DETAILED ACTION
Claims 1-20 are pending. Claims 1-20 are considered in this Office action.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 11/14/2024 has been acknowledged.
The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. The initialed and dated copy of Applicant’s IDS form 1449 is attached to the instant Office action.
Claim Objections
Claims 1-20 are objected to because of the following informalities:
Claims 1, 8, and 15 recite the limitations of a “5GMS network device”. This is an acronym which needs to be clarified.
Appropriate correction is required.
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.
Alice – Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1, 8, and 15 recite the limitations for selecting a partially trained AI model in the 5GMS network (Receiving and Analyzed Information, an Observation and Evaluation; a Fundamental Economic Process, a Certain Method of Organizing Human Activity), broadcasting eligibility criteria for user devices to participate in federated learning in the 5GMS network (Analyzed Information, a Evaluation; a Fundamental Economic Process, a Certain Method of Organizing Human Activity), broadcasting failure reporting criteria for the user devices (Analyzed Information, a Evaluation; a Fundamental Economic Process, a Certain Method of Organizing Human Activity), and transmitting the partially trained AI model (Transmitting the Analyzed Information, a Judgment; a Fundamental Economic Process, a Certain Method of Organizing Human Activity), which under their broadest reasonable interpretation, covers performance of the limitation in the mind for the purposes of analyzing results and transmitting information, which is a Fundamental Economic Process, but for the recitation of generic computer components. That is, other than reciting a processor, triggering a federated learning session between a user device and the 5GMS network device, apparatus, medium, and memory, nothing in the claim elements preclude the step from practically being performed or read into the mind for the purposes of a Fundamental Economic Process, a Certain Method of Organizing Human Activity. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas, an observation, evaluation, and judgment. Further, as described above, the claims recite limitations for a Fundamental Economic Process, a “Certain Method of Organizing Human Activity”. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites the above stated additional elements to perform the abstract limitations as above. The processor, triggering a federated learning session between a user device and the 5GMS network device, apparatus, medium, and memory, are recited at a high-level of generality (i.e., as a generic software/module performing a generic computer function of storing, retrieving, sending, and processing data) such that they amount to no more than mere instructions to apply the exception using generic computer components. Even if taken as an additional element, the receiving and transmitting steps above are at best insignificant extra-solution activity as these are receiving, storing, and transmitting data as per the MPEP 2106.05(d). Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception, when considered both individually and as an ordered combination. As discussed above with respect to integration of the abstract idea into a practical application, the additional element being used to perform the abstract limitations stated above amount to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. The claim is not patent eligible. Applicant’s Specification states:
“[0027] In Fig. 1, the terminals 101, 102, 103 and 104 may be illustrated as servers, personal computers and smart phones but the principles of the present disclosure are not so limited. Embodiments of the present disclosure find application with laptop computers, tablet computers, media players and/or dedicated video conferencing equipment.”
Which shows that these steps can be performed on any generic computing device with a processor and memory, which can be used to perform the abstract limitations, such as a laptop, phone, desktop, etc., and from this interpretation, one would reasonably deduce the aforementioned steps are all functions that can be done on generic components, and thus application of an abstract idea on a generic computer, as per the Alice decision and not requiring further analysis under Berkheimer, but for edification the Applicant’s specification has been used as above satisfying any such requirement. This is “Applying It” by utilizing current technologies. For the receiving and transmitting steps that were considered extra-solution activity in Step 2A above, if they were to be considered additional elements, they have been re-evaluated in Step 2B and determined to be well-understood, routine, conventional, activity in the field. The background does not provide any indication that the additional elements, such as the apparatus, medium, processors, etc., nor the receiving and transmitting steps as above, are anything other than a generic, and the MPEP Section 2106.05(d) indicates that mere collection or receipt, storing, or transmission of data is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here). For these reasons, there is no inventive concept. The claim is not patent eligible.
Claims 2-7, 9-14, and 16-20 contain the identified abstract ideas, further narrowing them, with no new additional elements to be considered as part of a practical application or under prong 2 of the Alice analysis of the MPEP, thus not integrated into a practical application, nor are they significantly more for the same reasons and rationale as above.
After considering all claim elements, both individually and in combination, Examiner has determined that the claims are directed to the above abstract ideas and do not amount to significantly more. Therefore, the claims and dependent claims are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter. See Alice Corporation Pty. Ltd. v. CLS Bank International, No. 13–298.
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Amar (U.S. Publication No. 2024/024,9179) in view of Yip (U.S. Publication No. 2025/028,0305).
