DETAILED ACTION
This action is responsive to application filed on October 30, 2023.
Claims 1-20 are pending and are presented to examination.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Examiner Notes
Examiner cites particular columns, paragraphs, figures and line numbers in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner.
Drawings
The drawings filed on October 30, 2023 are acceptable for examination purposes.
Information Disclosure Statement
As required by M.P.E.P. 609, the applicant’s submission of the Information Disclosure Statements dated July 22, 2024, June 06, 2025 and September 23, 2025 are acknowledged by the examiner and the cited references have been considered in the examination of the claims now allowed.
Specification
The abstract of the disclosure is objected to because discloses “…a generative AI model…” please change that to “a generative artificial intelligence (AI)”. A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are: “a user interface component”, “a generative AI component”, and “a project generation component” in claim 1.
Because these claim limitations are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they are being interpreted to cover the corresponding structure described in the specification (e.g., paragraph [0026]) as performing the claimed function, and equivalents thereof.
If applicant does not intend to have these limitations interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation) recite sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1, lines 16-17, “the control code” is unclear whether it refers to “control code” in line 7 or 13 of the claim. For the examination purposes, “the control code” in lines 16-17 will be treated as --the generated control code--.
Claims 11 and 19 have the same issue and, for the examination purposes, “the control code” in line 13 of claim 11 and in line 15 of claim 19 will be treated as --the generated control code--, respectively.
Claims 2-10, 12-18, and 20 depend on the rejected claims and inherit the same issue.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l)(1) - 706.02(l)(3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1 of co-pending application No. 18/645,628. Herein the independent claims are shown mapped to claim 1 of the co-pending application. The dependent claims are ODP in view of dependent claims of claim 1 or in view of the prior art used in the art rejection below associated with that dependent claim.
Instant Application 18/497,191
App. No. 18/645,628
Claim 1A system, comprising: a memory that stores executable components and a generative artificial intelligence (AI) model; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to receive, as natural language input, a prompt comprising a request for control code for an industrial system project in development, wherein the request specifies one or more requirements of the control code; a generative AI component configured to perform contextual analysis on the industrial system project to determine at least one of a type of industrial application or an industrial vertical for which the industrial system project is being developed, and to generate, using the generative AI model, control code inferred to satisfy the one or more requirements based on analysis of the prompt and a result of the contextual analysis; and a project generation component configured to integrate the control code into the industrial system project.
Claim 1A system, comprising: a memory that stores executable components; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to receive, from a client device as natural language input, a query describing a performance issue relating to an industrial automation system for which technical support is requested; and a generative artificial intelligence (AI) component configured to, in response to receipt of the query, formulate a prompt, directed to a generative AI model, designed to obtain a response from the generative AI model comprising information used by the generative AI component to generate a natural language technical support response describing a recommendation for addressing the performance issue, wherein the generative AI component generates the prompt based on analysis of the query and a selected subset of industrial training data encoded in one or more custom models, wherein the user interface component is configured to render the natural language technical support response on the client device.
Claim 11A method, comprising: receiving, as natural language input by an industrial integrated development environment (IDE) system comprising a processor, a prompt comprising a request for control code for an industrial system project being developed, wherein the request specifies one or more requirements of the control code; performing, by the industrial IDE system using a generative artificial intelligence (AI) model, contextual analysis on the industrial system project to determine at least one of a type of industrial application or an industrial vertical for which the industrial system project is being developed; generating, by the industrial IDE system using the generative AI model, control code determined to satisfy the one or more requirements based on analysis of the prompt and a result of the contextual analysis; and integrating, by the industrial IDE system, the control code into the industrial system project.
Claim 1A system, comprising: a memory that stores executable components; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to receive, from a client device as natural language input, a query describing a performance issue relating to an industrial automation system for which technical support is requested; and a generative artificial intelligence (AI) component configured to, in response to receipt of the query, formulate a prompt, directed to a generative AI model, designed to obtain a response from the generative AI model comprising information used by the generative AI component to generate a natural language technical support response describing a recommendation for addressing the performance issue, wherein the generative AI component generates the prompt based on analysis of the query and a selected subset of industrial training data encoded in one or more custom models, wherein the user interface component is configured to render the natural language technical support response on the client device.
