DETAILED ACTION
Remarks
This office action is issued in response to communication filed on 4/6/2026. Claims 1-4,6-9 , 12-15 and 17-20 are pending 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 .
Response to Amendment/Arguments
Applicant’s amendments overcome the claim objection and 101 rejection. Accordingly, the objection and 101 rejection have been withdrawn.
Applicant’s arguments filed 4/6/26 with respect to 35 USC 103 rejection have been considered and are moot in view of new ground of rejection.
Claim Objections
Claim 1 is objected to because of the following informalities: Claim 1 recites the limitation “wherein each model plugin corresponds to one of the artificial intelligence model service modules”. There is insufficient antecedent basis for this claim limitation because “ artificial intelligence model service modules” has not been mentioned before in the claim . Appropriate correction is required.
Allowable Subject Matter
Claims 6 and 17 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. Although these claims are allowable over prior art, all other rejections and/or objections (if any) such as 101/112/claim objection must be overcome before the claims are allowed.
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.
Claims 1-4,7,9,12-15, 18 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Penilla et al.(US Patent Application Publication 2020/0249822 A1, hereinafter “Penilla”) and further in view of Gopalan et al.(US Patent Application Publication 2020/0310888 A1, hereinafter “Gopalan”)
As to claims 1 and 12, Penilla teaches an artificial intelligence model control system, comprising:
a plurality different computers, [ each with an artificial intelligence model service module] and a computer mainframe (Penilla par [0313] teaches “embodiments of the present invention may be practiced with various computer system configurations including hand-held devices, microprocessor systems, microprocessor-based or programmable consumer electronics, minicomputers, mainframe computers and the like”), comprises:
a plurality of model plugins , wherein each model plugin corresponds to one of [the artificial intelligence model service modules ], and the model plugin communicates with the corresponding artificial intelligence model service module (Penilla Fig.12 and par [0194] teaches a user interacts with a model view controller software environment 1800 useful for processing APPS using APIs 130 on vehicles with vehicle operating systems 129 capable of processing computer code) ; and
a model controller, connected to the model plugins and controlling, through the model plugin, [the corresponding artificial intelligence model service module] to perform a task. (Penilla Fig.12 and par [0194] controller 1804 that may constantly poll electrical, capacitive and physical sensors, and input streams to detect if interactions 1808 such as network passive updates, network active updates, user touch, user speech, user input, user selection among others has been triggered)
wherein each of [the artificial intelligence model service module] further comprises:
a model interface, establishing a corresponding transmission relationship with the corresponding model plugin (Pinella Fig.12 and par [0198] teaches The model view controller paradigm 1800 described is one example of the software input output lifecycle that may be used to invoke, manipulate, process, update portions of computer readable code such as APPS 104 using an intermediary API 130 to communicate with the vehicle's operating system 130. Although Pinella is silent with respect to a model interface, In order for the APP to use the intermediate API to communicate, the interface between the app and API must exist and therefore, Penilla teaches or suggests the “model interface”); and
an artificial intelligence model, connected to the model interface, wherein the artificial intelligence model communicates with the model plugin through the model interface, so that the model controller controls, through the model plugin and the model interface, the artificial intelligence model to perform the task.(Penilla Fig.12 and par [0195] teaches Each input 1804 will then trigger manipulation of the system's model 1802 portion of the APP software paradigm thus invoking stored routines within APPS 104 which then in turn interact with the vehicle's API system 130 built upon the vehicle's operating system 129. Depending on the app presented to the user 121, the input may trigger stored routines or functions on APP software or operating system level restricted stored routines or functions. Pinella par [0211]-[0212] teaches APP 104 which being interpreted as AI model)
Pinella fails to expressly teach an artificial intelligence model service module.
However, Gopalan teaches an artificial intelligence model service module.( Gopalan par [0149] a ML service module )
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teaching of Pinella and Gopalan to achieve the claimed invention. One would have been motivated to make such combination to allow each service module to exist and work independently of each other, thereby enabling the developer to plug and play the APIs in order to build the client support application (Gopalan par [0068])
As to claims 2 and 13, Pinella and Gopalan teach , wherein the model plugin generates a request for the corresponding artificial intelligence model service module according to an instruction of the model controller, so that the artificial intelligence model service module executes the request. (Pinella par [0195]-[0196] teaches Such a system useful for running APPS on vehicle operating systems will accept inputs by a user 121, cloud services 120 via data streams, vehicle systems feedback and data streams 1812 used by a controller 1804 that may constantly poll electrical, capacitive and physical sensors, and input streams to detect if interactions 1808 such as network passive updates, network active updates, user touch, user speech, user input, user selection among others has been triggered.
[0195] Each input 1804 will then trigger manipulation of the system's model 1802 portion of the APP software paradigm thus invoking stored routines within APPS 104 which then in turn interact with the vehicle's API system 130 built upon the vehicle's operating system 129. Depending on the app presented to the user 121, the input may trigger stored routines or functions on APP software or operating system level restricted stored routines or functions.)
As to claims 3 and 14, Pinella and Gopalan teach wherein the artificial intelligence model service module generates a response according to a result of execution of the request, and transmits the response to the model controller through the model plugin. (Pinella par [0196] teaches [0195] Each input 1804 will then trigger manipulation of the system's model 1802 portion of the APP software paradigm thus invoking stored routines within APPS 104 which then in turn interact with the vehicle's API system 130 built upon the vehicle's operating system 129 )
As to claims 4 and 15 , Pinella and Gopalan teach, wherein the model plugin communicates with the artificial intelligence model service module through a Web application programming interface (API). ( Pinella Fig.12 and par [0198] teaches The model view controller paradigm 1800 described is one example of the software input output lifecycle that may be used to invoke, manipulate, process, update portions of computer readable code such as APPS 104 using an intermediary API 130 to communicate with the vehicle's operating system 130)
As to claims 7 and 18, Pinella and Gopalan teach further comprising a user interface connected to the model controller, so that data is provided to the model controller through the user interface. (Pinella par [0196] teaches after the processing of stored procedure code is manipulated with arguments provided by the controller 1804 inputs, visual and or sensory results are presented to the user in the view 1806 portion of the model view controller paradigm)
As to claims 9 and 20, Pinella and Gopalan teach wherein the task is a training, a verification, a deployment, or an inference. (Pinella par [0212] teaches some of the inputs and results 2102 that an APP can take and produce locally or remotely include but are not limited to the set 2104 that can receive an action, react to an action, control an action, manipulate data models, report changes to a view or GUI, record events or incidents, learn the types of requests being submitted, learn the times of request being submitted over time, learn the days of the year the requests are being submitted over time, generalize and interpret requests, assume user intent in order to automatically invoke changes, automatically and pre-emptively act on behalf of a user, fine tune learned user behavior etc.)
Claims 8 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Pinella, Gopalan and further in view of Li.(US Patent Application Publication 2015/0150128 A1, hereinafter “Li”)
As to claims 8 and 19, Pinella and Gopalan fail to teach wherein each of the model plugins is an independent dynamic link library.
However, Li teaches wherein each of the model plugins is an independent dynamic link library. (Li par [0066] teaches the performance acquisition model 201, evaluation / determinate module 202 and plugin processing module 203 generally can be one or several independent installation files based on the needs and whose functionalities can be implemented as either Dynamic Link Library (DLL) or Label information Base (LIB)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teaching of Pinella , Gopalan and Li to achieve the claimed invention. One would have been motivated to make such combination to enhance the stability of the system.(Li par [0006])
Conclusion
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/HIEN L DUONG/Primary Examiner, Art Unit 2147
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