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
Claims 21-26 have been added. Claims 17-18 have been canceled. Claims 1-16 and 19-26 are pending and rejected in the application. This action is Final.
Objected Subject Matter
Claims 21, 22, 23, and 24 are objected to as being dependent upon a rejected base claim, but would be allowable if all the objected claims were rewritten in independent form including all of the limitations of the base claim and all intervening claims. The amendment will not overcome the 35 USC § 101 rejection.
Arguments
Applicant Argues
For claims 1, 5-8, 11-13, 15-16 and 19-20, the claims recite the practical application of resolving an unstructured query. Such limitations amount to an improvement in the functioning of a computer, as discussed in MPEP § 2106.05(a), by not requiring additional queries and/or separate inputs for resolving an unstructured query. Additionally, such limitations are a specific limitation other than what is well-understood, routine, conventional activity in the field, as discussed in MPEP § 2106.05(d). Claims 2-4, 10, and 14 depend from independent claims 1, 8, and 13 respectively. Accordingly, claims 2-4, 10, and 14 recite the practical application at least based on their dependency on independent claims 1, 8, and 13.
Examiner Responds:
Applicant's 35 USC § 101 arguments with respect to claims 1-16 and 19-26 have been fully considered but they are not persuasive.
MPEP 2106.04(d)(1) provides:
“The courts have not provided an explicit test for this consideration, but have instead illustrated how it is evaluated in numerous decisions. These decisions, and a detailed explanation of how examiners should evaluate this consideration are provided in MPEP § 2106.05(a). In short, first the specification should be evaluated to determine if the disclosure provides sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. The specification need not explicitly set forth the improvement, but it must describe the invention such that the improvement would be apparent to one of ordinary skill in the art. Conversely, if the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology. Second, if the specification sets forth an improvement in technology, the claim must be evaluated to ensure that the claim itself reflects the disclosed improvement. That is, the claim includes the components or steps of the invention that provide the improvement described in the specification. The claim itself does not need to explicitly recite the improvement described in the specification (e.g., "thereby increasing the bandwidth of the channel").”
This claim is directed to a generic information retrieval and query-processing workflow that merely automates conventional search and data aggregation techniques using generic computer components. The steps of receiving a user query, converting the query into structured search requests, identifying appropriate data sources, querying those sources, aggregating returned results, filtering the aggregated results, and displaying the final output constitute a series of routine data processing operations that can be performed mentally or by a human researcher using ordinary tools. The recitation of a “first LLM” and a “second LLM” merely identifies the use of known artificial intelligence models as tools to perform the abstract tasks of query reformulation and result filtering, without describing any specific technological improvement to the operation of the models, the computer system, or the knowledge sources themselves. Accordingly, the claim is directed to the abstract idea of collecting, analyzing, organizing, and presenting information, implemented on generic computing devices, and therefore falls within the scope of subject matter that is well-understood, routine, and conventional under Alice Step 1 and lacks significantly more under Alice Step 2.
Applicant Argues
Li fails to disclose the features of claims 1, 8, 13, and 19. Specifically, Li fails to disclose "providing the unstructured query to a first large language model (LLM) to produce a plurality of structured queries" as recited in claim 1 and "a first large language model (LLM) produces a plurality of structured queries based on the unstructured query" as recited in claim 13. At most, Li discloses providing the unstructured query to an LLM to produce a plurality of interpretations of the search query (e.g. "parsing result represents a semantic interpretation of the natural language input and each parsing result comprises respective mappings of one or more domain properties to one or more words of the natural language input"). Li [0281]. Such interpretations are not structured queries as recited by claims 1 and 13. Claims 4-6 and 15 depend from independent claims 1 and 13 respectively. Accordingly, the combination of Li and Gomes fails to disclose, teach, and/or suggest claims 4-6 and 15 at least based on their dependency on independent claims 1 and 13.
Examiner Responds:
Applicant's 35 USC § 103 arguments with respect to claims 1-16 and 19-26 have been fully considered but they are not persuasive. Li discloses providing an unstructured natural language query to a neural-network-based natural language understanding system that generates multiple semantic parsing results corresponding to different interpretations of the query. See Li, paragraph [0281]. Each parsing result includes mappings of domain properties to words of the natural language input and is used to query one or more selected domain sources to obtain corresponding results. See Li, paragraph [0282]. One of ordinary skill in the art would understand these parsing results to constitute structured queries because they transform the unstructured natural language input into machine-readable query representations containing structured semantic components usable for querying downstream knowledge sources. The claims do not require any particular query syntax or database-specific format for the “structured queries,” nor do they exclude semantic query representations generated by a neural network model. Accordingly, Li’s semantic parsing outputs reasonably correspond to the claimed plurality of structured queries produced from the unstructured query. Further, Li discloses selecting respective knowledge sources based on aspects of the parsed query interpretations and obtaining corresponding results from those sources, as recited in the claims. Therefore, Li teaches or at least suggests the disputed limitations of independent claims 1 and 13, and claims 4-6 and 15 fall therewith.
Applicant Argues
Additionally, Li fails to disclose "providing the unstructured query to a first large language model (LLM) to produce a query understanding object, wherein the query understanding object includes a plurality of tasks, and each task of the plurality of tasks includes a respective category and respective one or more properties" as recited in claim 8.
Examiner Responds:
Applicant's 35 USC § 103 arguments with respect to claims 1-16 and 19-26 have been fully considered but they are not persuasive. Li discloses processing a natural language query using a neural-network-based natural language understanding framework to identify a task corresponding to the user's intent and one or more associated property nodes. See Li ¶¶ 227-229. Li further discloses generating semantic representations of the natural language input, including mappings between query terms, tasks, and properties within an ontology-based knowledge framework. See, e.g., Li ¶¶ 227-229, 281-282. The identified task corresponds to the claimed respective category, while the associated property nodes correspond to the claimed one or more properties. Under the broadest reasonable interpretation, Li's semantic representation of the query constitutes the claimed query understanding object because it organizes the unstructured natural language query into a structured representation containing task information and associated properties for subsequent processing. The claim does not require any particular format, schema, or nomenclature for the query understanding object. Accordingly, Li teaches or at least suggests producing a query understanding object that includes tasks and associated properties, and therefore teaches or renders obvious the disputed limitation of claim 8. Therefore, the rejection is maintained.
Applicant Argues
Additionally, Li fails to disclose…and "the filtered results are generated using a first large language model (LLM) that produces a query understanding object, wherein the query understanding object includes a plurality of tasks, and each task of the plurality of tasks includes a respective category and respective one or more properties" as recited in claim 19.
Examiner Responds:
Applicant's 35 USC § 103 arguments with respect to claims 1-16 and 19-26 have been fully considered but they are not persuasive. Applicant's arguments have been considered but are not persuasive. Li discloses processing a natural language query using a neural-network-based natural language understanding framework to determine a task corresponding to the user's intent and associated property nodes. See Li ¶¶ 227-229. Li further discloses generating semantic representations of the query and mapping query elements to domain properties for downstream processing. See Li ¶¶ 281-282. The identified task corresponds to the claimed category, and the associated property nodes correspond to the claimed one or more properties. Under the broadest reasonable interpretation, Li's semantic representation constitutes the claimed query understanding object because it structures the unstructured query into task-based and property-based components used for subsequent processing. Accordingly, Li teaches or at least suggests the disputed limitation of claim 19, and the rejection is maintained.
Applicant Argues
The combination of Li, Gomes, and Chao fail to disclose, teach, and/or suggest the features of claim 25, the replacement for claim 17. Specifically, Chao fails to disclose "displaying, via the one or more display generation components, a user interface including an affordance to display an explanation as to why the response is relevant to the unstructured query; while displaying the user interface including the response and the affordance to display the…etc.
Examiner Responds:
Applicant's 35 USC § 103 arguments with respect to claims 21-40 have been considered but are moot in view of the new ground(s) of rejection.
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 1-16 and 19-26 are rejected under 35 U.S.C. 101 because the claims are directed to non-statutory subject matter.
Claims 1-7, 21, 22, and 24 are ineligible:
As to step one, claim 1 recites a series of steps and, therefore, is a process which is a statutory category.
As to step 2A-prong one, claim 1 recites a method, comprising, at a server computing device:
providing the unstructured query to a first large language model (LLM) to produce a plurality of structured queries;
for each structured query of the plurality of structured queries:
identifying, based on at least one aspect of the structured query, respective one or more knowledge sources to produce respective results for the structured query, and providing the structured query to the respective one or more knowledge sources to produce the respective results;
aggregating the results to produce aggregated results;
providing the aggregated results to a second LLM to produce filtered results.
