system is further configured to transmit the one or more queries to the AI engine to elicit search and identification of at least one approach to prevent an incident at an asset located at a particular geolocation as the one or more responses (see p. 66, “Further processing can include data modeling feature inspection and/or machine learning model simulations to select one or more appropriate analysis channels…, geolocation”).
It would have been obvious to a person having ordinary skill in the art at the time the invention was made to have modified Hurwitz by the teaching of Siebel., because wherein the processing system is further configured to transmit the one or more queries to the AI engine to elicit search and identification of at least one approach to prevent an incident at an asset located at a particular geolocation as the one or more responses, would enable the method to provide the correct information.
As to claim 12, Hurwitz as modified teaches wherein the processing system is further
configured to transmit the one or more queries to the AI engine to elicit search and identification of estimated consumption of products and associated cost at an asset located at a particular geolocation as the one or more responses (see Siebel, p. 66, “Further processing can include data modeling feature inspection and/or machine learning model simulations to select one or more appropriate analysis channels. Example data objects can include accounts, products, employees, suppliers, opportunities, contracts, locations, digital portals, geolocation manufacturers, supervisory control and data acquisition (SCADA) information, open manufacturing system (OMS) information, inventories, supply chains, bills of materials, transportation services, maintenance logs, and service logs”).
As to claim 13, Hurwitz as modified teaches wherein the processing system is further
configured to transmit the one or more queries to the AI engine to elicit search and identification of life expectancy of equipment at an asset located at a particular geolocation, to elicit identification of a timing or type of repair of the equipment, or to elicit identification of one or more replacement options for replacement of the equipment as the one or more responses (see Siebel, p. 99 replace).
As to claim 14, Hurwitz as modified teaches wherein the processing system is further configured to transmit the one or more queries to the AI engine to elicit identification of combinations of equipment, parameters, and services to improve production of assets in a geo fence region as the one or more responses (see Siebel, p. 66, “Further processing can include data modeling feature inspection and/or machine learning model simulations to select one or more appropriate analysis channels. Example data objects can include accounts, products, employees, suppliers, opportunities, contracts, locations, digital portals, geolocation manufacturers, supervisory control and data acquisition (SCADA) information, open manufacturing system (OMS) information, inventories, supply chains, bills of materials, transportation services, maintenance logs, and service logs”).
Claims 12-14 have the same motivation of claim 11, above.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BELIX M ORTIZ DITREN whose telephone number is (571)272-4081. The examiner can normally be reached M-F 9am -5pm.
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BELIX M. ORTIZ DITREN
Primary Examiner
Art Unit 2164
/Belix M Ortiz Ditren/Primary Examiner, Art Unit 2164
Prosecution Insights