Claim 19A non-transitory computer-readable medium having stored thereon instructions that, in response to execution, cause an industrial integrated development environment (IDE) system comprising a processor to perform operations, the operations comprising:receiving a natural language prompt requesting control code for an industrial system project being developed, wherein the natural language prompt describes one or more requirements of the control code; performing, using a generative artificial intelligence (AI) model, contextual analysis on the industrial system project to determine at least one of a type of industrial application or an industrial vertical for which the industrial system project is being developed; generating, using the generative AI model, control code that satisfies the one or more requirements based on analysis of the prompt and a result of the contextual analysis; and integrating the control code into the industrial system project.
Claim 1A system, comprising: a memory that stores executable components; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to receive, from a client device as natural language input, a query describing a performance issue relating to an industrial automation system for which technical support is requested; and a generative artificial intelligence (AI) component configured to, in response to receipt of the query, formulate a prompt, directed to a generative AI model, designed to obtain a response from the generative AI model comprising information used by the generative AI component to generate a natural language technical support response describing a recommendation for addressing the performance issue, wherein the generative AI component generates the prompt based on analysis of the query and a selected subset of industrial training data encoded in one or more custom models, wherein the user interface component is configured to render the natural language technical support response on the client device.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1 of cop ending application No. 18/614,925. Herein the independent claims are shown mapped to claim 1 of the co-related applications. The dependent claims are ODP in view of dependent claims of claim 1 or in view of the prior art used in the art rejection below associated with that dependent claim.
Instant Application 18/497,191
App. No. 18/614,925
Claim 1A system, comprising: a memory that stores executable components and a generative artificial intelligence (AI) model; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to receive, as natural language input, a prompt comprising a request for control code for an industrial system project in development, wherein the request specifies one or more requirements of the control code; a generative AI component configured to perform contextual analysis on the industrial system project to determine at least one of a type of industrial application or an industrial vertical for which the industrial system project is being developed, and to generate, using the generative AI model, control code inferred to satisfy the one or more requirements based on analysis of the prompt and a result of the contextual analysis; and a project generation component configured to integrate the control code into the industrial system project.
Claim 1A system, comprising: a memory that stores executable components and one or more custom models; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to render an integrated development environment (IDE) interface and to receive, via interaction with the IDE interface, industrial control code input that defines an industrial control program; and a project generation component configured to generate, based on the industrial control programming input, an executable control program file that, in response to execution on an industrial controller, causes the industrial controller to monitor and control an industrial automation system in accordance with the industrial control program, wherein the user interface component is further configured to receive a natural language request for control code to be included in the industrial control program, wherein the natural language request specifies one or more requirements of the control code, the executable components further comprise a generative artificial intelligence (AI) component configured to, in response to receipt of the natural language request, formulate a prompt, directed to a generative AI model, designed to obtain a response from the generative AI model comprising information used by the generative AI component to generate control code inferred to satisfy the one or more requirements, wherein the prompt is generated based on analysis of the natural language request and industry knowledge encoded in the one or more custom models, and the project generation component is further configured to integrate the control code into the industrial control program.
Claim 11A method, comprising: receiving, as natural language input by an industrial integrated development environment (IDE) system comprising a processor, a prompt comprising a request for control code for an industrial system project being developed, wherein the request specifies one or more requirements of the control code; performing, by the industrial IDE system using a generative artificial intelligence (AI) model, contextual analysis on the industrial system project to determine at least one of a type of industrial application or an industrial vertical for which the industrial system project is being developed; generating, by the industrial IDE system using the generative AI model, control code determined to satisfy the one or more requirements based on analysis of the prompt and a result of the contextual analysis; and integrating, by the industrial IDE system, the control code into the industrial system project.