The limitations, as drafted, are a process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of the generic computer components. The “a client computing device”, “a first large language model (LLM)”, and “a second LLM” amounts to mere generic computer components. That is other than reciting “a client computing device”, “a first large language model (LLM)”, and “a second LLM” nothing in the claim element precludes the steps from practically being performed in the mind. Thus, claim 1 is not patentable eligible under 35 U.S.C. 101.
For example, but for a first large language model (LLM), “providing the unstructured query to a first large language model (LLM) to produce a plurality of structured queries;” encompasses mentally a person producing a plurality of structured queries from an unstructured query.
Next, but for a first large language model (LLM), “for each structured query of the plurality of structured queries:
identifying, based on at least one aspect of the structured query, respective one or more knowledge sources to produce respective results for the structured query, and providing the structured query to the respective one or more knowledge sources to produce the respective results;” encompasses mentally a person for each structured query of the plurality of structured queries, identifying, based on at least one aspect of the structured query, respective one or more knowledge sources to produce respective results for the structured query, and providing the structured query to the respective one or more knowledge sources to produce the respective results.
Next, but for a first large language model (LLM), “aggregating the results to produce aggregated results;” encompasses mentally a person aggregating the results to produce aggregated results.
Next, but for a second LLM, “providing the aggregated results to a second LLM to produce filtered results;” encompasses mentally a person providing the aggregated results to a second LLM to produce filtered results. The mere nominal recitation of a system do not take the claim limitations out of the mental processes grouping. If claim limitation(s), under its broadest reasonable interpretation, covers performance of the limitation(s) in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
As to Step 2A-prong two, the judicial exception is not integrated into a practical application. Claim 1 recites receiving an unstructured query from a client computing device; and
causing the client computing device to display at least a portion of the filtered results.
Next, “receiving an unstructured query from a client computing device;” encompasses insignificant extra-solution activity and amounts to mere data gathering (see MPEP 2106.05(g)) and, as stated above, a client computing device is a mere generic computer component.
In addition, “causing the client computing device to display at least a portion of the filtered results.” amounts to an insignificant post extra-solution activity of outputting data (see MPEP 2106.05(g)). Accordingly, 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. Thus, the claim is directed to an abstract idea. Accordingly, 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. Thus, the claim is directed to an abstract idea.
As to step 2B, the claim as a whole does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, claim 1 additional limitation amounts to no more than mere extra solution activity and generic computer components do not amount to significantly more than the judicial exception because the generic computer components are implementing the limitations in a generic manner. Thus, even when viewed as a whole, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea. Mere retrieving and filtering data cannot provide an inventive concept. Thus, claim 1 is not patentable eligible under 35 USC 101.
Under the 2019 PEG, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B. Here, the “receiving an unstructured query from a client computing device” and “causing the client computing device to display at least a portion of the filtered results.” steps are considered to be extra-solution activity in Step 2A, and thus it is re-evaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The specification does not provide any indication that the limitations are anything other than extra solution activity.
Here, “receiving an unstructured query from a client computing device” is merely data gathering. OIP Techs court decision cited in MPEP 2106.05(d)(II) indicate that mere retrieving data is a well-understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here).
Here, “causing the client computing device to display at least a portion of the filtered results.” is merely displaying filtered results. U.S. Patent Publication (2024/0134905) paragraph[0054] is proof of displaying filtered data and shows the limitation is a well-understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here).
Accordingly, a conclusion that the “receiving an unstructured query from a client computing device” and “causing the client computing device to display at least a portion of the filtered results.” steps are well-understood, routine, conventional activity is supported under Berkheimer Option 2. For these reasons, there is no inventive concept in the claim, and thus it is ineligible.
Next, “prior to causing the client computing device to display the at least a portion of the filtered results: providing the filtered results to a third LLM to assign, to each result of one or more results of the filtered results, a respective explanation as to why the result is relevant to the unstructured query.” of dependent claim 2 is abstract because the claim encompasses mentally a person providing the filtered results to a third LLM to assign, to each result of one or more results of the filtered results, a respective explanation as to why the result is relevant to the unstructured query. Accordingly, 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. Thus, claim 2 is directed to an abstract idea.
Next, “prior to causing the client computing device to display the at least a portion of the filtered results: providing the filtered results to a third LLM to assign, to the filtered results, one or more words that summarize the filtered results.” of dependent claim 3 is abstract because the claim encompasses mentally a person providing the filtered results to a third LLM to assign, to the filtered results, one or more words that summarize the filtered results. Accordingly, 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. Thus, claim 3 is directed to an abstract idea.
Next, “prior to causing the client computing device to display the at least a portion of the filtered results: providing the filtered results to at least one artificial intelligence (AI) engine to generate media content that pertains to the filtered results, wherein the media content comprises image content, audio content, and/or video content.” of dependent claim 4 is abstract because the claim encompasses mentally a person providing the filtered results to at least one artificial intelligence (AI) engine to generate media content that pertains to the filtered results, wherein the media content comprises image content, audio content, and/or video content. Accordingly, 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. Thus, claim 4 is directed to an abstract idea.
Next, “wherein the one or more knowledge sources include: at least one web search engine” of dependent claim 5 is abstract because the claim amounts to mere generic computer components. In addition, “at least one question and answer (Q&A) knowledge source” of dependent claim 5 is abstract because the claim amounts to mere generic computer components. Next, “at least one knowledge graph” of dependent claim 5 is abstract because the claim encompasses mentally a person determining at least one knowledge graph. Further, “at least one approximate nearest-neighbor (ANN) index;” is abstract because the claim amounts to mere generic computer components. Next, “at least one other LLM; or some combination thereof.” is abstract because the claim amounts to mere generic computer components. Accordingly, 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. Thus, claim 5 is directed to an abstract idea.
Next, “wherein: at least one structured query of the plurality of structured queries includes at least one placeholder value;” of dependent claim 6 is abstract because the claim encompasses mentally a person determining at least one structured query of the plurality of structured queries includes at least one placeholder value. Next, “and at least one respective result for at least one other structured query of the plurality of structured queries is assigned to the at least one placeholder value.” of dependent claim 6 is abstract because the claim encompasses mentally a person determining at least one respective result for at least one other structured query of the plurality of structured queries is assigned to the at least one placeholder value. Accordingly, 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. Thus, claim 6 is directed to an abstract idea.
Next, “wherein: the unstructured query is paired with at least one conversation history that is associated and received from the client computing device;” of dependent claim 7 is abstract because the claim encompasses insignificant extra-solution activity and amounts to mere data gathering (see MPEP 2106.05(g)). Next, “the at least one conversation history is provided to: the first LLM along with the unstructured query, and/or the second LLM along with the filtered results;” of dependent claim 7 is abstract because the claim encompasses insignificant extra-solution activity and amounts to mere data gathering (see MPEP 2106.05(g)). Next, “and the at least one conversation history is forgotten by the server computing device in conjunction with providing the aggregated results to the second LLM to produce filtered results.” of dependent claim 7 is abstract because the claim encompasses insignificant extra-solution activity and amounts to mere data gathering (see MPEP 2106.05(g)). The claim does not recite additional limitations to integrate the abstract idea into a practical application because the claims do not impose any meaningful limits on practicing the abstract idea. The claim is insignificant extra-solution because 2106.05(d) court decision OIP Techs court states retrieving data is extra solution activity. Thus, claim 7 is not patent eligible under 35 USC 101.
Next, “in accordance with a determination that the first LLM is in a first mode, the plurality of structured queries do not include a structured query that relies on a result of another structured query;” of dependent claim 21 is abstract because the claim encompasses mentally a person determining in accordance with a determination that the first LLM is in a first mode, the plurality of structured queries do not include a structured query that relies on a result of another structured query. Further, “in accordance with a determination that the first LLM is in a second mode, the plurality of queries includes a second structured query that relies on a result of a first structured query included in the plurality of queries;” of dependent claim 21 is abstract because the claim encompasses mentally a person determining in accordance with a determination that the first LLM is in a second mode, the plurality of queries includes a second structured query that relies on a result of a first structured query included in the plurality of queries. Next, “the second mode is different from the first mode” of dependent claim 21 is abstract because the claim encompasses mentally a person determining the second mode is different from the first mode. Next, “the second structured query is different from the first structured query.” of dependent claim 21 is abstract because the claim encompasses mentally a person determining the second structured query is different from the first structured query. Accordingly, 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. Thus, claim 21 is directed to an abstract idea.
