DETAILED ACTION
Remarks
This office action is issued in response to communication filed on 10/20/25. 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 to claims 1 and 12 to recite “deployed in a computer main frame or different computers” fail to overcome the 101 rejection because the recited “computer mainframe or different computers” are not part of the hardware of claims 1 and 12. The examiner suggest amending these claims to recite “..comprising : a computer mainframe or different computers” or “..comprising : a processor” to overcome the rejection.
Applicant’s arguments with respect to 35 USC 103 rejection have been considered and are moot in view of new ground of rejection.
Claim Objections
Claims 1 and 12 are objected to because of the following informalities: Claim 1 and 12 now recite in part “ wherein the artificial intelligence service modules further comprises”. There is insufficient antecedent basis for the recited “service modules” (in plural form). Claims 1 and 12 only recite “at least one artificial intelligence model service model” . The examiner suggests amending the claims to recite “wherein the at least one artificial intelligence model service module further comprises”. 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.
Claims 1- 4,6-9,12-15 and 17-20 are rejected under 35 U.S.C. 101 because claimed invention directed toward non-statutory subject matter.
Claim 1 and 12 recite a system with different “module”, model plugin and “controller” but fail to specify a qualified hardware element. During examination, the claims must be interpreted as broadly as their terms reasonably allow. The broadest reasonable interpretation of a claim drawn to a system that fails to recite a required hardware element covers software per se. Software is not a “process”, a “machine”, a manufacture”, or a “composition of matter” as defined in 35 U.S.C. 101.
Accordingly, the recited “system” is not a “process”, a “machine”, a “manufacture”, or a “composition of matter" as defined in 35 U.S.C 101 and claim 1 and 12 fail to recite statutory subject matter as defined in 35 U.S.C 101. Claims 2-4,6-9. 13-15 and 16-20 are also rejected under 35 USC 101 for failing to further recite a hardware element. Appropriate correction is required.
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 1-4,6-7,9,12-15,17-18 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Padinjarel et al.(US Patent Application Publication 2015/0058868 A1, hereinafter “and further in view of Goyal et al.(US Patent Application Publication 2023/0214276 A1, hereinafter “Goyal”), further in view of Liljenstam et al.(US Patent Application Publication 2025/0021652 A1, hereinafter “Liljenstam”
As to claims 1 and 12, Padinjarel teaches an artificial intelligence model control system, comprising:
a plurality of artificial intelligence model service modules , deployed in a computer mainframe or different computers;( Padinjarel par [0025] teaches backend system 170)
a plurality of model plugins deployed in the computer mainframe, 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 (Padinjarel par [0026] teaches plurality of plugins 150-a. Padinjarel par [0028] teaches different reading plugins may be used with different backend systems or with different configurations of a backend system 170) ; and
a model controller, modules, deployed in the computer mainframe and connected to the model plugins and controlling, through the model plugin, the corresponding artificial intelligence model service module to perform a task. (Padinjarel par [0025] teaches the execution system may comprise a common controller object 130 operative to receive standardized command 120 and generate a first standardized plugin command 140)
Padinjarel fails to expressly teach a plurality of artificial intelligence model service modules, deployed in a computer mainframe or different computers.
However, Goyal teaches a plurality of artificial intelligence model service modules, (Goyal Fig.3 and par [0060] teaches artificial intelligence models 332 located on the server computer 304) deployed in a computer mainframe or different computers.(Goyal par [0048] teaches mainframes 210)
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 Padinjarel with Goyal’s a plurality of artificial intelligence model service modules, deployed in a computer mainframe or different computers to achieve the claimed invention. One would have been motivated to make such combination to insulate applications from changes in artificial intelligence models.(Goyal par [0144])
Padinjarel and Goyal fail to expressly teach wherein each of the artificial intelligence model service modules further comprises: a model interface, establishing a corresponding transmission relationship with the corresponding model plugin; 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.
However, Liljenstam teaches a model interface, establishing a corresponding transmission relationship with the corresponding model plugin; 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.( Liljenstam Fig.3 and par [00102] teaches the ML assisted service 300 includes query handler 310 ( interpreted as the “model interface”) that receives incoming inference queries and decide how to handle them …)
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 Padinjarel and Goyal with the teachings of Liljenstam to achieve the claimed invention. One would have been motivated to make such combination to improve the security of ML models exposed over APIs. (Liljenstam par [0017])
As to claims 2 and 13, Padinjarel , Goyal and Liljenstam 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. (Padinjarel par [0026] teaches the plugins 150-a may provide access to the back end system 170 and perform various tasks using the backend system 170)
As to claims 3 and 14, Padinjarel , Goyal and Liljenstam 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. (Padinjarel par [0030] teaches the plugins 150-a may return results after receiving and performing commands)
As to claims 4 and 15 , Padinjarel , Goyal and Liljenstam teach, wherein the model plugin communicates with the artificial intelligence model service module through a Web application programming interface (API). ( Padinjarel par [0015] teach providing a common API for access to a backend system)
As to claims 6 and 17, Padinjarel , Goyal and Liljenstam teach wherein when a specific one of the artificial intelligence model service modules is disabled, the specific artificial intelligence model service module is directly disabled in the model controller, so that the model controller and the model plugin are not connected. (disabling the service module in the controller is well known in the art)
As to claims 7 and 18, Padinjarel , Goyal and Liljenstam teach further comprising a user interface connected to the model controller, so that data is provided to the model controller through the user interface. (Padinjarel par [0050] teaches the module 110 may comprise a user interface component operative to receive a user command from a user, to determine the standardized command 120 based on the user command, to submitted the standardized command 120 to the common controller object 130, to receive a standardized result 225 or combined result 625 from the common controller object 130, and to display the standardized result 225 or combined result 625 for the user)
As to claims 9 and 20, Padinjarel , Goyal and Liljenstam teach wherein the task is a training, a verification, a deployment, or an inference. ( Goyal Fig.3 and par [0060] teaches artificial intelligence models 332. AI model that performs the task of inference is well known )
Claims 8 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Padinjarel , Goyal and Liljenstam and further in view of Li.(US Patent Application Publication 2015/0150128 A1, hereinafter “Li”)
As to claims 8 and 19, Padinjarel , Goyal and Liljenstam 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 Padinjarel , Goyal and Liljenstam 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
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
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/HIEN L DUONG/Primary Examiner, Art Unit 2147