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 .
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) 9 – 10 and 14 -15 are rejected under 35 U.S.C. 103 as being unpatentable over Chen, publication number: US 2025/0254207 in view of Lally, patent number: US 12 518 038.
As per claim 9, Chen teaches a system for controlling access to artificial intelligence models, the system
comprising:
one or more processors; and
a memory storing instructions, that when executed by the one or more processors, cause the system to perform operations comprising:
generating a request to retrieve an AI model for local use on the system (request, [0031]);
receiving an identification of a distribution server, storing an encrypted version of
the AI model, that is located closest to the system as compared to other distribution
servers storing the encrypted version of the AI model (selection based on latency, [0094][0098-0099][0119-0120]);
transmitting the generated request to the identified distribution server (orchestration, [0096]);
receiving, from the identified distribution server, the encrypted version of the AI
model (receiving encrypted model, [0055]);
Chen does not teach transmitting a license request to a licensing server for a license to use the AI model on the system; and
receiving, from the licensing server, a license package including the license and a decryption key for the model.
In analogous art, Lally teaches transmitting a license request to a licensing server for a license to use the AI model on the system; and
receiving, from the licensing server, a license package including the license and a decryption key for the model (accessing license terms and encryption keys, col. 15, line 62- col. 16, line 9, Fig. 12).
Therefore, it would have been obvious to one of ordinary skill in the art, prior to the effective filing date of the claimed invention to modify Chen’s model request system to include requesting a license and a key as described in Lally’s controlled model access system for the advantage of having a more secure remote processing system.
As per claim 10, the combination teaches wherein the license package includes a first decryption key to decrypt a first component of the model and a second decryption key to decrypt a second component of the model (Chen: wrapped key, [0036]).
As per claim 14, the combination teaches wherein the identified distributed server is located geographically closest to the system (Chen: latency considerations, [0094][0098-0099]).
As per claim 15, the combination teaches wherein the identified distributed server is located closest to the system based on at least one of network topology, latency, or network transmission cost (Chen: latency considerations, [0094][0098-0099]).
Claim(s) 11 – 13 are rejected under 35 U.S.C. 103 as being unpatentable over Chen, publication number: US 2025/0254207 in view of Lally, patent number: US 12 518 038 in further view of Johnson, publication number: US 2024/0232705.
As per claim 11, Chen and Lally teach receiving a model based on latency with regards to servers.
The combination does not teach wherein the operations further comprise:
generating a request for available AI models; and
receiving a list of available AI models, including the AI model.
In an analogous art, Johnson teaches wherein the operations further comprise:
generating a request for available AI models; and
receiving a list of available AI models, including the AI model (receiving a request for models, ranking available models based on execution environment, Fig. 2a, [0045-0058]).
Therefore, it would have been obvious to one of ordinary skill in the art, prior to the effective filing date of the claimed invention to modify the combination of Chen and Lally to include providing only relevant model as described in Johnson’s model provision system for the advantage of providing only context relevant models thereby creating a more efficient system.
As per claim 12, the combination teaches wherein the request for available AI models includes device-level details of the system, and the list of available AI models is based on the device-level details (Johnson: ranking available models based on execution environment, Fig. 2a, [0045-0058]).
As per claim 13, the combination teaches wherein the request for available AI models includes account-level details for a user of the system, and the list of available Al models is based on the account-level details (Johnson: ranking available models based on execution environment, Fig. 2a, [0045-0058], Lally: authorization capability, col. 15, line 61 – col. 16, line 10).
Conclusion
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/OLUGBENGA O IDOWU/Primary Examiner, Art Unit 2494
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