Next, “in response to producing the plurality of structured queries: in accordance with a determination that the plurality of structured queries has an expected first latency, implementing a latency limitation;” of dependent claim 22 is abstract because the claim encompasses mentally a person determining in response to producing the plurality of structured queries: in accordance with a determination that the plurality of structured queries has an expected first latency, implementing a latency limitation. Further, “in accordance with a determination that the plurality of structured queries has an expected second latency, forgoing implementation of the latency limitation, wherein the expected second latency is different from the expected first latency.” of dependent claim 22 is abstract because the claim encompasses mentally a person determining in accordance with a determination that the plurality of structured queries has an expected second latency, forgoing implementation of the latency limitation, wherein the expected second latency is different from the expected first latency. Accordingly, 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. Thus, claim 22 is directed to an abstract idea.
Next, “wherein providing the unstructured query to the first LLM to produce the plurality of structured queries includes generating, using the first LLM, the plurality of structured queries, and wherein a combination of performing the plurality of structured queries results in a response to the unstructured query.” of dependent claim 24 is abstract because the claim encompasses mentally a person determining wherein providing the unstructured query to the first LLM to produce the plurality of structured queries includes generating, using the first LLM, the plurality of structured queries, and wherein a combination of performing the plurality of structured queries results in a response to the unstructured query.. Accordingly, 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. Thus, claim 24 is directed to an abstract idea.
Claims 8-12 and 23 are ineligible:
As to step one, claim 8 recites a series of steps and, therefore, is a process which is a statutory category.
As to step 2A-prong one, claim 8 recites a method, comprising, at a server computing device:
providing the unstructured query to a first large language model (LLM) to produce a query understanding object, wherein the query understanding object includes a plurality of tasks, and each task of the plurality of tasks includes a respective category and respective one or more properties;
for each task of the plurality of tasks:
identifying, based on the respective category and the respective one or more properties, respective one or more knowledge sources to produce respective results for the task, and providing the task to the respective one or more knowledge sources to produce the respective results;
aggregating the results to produce aggregated results;
providing the aggregated results to a second LLM to produce filtered results.
The limitations, as drafted, are a process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of the generic computer components. The “a client computing device”, “a first large language model (LLM)”, and “a second LLM” amounts to mere generic computer components. That is other than reciting “a client computing device”, “a first large language model (LLM)”, and “a second LLM” nothing in the claim element precludes the steps from practically being performed in the mind. Thus, claim 8 is not patentable eligible under 35 U.S.C. 101.
For example, but for a first large language model (LLM), “providing the unstructured query to a first large language model (LLM) to produce a query understanding object, wherein the query understanding object includes a plurality of tasks, and each task of the plurality of tasks includes a respective category and respective one or more properties;” encompasses mentally a person producing a query understanding object, wherein the query understanding object includes a plurality of tasks, and each task of the plurality of tasks includes a respective category and respective one or more properties.
Next, but for a first large language model (LLM), “for each task of the plurality of tasks:
identifying, based on the respective category and the respective one or more properties, respective one or more knowledge sources to produce respective results for the task, and providing the task to the respective one or more knowledge sources to produce the respective results;” encompasses mentally a person for each task of the plurality of tasks, identifying, based on the respective category and the respective one or more properties, respective one or more knowledge sources to produce respective results for the task, and providing the task to the respective one or more knowledge sources to produce the respective results.
Next, but for a first large language model (LLM), “aggregating the results to produce aggregated results;” encompasses mentally a person aggregating the results to produce aggregated results.
Next, but for a second LLM, “providing the aggregated results to a second LLM to produce filtered results;” encompasses mentally a person providing the aggregated results to a second LLM to produce filtered results. The mere nominal recitation of a system does not take the claim limitations out of the mental processes grouping. If claim limitation(s), under its broadest reasonable interpretation, covers performance of the limitation(s) in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
As to Step 2A-prong two, the judicial exception is not integrated into a practical application. Claim 8 recites receiving an unstructured query from a client computing device; and
causing the client computing device to display at least a portion of the filtered results.
Next, “receiving an unstructured query from a client computing device;” encompasses insignificant extra-solution activity and amounts to mere data gathering (see MPEP 2106.05(g)) and, as stated above, a client computing device is a mere generic computer component.
In addition, “causing the client computing device to display at least a portion of the filtered results.” amounts to an insignificant post extra-solution activity of outputting data (see MPEP 2106.05(g)). Accordingly, 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. Thus, the claim is directed to an abstract idea. Accordingly, 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. Thus, the claim is directed to an abstract idea.
As to step 2B, the claim as a whole does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, claim 8 additional limitation amounts to no more than mere extra solution activity and generic computer components do not amount to significantly more than the judicial exception because the generic computer components are implementing the limitations in a generic manner. Thus, even when viewed as a whole, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea. Mere retrieving and filtering data cannot provide an inventive concept. Thus, claim 8 is not patentable eligible under 35 USC 101.
Under the 2019 PEG, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B. Here, the “receiving an unstructured query from a client computing device” and “causing the client computing device to display at least a portion of the filtered results.” steps are considered to be extra-solution activity in Step 2A, and thus it is re-evaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The specification does not provide any indication that the limitations are anything other than extra solution activity.
Here, “receiving an unstructured query from a client computing device” is merely data gathering. OIP Techs court decision cited in MPEP 2106.05(d)(II) indicate that mere retrieving data is a well-understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here).
Here, “causing the client computing device to display at least a portion of the filtered results.” is merely displaying filtered results. U.S. Patent Publication (2024/0134905) paragraph[0054] is proof of displaying filtered data and shows the limitation is a well-understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here).
Accordingly, a conclusion that the “receiving an unstructured query from a client computing device” and “causing the client computing device to display at least a portion of the filtered results.” steps are well-understood, routine, conventional activity is supported under Berkheimer Option 2. For these reasons, there is no inventive concept in the claim, and thus it is ineligible.
Next, “prior to causing the client computing device to display the at least a portion of the filtered results: providing the filtered results to a third LLM to assign, to each result of one or more results of the filtered results, a respective explanation as to why the result is relevant to the unstructured query, providing the filtered results to the third LLM to assign, to the filtered results, one or more words that summarize the filtered results, or some combination thereof.” of dependent claim 9 is abstract because the claim encompasses mentally a person providing the filtered results to a third LLM to assign, to each result of one or more results of the filtered results, a respective explanation as to why the result is relevant to the unstructured query, providing the filtered results to the third LLM to assign, to the filtered results, one or more words that summarize the filtered results, or some combination thereof. Accordingly, 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. Thus, claim 9 is directed to an abstract idea.
Next, “prior to causing the client computing device to display the at least a portion of the filtered results: providing the filtered results to at least one artificial intelligence (AI) engine to generate media content that pertains to the filtered results, wherein the media content comprises image content, audio content, and/or video content.” of dependent claim 10 is abstract because the claim encompasses mentally a person prior to causing the client computing device to display the at least a portion of the filtered results: providing the filtered results to at least one artificial intelligence (AI) engine to generate media content that pertains to the filtered results, wherein the media content comprises image content, audio content, and/or video content. Accordingly, 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. Thus, claim 10 is directed to an abstract idea.
Next, “wherein: the respective category of a given task corresponds to album information, artist information, beats per minute (BPM) information, composer information, conductor information, content group information, copyright information, cover art information, disk number information, encoding information, genre information, initial key information, mood information, original artist information, publisher information, release date information, subtitle information, track title information, track number information, and/or year information” of dependent claim 11 is abstract because the claim encompasses mentally a person determining the respective category of a given task corresponds to album information, artist information, beats per minute (BPM) information, composer information, conductor information, content group information, copyright information, cover art information, disk number information, encoding information, genre information, initial key information, mood information, original artist information, publisher information, release date information, subtitle information, track title information, track number information, and/or year information. Next, “and the respective one or more properties of the given task function as values for the respective category of the given task.” of dependent claim 11 is abstract because the claim encompasses mentally a person determining the respective one or more properties of the given task function as values for the respective category of the given task. Accordingly, 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. Thus, claim 11 is directed to an abstract idea.