Regarding Claims 1, 8, and 15, Amar, a system and method for training federated learning models, teaches a method for distributed artificial intelligence/machine learning (AI/ML) federated learning in a 5GMS network, the method being executed by a processor ([0005-7] a network using a processor for federated learning), and the method comprising:
triggering, by a network device, a federated learning session between a user device and the 5GMS network device ([0024] a federated learning session between client/user devices to collaborate are triggered so that users can being use);
selecting a partially trained AI model in the network ([0033] partially trained models are selected and used to update the model)
broadcasting, by the network device to the user device, eligibility criteria for user devices to participate in federated learning in the network ([0027-28] parameters and criteria are used to see if the [0024] clients can participate in the federated learning model session)
broadcasting, by the network device to the user device, failure reporting criteria for the user devices ([0035] and [0044] reported failure of training of the models is sent through and to the server) and
transmitting, by the network device and to the user device, the partially trained AI model ([0045] and [0047] partially trained model is updated and sent to the devices and server)
Although Amar teaches use of partially trained models over a network as above, it does not explicitly state a 5Gms network.
Yip, a method and apparatus for presenting AI and ML media services in wireless communication systems, teaches determination and evaluation of AI models in 5G media services as in [0047] and [0088] which use partially trained models in the process as in [0188].
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the network and use of federated learning for client devices of a network of Amar with the partial models over a 5gms network of Yip as they are both analogous art along with the claimed invention which teach solutions to training models over a network, and the combination would lead to an improved system which would increase frequency efficiency of communication over the network as taught in [0007] of Yip.
Examiner notes Amar teaches an apparatus, memory, processor, and computer readable medium ([0057-58] system with processor, memory, and medium)
Regarding Claims 2, 9, and 16, Amar teaches a partially trained model as in Claim 1 above, but does not teach evaluation of that model.
Yip teaches transmitting a request for evaluating the partially trained AI mode ([0047] and [0042] where there is a request for a inference/evaluation of the partially trained AI model) and
receiving one of: evaluation results in response to successfully evaluating the partially trained AI model or failure results in response to an successfully evaluation of the partially trained AI model by the user device ([0080] a success based on the parameter change and evaluation for each model is determined)
and Yip teaches determination and evaluation of AI models in 5G media services as in [0047] and [0088] which use partially trained models in the process as in [0188].
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the network and use of federated learning for client devices of a network of Amar with the partial models over a 5gms network of Yip as they are both analogous art along with the claimed invention which teach solutions to training models over a network, and the combination would lead to an improved system which would increase frequency efficiency of communication over the network as taught in [0007] of Yip.
Regarding Claims 3, 10, and 17, Amar teaches wherein the method further comprises:
Updating the eligibility criteria for the user devices to participate in federated learning in the network ([0033] parameters and criteria are updated for training in the federated learning).
Regarding Claims 4, 11, and 18, Amar teaches a partially trained model as in Claim 1 above as well as teach updating the model and criteria as in Claim 3 above, but does not teach evaluation of that model.
Yip teaches transmitting a request for evaluating the partially trained AI mode ([0047] and [0042] where there is a request for a inference/evaluation of the partially trained AI model) and
teaches determination and evaluation of AI models in 5G media services as in [0047] and [0088] which use partially trained models in the process as in [0188].
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the network and use of federated learning for client devices of a network of Amar with the partial models over a 5gms network of Yip as they are both analogous art along with the claimed invention which teach solutions to training models over a network, and the combination would lead to an improved system which would increase frequency efficiency of communication over the network as taught in [0007] of Yip.
Regarding Claims 5, 12, and 19, Amar teaches wherein the method further comprises:
transmitting, by the 5GMS network device and to the user device, a request for training the partially trained AI model Yip teaches transmitting a request for evaluating the partially trained AI mode ([0047] and [0042] where there is a request for a inference/evaluation of the partially trained AI model) and
receiving, by the 5GMS network device and from the user device, one of:
an updated AI model in response to a training by the user device of the partially trained AI model ([0033] parameters and criteria are updated for training in the federated learning), evaluation results in response to successfully evaluating the partially trained AI model; or failure results in response to an unsuccessful training of the partially trained AI model by the user device ([0044] and [0052] failure reports for unsuccessful training are sent)
Regarding Claims 6, 13, and 20, Amar teaches updating the partially trained AI model by the network device by aggregating results from one or more user device ([0047] partially trained AI model is aggregating from the model)
Regarding Claims 7 and 14, Amar teaches The method of claim 6, further comprising:
transmitting, by the 5GMS network device to the user device, the updated partially trained AI model ([0045] and [0047] partially trained model is updated and sent to the devices and server)
Conclusion
The prior art made of record is considered pertinent to applicant's disclosure.
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EXPLAINABLE TRANSDUCER TRANSFORMERS
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOSEPH M WAESCO whose telephone number is (571)272-9913. The examiner can normally be reached on 8 AM - 5 PM M-F.
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/JOSEPH M WAESCO/Primary Examiner, Art Unit 3625B 9/15/2026
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