Claim 1A system, comprising: a memory that stores executable components and one or more custom models; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to render an integrated development environment (IDE) interface and to receive, via interaction with the IDE interface, industrial control code input that defines an industrial control program; and a project generation component configured to generate, based on the industrial control programming input, an executable control program file that, in response to execution on an industrial controller, causes the industrial controller to monitor and control an industrial automation system in accordance with the industrial control program, wherein the user interface component is further configured to receive a natural language request for control code to be included in the industrial control program, wherein the natural language request specifies one or more requirements of the control code, the executable components further comprise a generative artificial intelligence (AI) component configured to, in response to receipt of the natural language request, formulate a prompt, directed to a generative AI model, designed to obtain a response from the generative AI model comprising information used by the generative AI component to generate control code inferred to satisfy the one or more requirements, wherein the prompt is generated based on analysis of the natural language request and industry knowledge encoded in the one or more custom models, and the project generation component is further configured to integrate the control code into the industrial control program.
Claim 19A non-transitory computer-readable medium having stored thereon instructions that, in response to execution, cause an industrial integrated development environment (IDE) system comprising a processor to perform operations, the operations comprising:receiving a natural language prompt requesting control code for an industrial system project being developed, wherein the natural language prompt describes one or more requirements of the control code; performing, using a generative artificial intelligence (AI) model, contextual analysis on the industrial system project to determine at least one of a type of industrial application or an industrial vertical for which the industrial system project is being developed; generating, using the generative AI model, control code that satisfies the one or more requirements based on analysis of the prompt and a result of the contextual analysis; and integrating the control code into the industrial system project.
Claim 1A system, comprising: a memory that stores executable components and one or more custom models; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to render an integrated development environment (IDE) interface and to receive, via interaction with the IDE interface, industrial control code input that defines an industrial control program; and a project generation component configured to generate, based on the industrial control programming input, an executable control program file that, in response to execution on an industrial controller, causes the industrial controller to monitor and control an industrial automation system in accordance with the industrial control program, wherein the user interface component is further configured to receive a natural language request for control code to be included in the industrial control program, wherein the natural language request specifies one or more requirements of the control code, the executable components further comprise a generative artificial intelligence (AI) component configured to, in response to receipt of the natural language request, formulate a prompt, directed to a generative AI model, designed to obtain a response from the generative AI model comprising information used by the generative AI component to generate control code inferred to satisfy the one or more requirements, wherein the prompt is generated based on analysis of the natural language request and industry knowledge encoded in the one or more custom models, and the project generation component is further configured to integrate the control code into the industrial control program.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1 of co-pending application No. 18/614,956. Herein the independent claims are shown mapped to claim 1 of the co-pending application. The dependent claims are ODP in view of dependent claims of claim 1 or in view of the prior art used in the art rejection below associated with that dependent claim.
Instant Application 18/497,191
App. No. 18/614,956
Claim 1A system, comprising: a memory that stores executable components and a generative artificial intelligence (AI) model; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to receive, as natural language input, a prompt comprising a request for control code for an industrial system project in development, wherein the request specifies one or more requirements of the control code; a generative AI component configured to perform contextual analysis on the industrial system project to determine at least one of a type of industrial application or an industrial vertical for which the industrial system project is being developed, and to generate, using the generative AI model, control code inferred to satisfy the one or more requirements based on analysis of the prompt and a result of the contextual analysis; and a project generation component configured to integrate the control code into the industrial system project.
Claim 1A system, comprising: a memory that stores executable components and one or more custom models; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to render a project development interface and to receive, via interaction with the project development interface, design input that defines aspects of an industrial system project, wherein the design input comprises natural language requests received via a chat interface; a generative artificial intelligence (AI) component configured to, in response to receipt of a first natural language request, of the natural language requests, describing one or more requirements of control code to be created as part of the industrial system project, generate control code inferred to satisfy the one or more requirements and create a smart object definition representing the control code, wherein the generative AI component is configured to generate the control code based on based on analysis of the first natural language request, industry-specific information encoded in the one or more custom models, and a response prompted from a generative AI model, and in response to receipt of a second natural language request, of the natural language requests, to allocate an instance of the smart object definition to a controller definition defined in the industrial system project and representing an industrial controller, record a binding between the instance of the smart object definition and the controller definition, wherein the binding configures the industrial system project to assign a copy of the control code associated with the smart object definition to the industrial controller represented by the controller definition; and a project generation component configured to generate, based on the design input, an executable control program file that, in response to execution on the industrial controller represented by the controller definition, configures the industrial controller in accordance with the controller definition and causes the industrial controller to monitor and control an industrial automation system in accordance with the control code.