Next, “wherein: the unstructured query is paired with at least one conversation history that is associated and received from the client computing device;” of dependent claim 12 is abstract because the claim encompasses insignificant extra-solution activity and amounts to mere data gathering (see MPEP 2106.05(g)). Next, “the at least one conversation history is provided to: the first LLM along with the unstructured query, and/or the second LLM along with the filtered results;” of dependent claim 12 is abstract because the claim encompasses insignificant extra-solution activity and amounts to mere data gathering (see MPEP 2106.05(g)). Next, “and the at least one conversation history is forgotten by the server computing device in conjunction with providing the aggregated results to the second LLM to produce filtered results.” of dependent claim 12 is abstract because the claim encompasses insignificant extra-solution activity and amounts to mere data gathering (see MPEP 2106.05(g)). The claim does not recite additional limitations to integrate the abstract idea into a practical application because the claims do not impose any meaningful limits on practicing the abstract idea. The claim is insignificant extra-solution because 2106.05(d) court decision OIP Techs court states retrieving data is extra solution activity. Thus, claim 12 is not patent eligible under 35 USC 101.
Next, “wherein the query understanding object includes an expanded query, generated by the first LLM, of the unstructured query, and wherein the expanded query includes additional information not included in the unstructured query.” of dependent claim 23 is abstract because the claim encompasses mentally a person determining wherein the query understanding object includes an expanded query, generated by the first LLM, of the unstructured query, and wherein the expanded query includes additional information not included in the unstructured query. Accordingly, 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. Thus, claim 23 is directed to an abstract idea.
Claims 13-16 are ineligible:
As to step one, claim 13 recites a series of steps and, therefore, is a process which is a statutory category.
As to step 2A-prong one, claim 13 recites a method, comprising, by an application executing on a client computing device:
a first large language model (LLM) produces a plurality of structured queries based on the unstructured query, each structured query of the plurality of structured queries is provided to respective one or more knowledge sources that are selected based on at least one aspect of the structured query and provide respective results, and the results are aggregated and filtered by a second LLM to generate the filtered results; and
in response to receiving the filtered results, performing at least one action associated with the filtered results.
The limitations, as drafted, are a process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of the generic computer components. The “a client computing device”, “an operating system”, “a first large language model (LLM)”, and “a second LLM” amounts to mere generic computer components. That is other than reciting “a client computing device”, “an operating system”, “a first large language model (LLM)”, and “a second LLM” nothing in the claim element precludes the steps from practically being performed in the mind. Thus, claim 13 is not patentable eligible under 35 U.S.C. 101.
For example, but for a first large language model (LLM) and second LLM, “a first large language model (LLM) produces a plurality of structured queries based on the unstructured query, each structured query of the plurality of structured queries is provided to respective one or more knowledge sources that are selected based on at least one aspect of the structured query and provide respective results, and the results are aggregated and filtered by a second LLM to generate the filtered results;” encompasses mentally a person produces a plurality of structured queries based on the unstructured query, each structured query of the plurality of structured queries is provided to respective one or more knowledge sources that are selected based on at least one aspect of the structured query and provide respective results, and the results are aggregated and filtered to generate the filtered results.
Next, but for a first large language model (LLM) and second LLM, “in response to receiving the filtered results, performing at least one action associated with the filtered results.” encompasses mentally a person in response to receiving the filtered results, performing at least one action associated with the filtered results. The mere nominal recitation of a system does not take the claim limitations out of the mental processes grouping. If claim limitation(s), under its broadest reasonable interpretation, covers performance of the limitation(s) in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
As to Step 2A-prong two, the judicial exception is not integrated into a practical application. Claim 13 recites obtaining an unstructured query from a user of the client computing device;
in response to obtaining the unstructured query, providing the unstructured query to an operating system (OS) executing on the client computing device;
in response to providing the unstructured query to the OS, receiving filtered results associated with the unstructured query, wherein:
Next, “obtaining an unstructured query from a user of the client computing device;” encompasses insignificant extra-solution activity and amounts to mere data gathering (see MPEP 2106.05(g)) and, as stated above, a client computing device is a mere generic computer component.
Next, “in response to obtaining the unstructured query, providing the unstructured query to an operating system (OS) executing on the client computing device;” encompasses insignificant extra-solution activity and amounts to mere data gathering (see MPEP 2106.05(g)) and, as stated above, an operating system and the client computing device are mere generic computer components.
In addition, “in response to providing the unstructured query to the OS, receiving filtered results associated with the unstructured query,” encompasses insignificant extra-solution activity and amounts to mere data gathering (see MPEP 2106.05(g)) and, as stated above, an operating system is a mere generic computer component. Thus, the claim is directed to an abstract idea. Accordingly, 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. Thus, the claim is directed to an abstract idea.
As to step 2B, the claim as a whole does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, claim 13 additional limitation amounts to no more than mere extra solution activity and generic computer components do not amount to significantly more than the judicial exception because the generic computer components are implementing the limitations in a generic manner. Thus, even when viewed as a whole, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea. Mere retrieving and filtering data cannot provide an inventive concept. Thus, claim 13 is not patentable eligible under 35 USC 101.
Under the 2019 PEG, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B. Here, the “obtaining an unstructured query from a user of the client computing device;” and “in response to obtaining the unstructured query, providing the unstructured query to an operating system (OS) executing on the client computing device;” and “in response to providing the unstructured query to the OS, receiving filtered results associated with the unstructured query, wherein:” steps are considered to be extra-solution activity in Step 2A, and thus it is re-evaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The specification does not provide any indication that the limitations are anything other than extra solution activity.
Here, “obtaining an unstructured query from a user of the client computing device;” is merely data gathering. OIP Techs court decision cited in MPEP 2106.05(d)(II) indicate that mere retrieving data is a well-understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here).
Here, “in response to obtaining the unstructured query, providing the unstructured query to an operating system (OS) executing on the client computing device;” is merely data gathering. OIP Techs court decision cited in MPEP 2106.05(d)(II) indicate that mere retrieving data is a well-understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here).
Here, “in response to providing the unstructured query to the OS, receiving filtered results associated with the unstructured query, wherein:” is merely data gathering. OIP Techs court decision cited in MPEP 2106.05(d)(II) indicate that mere retrieving data is a well-understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here).
Accordingly, a conclusion that the “obtaining an unstructured query from a user of the client computing device;” and “in response to obtaining the unstructured query, providing the unstructured query to an operating system (OS) executing on the client computing device;” and “in response to providing the unstructured query to the OS, receiving filtered results associated with the unstructured query, wherein:” steps are well-understood, routine, conventional activity is supported under Berkheimer Option 2. For these reasons, there is no inventive concept in the claim, and thus it is ineligible.
Next, “wherein the filtered results are further provided to: a third LLM to assign, to each result of one or more results of the filtered results, a respective explanation as to why the result is relevant to the unstructured query, the third LLM to assign, to the filtered results, one or more words that summarize the filtered results, at least one artificial intelligence (AI) engine to generate media content that pertains to the filtered results, wherein the media content comprises image content, audio content, and/or video content, or some combination thereof.” of dependent claim 14 is abstract because the claim encompasses mentally a person assigning, to each result of one or more results of the filtered results, a respective explanation as to why the result is relevant to the unstructured query, and determining to the filtered results, one or more words that summarize the filtered results, to generate media content that pertains to the filtered results, wherein the media content comprises image content, audio content, and/or video content, or some combination thereof. Accordingly, 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. Thus, claim 14 is directed to an abstract idea.
Next, “wherein: at least one structured query of the plurality of structured queries includes at least one placeholder value” of dependent claim 15 is abstract because the claim encompasses mentally a person determining at least one structured query of the plurality of structured queries includes at least one placeholder value. Next, “and at least one respective result for at least one other structured query of the plurality of structured queries is assigned to the at least one placeholder value.” of dependent claim 15 is abstract because the claim encompasses mentally a person determining at least one respective result for at least one other structured query of the plurality of structured queries is assigned to the at least one placeholder value. Accordingly, 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. Thus, claim 15 is directed to an abstract idea.
Next, “wherein: the unstructured query is paired with at least one conversation history that is associated the user;” of dependent claim 16 is abstract because the claim encompasses insignificant extra-solution activity and amounts to mere data gathering (see MPEP 2106.05(g)). Next, “the at least one conversation history is provided to: the first LLM along with the unstructured query, and/or the second LLM along with the filtered results;” of dependent claim 16 is abstract because the claim encompasses insignificant extra-solution activity and amounts to mere data gathering (see MPEP 2106.05(g)). Next, “and the at least one conversation history is forgotten by the client computing device in conjunction with providing aggregated results to the second LLM to produce filtered results.” of dependent claim 16 is abstract because the claim encompasses insignificant extra-solution activity and amounts to mere data gathering (see MPEP 2106.05(g)). The claim does not recite additional limitations to integrate the abstract idea into a practical application because the claims do not impose any meaningful limits on practicing the abstract idea. The claim is insignificant extra-solution because 2106.05(d) court decision OIP Techs court states retrieving data is extra solution activity. Thus, claim 16 is not patent eligible under 35 USC 101.
