DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This action is in response to the communication filed on December 30, 2024.
Claims 1-20 are pending in this action.
Claim Objections
Claims 19 is objected to under 37 CFR 1.75 as being a substantial duplicate of claim 18. When two claims in an application are duplicates or else are so close in content that they both cover the same thing, despite a slight difference in wording, it is proper after allowing one claim to object to the other as being a substantial duplicate of the allowed claim. See MPEP § 608.01(m).
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 3-10, 13, 15-17 and 20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Dong et al. (US 2025/0231942).
As per claim 1, Dong discloses, a method comprising:
generating, based at least on a primary agent of a multi-agent system using one or more language models to process input data representing a request for information, text data representing instructions associated with a plan for obtaining the information from a plurality of specialized agents (Paragraph 0015);
sending, based at least on the plan, one or more first portions of the text data to one or more first specialized agents of the plurality of specialized agents to obtain one or more first portions of the information (Paragraphs 0081-0084);
sending, based at least on the plan, one or more second portions of the text data and the one or more first portions of the information to one or more second specialized agents of the plurality of specialized agents to obtain one or more second portions of the information (Paragraphs 0081-0084);
generating, based at least on the primary agent using the one or more language models to process at least the one or more first portions of the information and the one or more second portions of the information, output data representative of a response to the request that includes the information (Paragraphs 0086-0090); and
sending, to a computing device, the output data representative of the response (Paragraphs 0086-0090).
As per claim 3, Dong discloses, wherein the one or more first specialized agents include at least a database agent, the database agent configured to perform operations comprising:
generating, based at least on using one or more second language models to process the one or more first portions of the text data, one or more structured query language (SQL) statements for one or more relational databases to execute (Paragraph 0084);
obtaining results associated with the one or more relational databases executing the one or more SQL statements (Paragraph 0087); and
generating, based at least on using the one or more second language models to process at least a portion of the results, one or more strings of text representative of a description of the results; wherein the one or more first portions of the information include the one or more strings of text (Paragraph 0088).
As per claim 4, Dong discloses, wherein, based at least on receiving the one or more first portions of the text data from the primary agent, the one or more first specialized agents are configured to perform operations comprising:
generating, based at least on using one or more second language models to process the one or more first portions of the text data, text representative of code for making one or more application programming interface (API) calls (Paragraph 0078);
obtaining, based at least on using the code to execute the one or more API calls, the one or more first portions of the information (Paragraph 0078); and
sending the one or more first portions of the information to the primary agent (Paragraphs 0079-0080).
As per claim 5, Dong discloses, further comprising: receiving at the primary agent, a configuration file associated with the multi-agent system, the configuration file indicating at least:
one or more respective capabilities of each one of the plurality of specialized agents;
one or more respective sample queries that each one of the plurality of specialized agents is configured to solve; and
respective network endpoints for each one of the plurality of specialized agents (Paragraphs 0082-0084); and
updating at least the one or more language models associated with the primary agent using the configuration file, wherein the generating of the text data representing the instructions using the one or more language models is based at least on the updating (Paragraph 0083).
As per claim 6, Dong discloses, wherein at least one of the one or more first specialized agents or the one or more second specialized agents are configured to cause one or more autonomous or semi-autonomous machines to perform one or more control operations (Fig. 5A).
As per claim 7, Dong discloses, wherein the response is a multimodal response including a combination of two or more of: text data; audio data; video data; or image data (Paragraphs 0090 and 0110).
As per claim 8, Dong discloses, a system comprising:
one or more processors (Paragraph 0110) to:
obtain, from a computing device, input data representing a query (Paragraph 0015);
send at least one or more portions of the input data to one or more agents of a plurality of agents of a multi-agent system, the one or more agents including one or more first language models and one or more tools for determining information associated with responding to the query (Paragraphs 0081-0084);
receive, based at least on the sending, at least one or more portions of the information from the one or more agents (Paragraphs 0081-0084);
generate, based at least on using one or more second language models to process at least the one or more portions of the information, output data representative of a response to the query (Paragraphs 0086-0090); and
send, to the computing device, the output data representative of the response (Paragraphs 0086-0090).
As per claim 9, Dong discloses, wherein the one or more agents include at least one or more first agents and one or more second agents, the one or more first agents including one or more first tools and the one or more second agents including one or more second tools that are different from the one or more first tools (Paragraphs 0082-0084).
As per claim 10, Dong discloses, wherein the reception of the one or more portions of the information comprises: receiving one or more first portions of the information from the one or more first agents; and receiving one or more second portions of the information from the one or more second agents (Paragraphs 0081-0084).