Claim 11A method, comprising: receiving, as natural language input by an industrial integrated development environment (IDE) system comprising a processor, a prompt comprising a request for control code for an industrial system project being developed, wherein the request specifies one or more requirements of the control code; performing, by the industrial IDE system using a generative artificial intelligence (AI) model, contextual analysis on the industrial system project to determine at least one of a type of industrial application or an industrial vertical for which the industrial system project is being developed; generating, by the industrial IDE system using the generative AI model, control code determined to satisfy the one or more requirements based on analysis of the prompt and a result of the contextual analysis; and integrating, by the industrial IDE system, the control code into the industrial system project.
Claim 1A system, comprising: a memory that stores executable components and one or more custom models; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to render a project development interface and to receive, via interaction with the project development interface, design input that defines aspects of an industrial system project, wherein the design input comprises natural language requests received via a chat interface; a generative artificial intelligence (AI) component configured to, in response to receipt of a first natural language request, of the natural language requests, describing one or more requirements of control code to be created as part of the industrial system project, generate control code inferred to satisfy the one or more requirements and create a smart object definition representing the control code, wherein the generative AI component is configured to generate the control code based on based on analysis of the first natural language request, industry-specific information encoded in the one or more custom models, and a response prompted from a generative AI model, and in response to receipt of a second natural language request, of the natural language requests, to allocate an instance of the smart object definition to a controller definition defined in the industrial system project and representing an industrial controller, record a binding between the instance of the smart object definition and the controller definition, wherein the binding configures the industrial system project to assign a copy of the control code associated with the smart object definition to the industrial controller represented by the controller definition; and a project generation component configured to generate, based on the design input, an executable control program file that, in response to execution on the industrial controller represented by the controller definition, configures the industrial controller in accordance with the controller definition and causes the industrial controller to monitor and control an industrial automation system in accordance with the control code.
Claim 19A non-transitory computer-readable medium having stored thereon instructions that, in response to execution, cause an industrial integrated development environment (IDE) system comprising a processor to perform operations, the operations comprising:receiving a natural language prompt requesting control code for an industrial system project being developed, wherein the natural language prompt describes one or more requirements of the control code; performing, using a generative artificial intelligence (AI) model, contextual analysis on the industrial system project to determine at least one of a type of industrial application or an industrial vertical for which the industrial system project is being developed; generating, using the generative AI model, control code that satisfies the one or more requirements based on analysis of the prompt and a result of the contextual analysis; and integrating the control code into the industrial system project.
Claim 1A system, comprising: a memory that stores executable components and one or more custom models; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to render a project development interface and to receive, via interaction with the project development interface, design input that defines aspects of an industrial system project, wherein the design input comprises natural language requests received via a chat interface; a generative artificial intelligence (AI) component configured to, in response to receipt of a first natural language request, of the natural language requests, describing one or more requirements of control code to be created as part of the industrial system project, generate control code inferred to satisfy the one or more requirements and create a smart object definition representing the control code, wherein the generative AI component is configured to generate the control code based on based on analysis of the first natural language request, industry-specific information encoded in the one or more custom models, and a response prompted from a generative AI model, and in response to receipt of a second natural language request, of the natural language requests, to allocate an instance of the smart object definition to a controller definition defined in the industrial system project and representing an industrial controller, record a binding between the instance of the smart object definition and the controller definition, wherein the binding configures the industrial system project to assign a copy of the control code associated with the smart object definition to the industrial controller represented by the controller definition; and a project generation component configured to generate, based on the design input, an executable control program file that, in response to execution on the industrial controller represented by the controller definition, configures the industrial controller in accordance with the controller definition and causes the industrial controller to monitor and control an industrial automation system in accordance with the control code.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1 of co-pending application No. 18/952,567. Herein the independent claims are shown mapped to claim 1 of the pending application. The dependent claims are ODP in view of dependent claims of claim 1 or in view of the prior art used in the art rejection below associated with that dependent claim.