Claims 19-20 are ineligible:
As to step one, claim 19 recites a series of steps and, therefore, is a process which is a statutory category.
As to step 2A-prong one, claim 19 recites a method, comprising, by an application executing on a client computing device:
the filtered results are generated using a first large language model (LLM) that produces a query understanding object, wherein the query understanding object includes a plurality of tasks, and each task of the plurality of tasks includes a respective category and respective one or more properties, each task of the plurality of tasks is (1) used to identify, based on the respective category and the respective one or more properties, respective one or more knowledge sources to produce respective results for the task, and (2) provided to the respective one or more knowledge sources to produce the respective results, and the results are aggregated and filtered by a second LLM to produce filtered results; and
in response to receiving the filtered results, performing at least one action associated with the filtered results.
The limitations, as drafted, are a process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of the generic computer components. The “a client computing device”, “an operating system”, and “an interface” amounts to mere generic computer components. That is other than reciting “a client computing device”, “an operating system”, and “an interface” nothing in the claim element precludes the steps from practically being performed in the mind. Thus, claim 19 is not patentable eligible under 35 U.S.C. 101.
For example, but for an interface, “the filtered results are generated using a first large language model (LLM) that produces a query understanding object, wherein the query understanding object includes a plurality of tasks, and each task of the plurality of tasks includes a respective category and respective one or more properties, each task of the plurality of tasks is (1) used to identify, based on the respective category and the respective one or more properties, respective one or more knowledge sources to produce respective results for the task, and (2) provided to the respective one or more knowledge sources to produce the respective results, and the results are aggregated and filtered by a second LLM to produce filtered results” encompasses mentally a person determining the filtered results are generated using a first large language model (LLM) that produces a query understanding object, wherein the query understanding object includes a plurality of tasks, and each task of the plurality of tasks includes a respective category and respective one or more properties, each task of the plurality of tasks is (1) used to identify, based on the respective category and the respective one or more properties, respective one or more knowledge sources to produce respective results for the task, and (2) provided to the respective one or more knowledge sources to produce the respective results, and the results are aggregated and filtered by a second LLM to produce filtered results.
Next, but for a first large language model (LLM) and second LLM, “in response to receiving the filtered results, performing at least one action associated with the filtered results” encompasses mentally a person in response to receiving the filtered results, performing at least one action associated with the filtered results. The mere nominal recitation of a system does not take the claim limitations out of the mental processes grouping. If claim limitation(s), under its broadest reasonable interpretation, covers performance of the limitation(s) in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
As to Step 2A-prong two, the judicial exception is not integrated into a practical application. Claim 19 recites obtaining an unstructured query from a user of the client computing device;
in response to obtaining the unstructured query, providing the unstructured query to an operating system (OS) executing on the client computing device;
in response to providing the unstructured query to the OS, receiving filtered results associated with the unstructured query, wherein:
Next, “obtaining an unstructured query from a user of the client computing device;” encompasses insignificant extra-solution activity and amounts to mere data gathering (see MPEP 2106.05(g)) and, as stated above, a client computing device is a mere generic computer component.
Next, “in response to obtaining the unstructured query, providing the unstructured query to an operating system (OS) executing on the client computing device;” encompasses insignificant extra-solution activity and amounts to mere data gathering (see MPEP 2106.05(g)) and, as stated above, a client computing device is a mere generic computer component.
Next, “in response to providing the unstructured query to the OS, receiving filtered results associated with the unstructured query, wherein:” encompasses insignificant extra-solution activity and amounts to mere data gathering (see MPEP 2106.05(g)) and, as stated above, a client computing device is a mere generic computer component. Accordingly, 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. Thus, the claim is directed to an abstract idea. Accordingly, 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. Thus, the claim is directed to an abstract idea.
As to step 2B, the claim as a whole does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, claim 19 additional limitation amounts to no more than mere extra solution activity and generic computer components do not amount to significantly more than the judicial exception because the generic computer components are implementing the limitations in a generic manner. Thus, even when viewed as a whole, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea. Mere retrieving and filtering data cannot provide an inventive concept. Thus, claim 19 is not patentable eligible under 35 USC 101.
Under the 2019 PEG, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B. Here, the “obtaining an unstructured query from a user of the client computing device;” and
“in response to obtaining the unstructured query, providing the unstructured query to an operating system (OS) executing on the client computing device;” and
“in response to providing the unstructured query to the OS, receiving filtered results associated with the unstructured query, wherein:” steps are considered to be extra-solution activity in Step 2A, and thus it is re-evaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The specification does not provide any indication that the limitations are anything other than extra solution activity.
Next, “wherein: the respective category of a given task corresponds to album information, artist information, beats per minute (BPM) information, composer information, conductor information, content group information, copyright information, cover art information, disk number information, encoding information, genre information, initial key information, mood information, original artist information, publisher information, release date information, subtitle information, track title information, track number information, and/or year information;” of dependent claim 20 is abstract because the claim encompasses mentally a person determining wherein: the respective category of a given task corresponds to album information, artist information, beats per minute (BPM) information, composer information, conductor information, content group information, copyright information, cover art information, disk number information, encoding information, genre information, initial key information, mood information, original artist information, publisher information, release date information, subtitle information, track title information, track number information, and/or year information. Next, “and the respective one or more properties of the given task function as values for the respective category of the given task.” of dependent claim 20 is abstract because the claim encompasses mentally a person determining the respective one or more properties of the given task function as values for the respective category of the given task. Accordingly, 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. Thus, claim 20 is directed to an abstract idea.
Claims 25-26 are ineligible:
As to step one, claim 25 recites a series of steps and, therefore, is a process which is a statutory category.
As to step 2A-prong one, claim 25 recites a method, comprising:
after requesting a response to an unstructured query, receiving the response;
in response to receiving the response, displaying, via the one or more display generation components, a user interface including the response and an affordance to display an explanation as to why the response is relevant to the unstructured query;
while displaying the user interface including the response and the affordance to display the explanation as to why the response is relevant to the unstructured, detecting, via the one or more input devices, an input corresponding to the affordance to display the explanation as to why the response is relevant to the unstructured query; and
in response to detecting the input corresponding to the affordance to display the explanation as to why the response is relevant to the unstructured query, displaying, via the one or more display generation components, the explanation as to why the response is relevant to the unstructured query. The limitations, as drafted, are a process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of the generic computer components. The “a client computing device” and “display” amounts to mere generic computer components. That is other than reciting “a client computing device” and “display” nothing in the claim element precludes the steps from practically being performed in the mind. Thus, claim 25 is not patentable eligible under 35 U.S.C. 101.
For example, “after requesting a response to an unstructured query, receiving the response” encompasses mentally a person determining after requesting a response to an unstructured query, receiving the response.
Next, but for the display generation components, “in response to receiving the response, displaying, via the one or more display generation components, a user interface including the response and an affordance to display an explanation as to why the response is relevant to the unstructured query;” encompasses mentally a person or person drawing on paper the response and an affordance to display an explanation as to why the response is relevant to the unstructured query.
Next, but for the display generation components, “while displaying the user interface including the response and the affordance to display the explanation as to why the response is relevant to the unstructured, detecting, via the one or more input devices, an input corresponding to the affordance to display the explanation as to why the response is relevant to the unstructured query” encompasses mentally a person or person drawing on paper the explanation as to why the response is relevant to the unstructured query.
Next, but for the display generation components, “in response to detecting the input corresponding to the affordance to display the explanation as to why the response is relevant to the unstructured query, displaying, via the one or more display generation components, the explanation as to why the response is relevant to the unstructured query.” encompasses mentally a person or person drawing on paper the explanation as to why the response is relevant to the unstructured. The mere nominal recitation of a system do not take the claim limitations out of the mental processes grouping. If claim limitation(s), under its broadest reasonable interpretation, covers performance of the limitation(s) in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
As to Step 2A-prong two, the judicial exception is not integrated into a practical application. Claim 25 recites at a client computing device that includes one or more input devices and one or more display generation components:
Next, “at a client computing device that includes one or more input devices and one or more display generation are recited at a high level of generality such tat it amounts to no more than mere generic computer components implementing an abstract idea. Thus, the claim is directed to an abstract idea. Accordingly, 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. Thus, the claim is directed to an abstract idea.