As per claim 13, Dong discloses, the one or more processors further to: generate, based at least on using the one or more second language models to process the input data, one or more text strings representative of one or more instructions for sending to the one or more agents to obtain the information associated with responding to the query, wherein the sending of the one or more portions of the input data to the one or more agents comprises sending the one or more text strings to the one or more agents (Paragraphs 0081-0084).
As per claims 15 and 20, Dong discloses, wherein the system is comprised in at least one of: a control system for an autonomous or semi-autonomous machine; a perception system for an autonomous or semi-autonomous machine; a system for performing simulation operations; a system for performing digital twin operations; a system for performing light transport simulation; a system for performing collaborative content creation for 3D assets; a system for performing deep learning operations; a system for performing remote operations; a system for performing real-time streaming; a system for generating or presenting one or more of augmented reality content, virtual reality content, or mixed reality content; a system implemented using an edge device; a system implemented using a robot; a system for performing conversational Al operations; a system implementing one or more multi-model language models; a system implementing one or more large language models (LLMs) (Paragraphs 0081-0082); a system implementing one or more small language models (SLMs); a system implementing one or more vision language models (VLMs); a system for generating synthetic data; a system for generating synthetic data using AI; a system incorporating one or more virtual machines (VMs); a system implemented at least partially in a data center; or a system implemented at least partially using cloud computing resources.
As per claim 16, Dong discloses, One or more processors comprising:
processing circuitry (Paragraph 0110) to:
generate, based at least on using one or more first language models to process first text data representing a first query, second text data representing one or more second queries (Paragraphs 0081-0084);
receive, from one or more agents of a multi-agent system, one or more text strings representing one or more responses to the one or more second queries, the one or more text strings generated by the one or more agents based at least on using one or more second language models to process information determined using one or more tools of the one or more agents (Paragraphs 0081-0084);
generate, based at least on using the one or more first language models to process at least the one or more text strings, output data representative of a response to the first query (Paragraphs 0086-0090); and
cause to present content based on the output data (Paragraphs 0086-0090).
As per claim 17, Dong discloses, wherein the one or more agents include at least a first agent and a second agent, the first agent including one or more first tools and the second agent including one or more second tools that are different from the one or more first tools (Paragraphs 0081-0084).
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, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 2 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Dong et al. (US 2025/0231942) as applied to claims 1 and 8 above, and further in view of Torek et al. (US 2026/0004786).
As per claim 2, Dong discloses, further comprising: sending, at a first time and based at least on the plan, the one or more first portions of the text data to one or more third specialized agents of the plurality of specialized agents (Fig. 5A, element 440);
Dong does not explicitly disclose, but Torek discloses, receiving, from the one or more third specialized agents responsive to the sending of the one or more first portions of the text data, an indication that the one or more third specialized agents are incapable of providing the one or more first portions of the information; and determining, by the primary agent and based at least on the indication, to send the one or more first portions of the text data to the one or more first specialized agents, wherein the one or more first portions of the text data are sent to the one or more first specialized agents at a second time after the first time (Paragraphs 0071-0073).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Dong by including determining incapable of providing the one or more first portions of the information as taught by Torek for the advantage of ensuring it is clear, accurate, and directly answer the question posed (Paragraph 0069).
Claim(s) 11-12, 18-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Dong et al. (US 2025/0231942) as applied to claims 1 and 8 above, and further in view of Li et al. (US 2025/01312206).
As per claims 11 and 18-19, Dong does not explicitly disclose, but Li discloses, wherein the plurality of agents include at least: one or more database agents; one or more video storage toolkit agents; one or more analytics agents; one or more documentation agents; one or more machine control agents; and one or more vision language model agents (Paragraphs 0056).
As per claim 12, Dong does not explicitly disclose, but Li discloses, wherein the one or more agents include at least a control agent and the one or more tools of the control agent include at least a tool to cause one or more machines to perform one or more operations based at least on receiving the one or more portions of the input data (Paragraphs 0056-0057).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Dong by including different agents and a control agent as taught by Li so as to using a large language model (LLM) based digital assistant to generate one or more user-specific suggestions or actions based on the personal activity data and the user query (Abstract).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Kanuga et al. (US 2026/0119489) discloses, parallel execution planner for agentic digital assistant.
Adams et al. (US 2026/0079988) discloses, systems and methods for isolated AI agents and files.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Abul K. Azad whose telephone number is (571) 272-7599. If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Bhavesh Mehta, can be reached at (571) 272-7453.
Any response to this action should be mailed to:
Commissioner for Patents
P.O. Box 1450
Alexandria, VA 22313-1450
Or faxed to: (571) 273-8300.
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July 22, 2026
/ABUL K AZAD/Primary Examiner, Art Unit 2656
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