As to step 2B, the claim as a whole does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, claim 25 additional limitation amounts to no more than mere extra solution activity and generic computer components do not amount to significantly more than the judicial exception because the generic computer components are implementing the limitations in a generic manner. Thus, even when viewed as a whole, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea. Mere displaying explanations cannot provide an inventive concept. Thus, claim 25 is not patentable eligible under 35 USC 101.
Next, “wherein the response includes an affordance to perform an operation, the method further comprising: while displaying the affordance to perform the operation, detecting, via the one or more input devices, an input corresponding to the affordance to perform the operation;” of dependent claim 26 is abstract because the claim amounts to mere insignificant instructions which does not amount to an inventive concept (see MPEP 2106.05(f)). Accordingly, 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. Thus, claim 26 is directed to an abstract idea.
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, 4-6, 8, 10, 11, 13, 15, 19, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over LI et al. U.S. Patent (2019/0236130; hereinafter: LI) in view of Gomes Pereira et al. U.S. Patent Publication (2022/0414168; hereinafter: Gomes)
Claim 1
As to claim 1, LI discloses a method, comprising, at a server computing device:
receiving an unstructured query from a client computing device (paragraph[0277], the reference describes receiving a natural language query.);
providing the unstructured query to a first large language model (LLM) to produce a plurality of structured queries (paragraph[0281], the reference describes natural language being processed by a neural network.);
for each structured query of the plurality of structured queries:
identifying, based on at least one aspect of the structured query, respective one or more knowledge sources to produce respective results for the structured query (paragraph[0292], the reference describes identifying the structured query is corresponding to a knowledge base (i.e., knowledge sources, as claimed).),
and providing the structured query to the respective one or more knowledge sources to produce the respective results (paragraph[00282], the reference describes obtaining results from the one or more domain sources.);
aggregating the results to produce aggregated results(paragraph[0303], the reference describes collecting and ranking the results.);
LI does not appear to explicitly disclose
providing the aggregated results to a second LLM to produce filtered results; and
causing the client computing device to display at least a portion of the filtered results.
However, Gomes discloses providing the aggregated results to a second LLM to produce filtered results (Figure 1, paragraph[0038] and paragraph[0040]-paragraph[0041], the reference describes using a search optimization program to filter results. The reference describes an optimizing program using Natural Language and Machine Learning techniques (i.e., a second LLM, as claimed) (e.g., paragraph[0038]) to filter results. The optimization program includes a machine learning model.); and
causing the client computing device to display at least a portion of the filtered results (paragraph[0043], the reference describes presenting the filtered results.). It would have been obvious to one of ordinary skill in the art before the effective filing data 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 LI with the teachings of Gomes to filter search results which would result in the claim invention. The skilled artisan would have been motivated to improve the teachings of LI with the teachings of Gomes to efficiently generate optimized search results (Gomes: paragraph[0003]).
Claim 4
As to claim 4, the combination of Li and Gomes discloses all the elements in claim 1, as noted above, and Li further disclose prior to causing the client computing device to display the at least a portion of the filtered results:
providing the filtered results to at least one artificial intelligence (AI) engine to generate media content that pertains to the filtered results, wherein the media content comprises image content, audio content, and/or video content (paragraph[0263]-paragraph[0264], the reference describes the media a music.).
Claim 5
As to claim 5, the combination of Li and Gomes discloses all the elements in claim 1, as noted above, and Gomes further disclose wherein the one or more knowledge sources include:
at least one web search engine (paragraph[0002], the reference describes using a search engine.);
at least one question and answer (Q&A) knowledge source;
at least one knowledge graph;
at least one approximate nearest-neighbor (ANN) index; at least one other LLM; or some combination thereof.
Claim 6
As to claim 6, the combination of Li and Gomes discloses all the elements in claim 1, as noted above, and Li further disclose wherein:
at least one structured query of the plurality of structured queries includes at least one placeholder value (paragraph[0338]-paragraph[0339], the reference describes determining a set of values in the structured query.); and
at least one respective result for at least one other structured query of the plurality of structured queries is assigned to the at least one placeholder value (paragraph[0338]-paragraph[0339], the reference describes mapping the values to the results.).
Claim 8
As to claim 8, LI discloses a method, comprising, at a server computing device:
receiving an unstructured query from a client computing device (paragraph[0277], the reference describes receiving a natural language query.);
providing the unstructured query to a first large language model (LLM) to produce a query understanding object, wherein the query understanding object includes a plurality of tasks, and each task of the plurality of tasks includes a respective category and respective one or more properties (paragraph[0227]-paragraph[0229], the reference describes the system determining a task from the natural query input and related property node (i.e., a respective category and one or more properties, as claimed).);
for each task of the plurality of tasks:
identifying, based on the respective category and the respective one or more properties, respective one or more knowledge sources to produce respective results for the task (paragraph[0289], the reference describes identifying what song the user is requesting to play and using task flows from the natural language input.), and providing the task to the respective one or more knowledge sources to produce the respective results (paragraph[0292], the reference describes the execution of a task flow using a knowledge base.);
aggregating the results to produce aggregated results (paragraph[0303], the reference describes collecting and ranking the results.);
LI does not appear to explicitly disclose
providing the aggregated results to a second LLM to produce filtered results; and
causing the client computing device to display at least a portion of the filtered results.
However, Gomes discloses providing the aggregated results to a second LLM to produce filtered results (Figure 1, paragraph[0038] and paragraph[0040]-paragraph[0041], the reference describes using a search optimization program to filter results. The reference describes an optimizing program using Natural Language and Machine Learning techniques (i.e., a second LLM, as claimed) (e.g., paragraph[0038]) to filter results. The optimization program includes a machine learning model.); and
causing the client computing device to display at least a portion of the filtered results (paragraph[0043], the reference describes presenting the filtered results.). It would have been obvious to one of ordinary skill in the art before the effective filing data 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 LI with the teachings of Gomes to filter search results which would result in the claim invention. The skilled artisan would have been motivated to improve the teachings of LI with the teachings of Gomes to efficiently generate optimized search results (Gomes: paragraph[0003]).
Claim 10
As to claim 10, the combination of Li and Gomes discloses all the elements in claim 8, as noted above, and Li further disclose further comprising, prior to causing the client computing device to display the at least a portion of the filtered results: providing the filtered results to at least one artificial intelligence (AI) engine to generate media content that pertains to the filtered results, wherein the media content comprises image content, audio content, and/or video content (paragraph[0263]-paragraph[0264], the reference describes the media a music.).
Claim 11
As to claim 11, the combination of Li and Gomes discloses all the elements in claim 8, as noted above, and Li further disclose wherein: the respective category of a given task corresponds to album information, artist information, beats per minute (BPM) information, composer information, conductor information, content group information, copyright information, cover art information, disk number information, encoding information, genre information, initial key information, mood information, original artist information, publisher information, release date information, subtitle information, track title information, track number information, and/or year information (paragraph[0290], the reference describes the task of finding the music title and Artist.); and
the respective one or more properties of the given task function as values for the respective category of the given task (paragraph[0314]-paragraph[0315], the reference describes generating a task.).
Claim 13
As to claim 13, LI discloses a method, comprising, by an application executing on a client computing device:
obtaining an unstructured query from a user of the client computing device (paragraph[0277], the reference describes receiving a natural language query.);
in response to obtaining the unstructured query, providing the unstructured query to an operating system (OS) executing on the client computing device(paragraph[0075], the reference describes using an operating system. In addition, paragraph[0281], the reference describes natural language being processed by a neural network.);
wherein:
a first large language model (LLM) produces a plurality of structured queries based on the unstructured query (paragraph[0281], the reference describes natural language being processed by a neural network.),
each structured query of the plurality of structured queries is provided to respective one or more knowledge sources that are selected based on at least one aspect of the structured query and provide respective results(paragraph[00282], the reference describes obtaining results from the one or more domain sources.),
LI does not appear to explicitly disclose in response to providing the unstructured query to the OS, receiving filtered results associated with the unstructured query, and
the results are aggregated and filtered by a second LLM to generate the filtered results; and
in response to receiving the filtered results, performing at least one action associated with the filtered results.
However, Gomes discloses in response to providing the unstructured query to the OS, receiving filtered results associated with the unstructured query(Figure 1, paragraph[0038] and paragraph[0040]-paragraph[0041], the reference describes using a search optimization program to filter results. The reference describes an optimizing program using Natural Language and Machine Learning techniques (i.e., a second LLM, as claimed) (e.g., paragraph[0038]), and
the results are aggregated and filtered by a second LLM to generate the filtered results(Figure 1, paragraph[0038] and paragraph[0040]-paragraph[0041], the reference describes using a search optimization program to filter results. The reference describes an optimizing program using Natural Language and Machine Learning techniques (i.e., a second LLM, as claimed) (e.g., paragraph[0038]); and
in response to receiving the filtered results, performing at least one action associated with the filtered results(paragraph[0043], the reference describes presenting the filtered results.). It would have been obvious to one of ordinary skill in the art before the effective filing data 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 LI with the teachings of Gomes to filter search results which would result in the claim invention. The skilled artisan would have been motivated to improve the teachings of LI with the teachings of Gomes to efficiently generate optimized search results (Gomes: paragraph[0003]).
Claim 15
As to claim 15, the combination of Li and Gomes discloses all the elements in claim 13, as noted above, and Li further disclose wherein:
at least one structured query of the plurality of structured queries includes at least one placeholder value(paragraph[0338]-paragraph[0339], the reference describes determining a set of values in the structured query.); and
at least one respective result for at least one other structured query of the plurality of structured queries is assigned to the at least one placeholder value (paragraph[0338]-paragraph[0339], the reference describes mapping the values to the results.).
Claim 19
As to claim 19, LI discloses a method, comprising, by an application executing on a client computing device:
obtaining an unstructured query from a user of the client computing device(paragraph[0277], the reference describes receiving a natural language query.);
in response to obtaining the unstructured query, providing the unstructured query to an operating system (OS) executing on the client computing device(paragraph[0075], the reference describes using an operating system. In addition, paragraph[0281], the reference describes natural language being processed by a neural network.);
, wherein:
the filtered results are generated using a first large language model (LLM) that produces a query understanding object, wherein the query understanding object includes a plurality of tasks, and each task of the plurality of tasks includes a respective category and respective one or more properties(paragraph[0227]-paragraph[0229], the reference describes the system determining a task from the natural query input and related property node (i.e., a respective category and one or more properties, as claimed).), each task of the plurality of tasks is (1) used to identify, based on the respective category and the respective one or more properties, respective one or more knowledge sources to produce respective results for the task(paragraph[0289], the reference describes identifying what song the user is requesting to play and using task flows from the natural language input.), and (2) provided to the respective one or more knowledge sources to produce the respective results(paragraph[0292], the reference describes the execution of a task flow using a knowledge base.),
LI does not appear to explicitly disclose in response to providing the unstructured query to the OS, receiving filtered results associated with the unstructured query
and the results are aggregated and filtered by a second LLM to produce filtered results; and
in response to receiving the filtered results, performing at least one action associated with the filtered results.
However, Gomes discloses in response to providing the unstructured query to the OS, receiving filtered results associated with the unstructured query(Figure 1, paragraph[0038] and paragraph[0040]-paragraph[0041], the reference describes using a search optimization program to filter results. The reference describes an optimizing program using Natural Language and Machine Learning techniques (i.e., a second LLM, as claimed) (e.g., paragraph[0038]) to filter results. The optimization program includes a machine learning model.)
and the results are aggregated and filtered by a second LLM to produce filtered results(Figure 1, paragraph[0038] and paragraph[0040]-paragraph[0041], the reference describes using a search optimization program to filter results. The reference describes an optimizing program using Natural Language and Machine Learning techniques (i.e., a second LLM, as claimed) (e.g., paragraph[0038]) to filter results. The optimization program includes a machine learning model.); and
in response to receiving the filtered results, performing at least one action associated with the filtered results(paragraph[0043], the reference describes presenting the filtered results.). It would have been obvious to one of ordinary skill in the art before the effective filing data 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 LI with the teachings of Gomes to filter search results which would result in the claim invention. The skilled artisan would have been motivated to improve the teachings of LI with the teachings of Gomes to efficiently generate optimized search results (Gomes: paragraph[0003]).
Claim 20
As to claim 20, the combination of Li and Gomes discloses all the elements in claim 19, as noted above, and Li further disclose wherein:
the respective category of a given task corresponds to album information, artist information, beats per minute (BPM) information, composer information, conductor information, content group information, copyright information, cover art information, disk number information, encoding information, genre information, initial key information, mood information, original artist information, publisher information, release date information, subtitle information, track title information, track number information, and/or year information(paragraph[0290], the reference describes the task of finding the music title and Artist.); and
the respective one or more properties of the given task function as values for the respective category of the given task(paragraph[0314]-paragraph[0315], the reference describes generating a task.).
Claims 2, 3, 9, and 14 are rejected under 35 U.S.C. 103 as being unpatentable over LI et al. U.S. Patent (2019/0236130; hereinafter: LI) in view of Gomes Pereira et al. U.S. Patent Publication (2022/0414168; hereinafter: Gomes) and further in view of Chao et al. U.S. Patent Publication (2024/0403373; hereinafter: Chao)
Claim 2
As to claim 2, the combination of Li and Gomes discloses all the elements in claim 1, as noted above, but do not appear to explicitly disclose and further disclose prior to causing the client computing device to display the at least a portion of the filtered results:
providing the filtered results to a third LLM to assign, to each result of one or more results of the filtered results, a respective explanation as to why the result is relevant to the unstructured query.
However, Chao discloses further disclose prior to causing the client computing device to display the at least a portion of the filtered results:
providing the filtered results to a third LLM to assign, to each result of one or more results of the filtered results, a respective explanation as to why the result is relevant to the unstructured query (paragraph[0041], the reference describes using a LLM model to generate an explanation of the search result relevance.). It would have been obvious to one of ordinary skill in the art before the effective filing data 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 LI with the teachings of Gomes and Chao to provide explanations of the relevant search results which would result in the claim invention. The skilled artisan would have been motivated to improve the teachings of LI with the teachings of Gomes and Chao to efficiently search and rank data sets within a data sharing platform (Chao: paragraph[0002]).
Claim 3
As to claim 3, the combination of Li and Gomes discloses all the elements in claim 1, as noted above, but do not appear to explicitly disclose further comprising, prior to causing the client computing device to display the at least a portion of the filtered results: providing the filtered results to a third LLM to assign, to the filtered results, one or more words that summarize the filtered results.
However, Chao discloses further comprising, prior to causing the client computing device to display the at least a portion of the filtered results: providing the filtered results to a third LLM to assign, to the filtered results, one or more words that summarize the filtered results (paragraph[0041], the reference describes using a LLM model to generate an explanation of the search result relevance.). It would have been obvious to one of ordinary skill in the art before the effective filing data 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 LI with the teachings of Gomes and Chao to provide explanations of the relevant search results which would result in the claim invention. The skilled artisan would have been motivated to improve the teachings of LI with the teachings of Gomes and Chao to efficiently search and rank data sets within a data sharing platform (Chao: paragraph[0002]).
Claim 9
As to claim, the combination of Li and Gomes discloses all the elements in claim 8, as noted above, but do not appear to explicitly disclose further comprising, prior to causing the client computing device to display the at least a portion of the filtered results:
providing the filtered results to a third LLM to assign, to each result of one or more results of the filtered results, a respective explanation as to why the result is relevant to the unstructured query, providing the filtered results to the third LLM to assign, to the filtered results, one or more words that summarize the filtered results, or some combination thereof.
However, Chao discloses further comprising, prior to causing the client computing device to display the at least a portion of the filtered results:
providing the filtered results to a third LLM to assign, to each result of one or more results of the filtered results, a respective explanation as to why the result is relevant to the unstructured query, providing the filtered results to the third LLM to assign, to the filtered results, one or more words that summarize the filtered results, or some combination thereof(paragraph[0041], the reference describes using a LLM model to generate an explanation of the search result relevance.). It would have been obvious to one of ordinary skill in the art before the effective filing data 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 LI with the teachings of Gomes and Chao to provide explanations of the relevant search results which would result in the claim invention. The skilled artisan would have been motivated to improve the teachings of LI with the teachings of Gomes and Chao to efficiently search and rank data sets within a data sharing platform (Chao: paragraph[0002]).
Claim 14
As to claim 14, the combination of Li and Gomes discloses all the elements in claim 13, as noted above, and Li further disclose wherein the filtered results are further provided to:
at least one artificial intelligence (AI) engine to generate media content that pertains to the filtered results, wherein the media content comprises image content, audio content, and/or video content, or some combination thereof(paragraph[0263]-paragraph[0264], the reference describes the media a music.).
The combination of Li and Gomes do not appear to explicitly disclose
a third LLM to assign, to each result of one or more results of the filtered results, a respective explanation as to why the result is relevant to the unstructured query,
the third LLM to assign, to the filtered results, one or more words that summarize the filtered results,
However, Chao discloses a third LLM to assign, to each result of one or more results of the filtered results, a respective explanation as to why the result is relevant to the unstructured query (paragraph[0041], the reference describes using a LLM model to generate an explanation of the search result relevance.),
the third LLM to assign, to the filtered results, one or more words that summarize the filtered results(paragraph[0041], the reference describes using a LLM model to generate an explanation of the search result relevance.). It would have been obvious to one of ordinary skill in the art before the effective filing data 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 LI with the teachings of Gomes and Chao to provide explanations of the relevant search results which would result in the claim invention. The skilled artisan would have been motivated to improve the teachings of LI with the teachings of Gomes and Chao to efficiently search and rank data sets within a data sharing platform (Chao: paragraph[0002]).
Claims 7, 12, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over LI et al. U.S. Patent (2019/0236130; hereinafter: LI) in view of Gomes Pereira et al. U.S. Patent Publication (2022/0414168; hereinafter: Gomes) and further in view of Mulligan et al. U.S. Patent Publication (2024/0267344; hereinafter: Mulligan)
Claim 7
As to claim 7, the combination of Li and Gomes discloses all the elements in claim 1, as noted above, but do not appear to explicitly disclose wherein:
the unstructured query is paired with at least one conversation history that is associated and received from the client computing device;
the at least one conversation history is provided to: the first LLM along with the unstructured query, and/or the second LLM along with the filtered results; and
the at least one conversation history is forgotten by the server computing device in conjunction with providing the aggregated results to the second LLM to produce filtered results.
However, Mulligan discloses wherein: the unstructured query is paired with at least one conversation history that is associated and received from the client computing device (paragraph[0210], the reference describes using conversation history received from the user’s device.);
the at least one conversation history is provided to:
the first LLM along with the unstructured query, and/or the second LLM along with the filtered results (paragraph[0210], the reference describes the conversation history being used by the LLM model.); and
the at least one conversation history is forgotten by the server computing device in conjunction with providing the aggregated results to the second LLM to produce filtered results (paragraph[0271], the reference describes the conversation history being removed from the system (i.e., forgotten, as claimed).). It would have been obvious to one of ordinary skill in the art before the effective filing data 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 LI with the teachings of Gomes and Mulligan to input conversation history into a model which would result in the claim invention. The skilled artisan would have been motivated to improve the teachings of LI with the teachings of Gomes and Mulligan to efficiently provide improved user intent detection during conversations with chatbots of an interactive platform (Mulligan: paragraph[0027]).
Claim 12
As to claim 12, the combination of Li and Gomes discloses all the elements in claim 8, as noted above, but do not appear to explicitly disclose wherein:
the unstructured query is paired with at least one conversation history that is associated and received from the client computing device;
the at least one conversation history is provided to: the first LLM along with the unstructured query, and/or the second LLM along with the filtered results; and
the at least one conversation history is forgotten by the server computing device in conjunction with providing the aggregated results to the second LLM to produce filtered results.
However, Mulligan discloses wherein:
the unstructured query is paired with at least one conversation history that is associated and received from the client computing device(paragraph[0210], the reference describes using conversation history received from the user’s device.);
the at least one conversation history is provided to:
the first LLM along with the unstructured query, and/or the second LLM along with the filtered results (paragraph[0210], the reference describes the conversation history being used by the LLM model.); and
the at least one conversation history is forgotten by the server computing device in conjunction with providing the aggregated results to the second LLM to produce filtered results(paragraph[0271], the reference describes the conversation history being removed from the system (i.e., forgotten, as claimed).). It would have been obvious to one of ordinary skill in the art before the effective filing data 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 LI with the teachings of Gomes and Mulligan to input conversation history into a model which would result in the claim invention. The skilled artisan would have been motivated to improve the teachings of LI with the teachings of Gomes and Mulligan to efficiently provide improved user intent detection during conversations with chatbots of an interactive platform (Mulligan: paragraph[0027]).
Claim 16
As to claim 16, the combination of Li and Gomes discloses all the elements in claim 13, as noted above, but do not appear to explicitly disclose wherein:
the unstructured query is paired with at least one conversation history that is associated the user;
the at least one conversation history is provided to:
the first LLM along with the unstructured query, and/or
the second LLM along with the filtered results; and
the at least one conversation history is forgotten by the client computing device in conjunction with providing aggregated results to the second LLM to produce filtered results.
However, Mulligan discloses wherein:
the unstructured query is paired with at least one conversation history that is associated the user(paragraph[0210], the reference describes using conversation history received from the user’s device.);
the at least one conversation history is provided to:
the first LLM along with the unstructured query, and/or
the second LLM along with the filtered results(paragraph[0210], the reference describes the conversation history being used by the LLM model.); and
the at least one conversation history is forgotten by the client computing device in conjunction with providing aggregated results to the second LLM to produce filtered results (paragraph[0271], the reference describes the conversation history being removed from the system (i.e., forgotten, as claimed).). It would have been obvious to one of ordinary skill in the art before the effective filing data 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 LI with the teachings of Gomes and Mulligan to input conversation history into a model which would result in the claim invention. The skilled artisan would have been motivated to improve the teachings of LI with the teachings of Gomes and Mulligan to efficiently provide improved user intent detection during conversations with chatbots of an interactive platform (Mulligan: paragraph[0027]).
Claims 25-26 are rejected under 35 U.S.C. 103 as being unpatentable Chao et al. U.S. Patent Publication (2024/0403373; hereinafter: Chao) in view of Zhang et al. U.S. Patent Publication (2025/0094774; hereinafter: Zhang)
Claim 25
As to claim 25, Chao discloses a method, comprising:
at a client computing device that includes one or more input devices and one or more display generation components (paragraph[0145], the reference describes using a computer device for display results.)
after requesting a response to an unstructured query, receiving the response;
in response to receiving the response, displaying, via the one or more display generation components, a user interface including the response and an affordance to display an explanation as to why the response is relevant to the unstructured query(paragraph[0041], the reference describes using a LLM model to generate an explanation of the search result relevance.);
Chao do not appear to explicitly disclose
while displaying the user interface including the response and the affordance to display the explanation as to why the response is relevant to the unstructured, detecting, via the one or more input devices, an input corresponding to the affordance to display the explanation as to why the response is relevant to the unstructured query; and
in response to detecting the input corresponding to the affordance to display the explanation as to why the response is relevant to the unstructured query, displaying, via the one or more display generation components, the explanation as to why the response is relevant to the unstructured query.
However, Zhang discloses while displaying the user interface including the response and the affordance to display the explanation as to why the response is relevant to the unstructured, detecting, via the one or more input devices, an input corresponding to the affordance to display the explanation as to why the response is relevant to the unstructured query (Figure 10, paragraph[0063], the reference describes explaining why songs where recommended based on the query.); and
in response to detecting the input corresponding to the affordance to display the explanation as to why the response is relevant to the unstructured query, displaying, via the one or more display generation components, the explanation as to why the response is relevant to the unstructured query(Figure 10, paragraph[0063], the reference describes explaining why songs where recommended based on the query.). It would have been obvious to one of ordinary skill in the art before the effective filing data 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 Chao with the teachings of Zhang to provide explanations of multimedia data results which would result in the claim invention. The skilled artisan would have been motivated to improve the teachings of Chao with the teachings of Zhang to efficiently aid users for the comprehension data (Zhang: paragraph[0016]).
Claim 26
As to claim 26, the combination of Chao and Zhang discloses all the elements in claim 25, as noted above, and Chao further disclose wherein the response includes an affordance to perform an operation, the method further comprising:
while displaying the affordance to perform the operation, detecting, via the one or more input devices, an input corresponding to the affordance to perform the operation (paragraph[0022], the reference describes the user selecting a track on the user interface.); and
in response to detecting the input corresponding to the affordance to perform the operation, performing the operation(paragraph[0022], the reference describes the user selecting a track on the user interface.).
Final Rejection
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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, Neveen Abel-Jalil can be reached on (571) 270-0474. 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 29, 2026
/DAWAUNE A CONYERS/Primary Examiner, Art Unit 2152 February 24, 2024
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