Instant Application 18/497,191
App. No. 18/952,567
Claim 1A system, comprising: a memory that stores executable components and a generative artificial intelligence (AI) model; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to receive, as natural language input, a prompt comprising a request for control code for an industrial system project in development, wherein the request specifies one or more requirements of the control code; a generative AI component configured to perform contextual analysis on the industrial system project to determine at least one of a type of industrial application or an industrial vertical for which the industrial system project is being developed, and to generate, using the generative AI model, control code inferred to satisfy the one or more requirements based on analysis of the prompt and a result of the contextual analysis; and a project generation component configured to integrate the control code into the industrial system project.
Claim 1A system, comprising: a memory that stores executable components and one or more custom models; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to render an integrated development environment (IDE) interface and to receive, via interaction with the IDE interface, a natural language request for control code to be included in an industrial control program, wherein the natural language request specifies one or more requirements of the control code; a generative artificial intelligence (AI) component configured to, in response to receipt of the natural language request: generate control code inferred to satisfy the one or more requirements based on content of the natural language request and responses prompted from a generative AI model, generate natural language documentation for the control code based on the content of the natural language request and the responses prompted from a generative AI model, and embed the natural language documentation into the control code; and a project generation component configured to generate, based on the control code, an executable control program file that, in response to execution on an industrial controller, causes the industrial controller to monitor and control an industrial automation system in accordance with the control code.
Claim 11A method, comprising: receiving, as natural language input by an industrial integrated development environment (IDE) system comprising a processor, a prompt comprising a request for control code for an industrial system project being developed, wherein the request specifies one or more requirements of the control code; performing, by the industrial IDE system using a generative artificial intelligence (AI) model, contextual analysis on the industrial system project to determine at least one of a type of industrial application or an industrial vertical for which the industrial system project is being developed; generating, by the industrial IDE system using the generative AI model, control code determined to satisfy the one or more requirements based on analysis of the prompt and a result of the contextual analysis; and integrating, by the industrial IDE system, the control code into the industrial system project.
Claim 1A system, comprising: a memory that stores executable components and one or more custom models; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to render an integrated development environment (IDE) interface and to receive, via interaction with the IDE interface, a natural language request for control code to be included in an industrial control program, wherein the natural language request specifies one or more requirements of the control code; a generative artificial intelligence (AI) component configured to, in response to receipt of the natural language request: generate control code inferred to satisfy the one or more requirements based on content of the natural language request and responses prompted from a generative AI model, generate natural language documentation for the control code based on the content of the natural language request and the responses prompted from a generative AI model, and embed the natural language documentation into the control code; and a project generation component configured to generate, based on the control code, an executable control program file that, in response to execution on an industrial controller, causes the industrial controller to monitor and control an industrial automation system in accordance with the control code.
Claim 19A non-transitory computer-readable medium having stored thereon instructions that, in response to execution, cause an industrial integrated development environment (IDE) system comprising a processor to perform operations, the operations comprising:receiving a natural language prompt requesting control code for an industrial system project being developed, wherein the natural language prompt describes one or more requirements of the control code; performing, using a generative artificial intelligence (AI) model, contextual analysis on the industrial system project to determine at least one of a type of industrial application or an industrial vertical for which the industrial system project is being developed; generating, using the generative AI model, control code that satisfies the one or more requirements based on analysis of the prompt and a result of the contextual analysis; and integrating the control code into the industrial system project.
Claim 1A system, comprising: a memory that stores executable components and one or more custom models; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to render an integrated development environment (IDE) interface and to receive, via interaction with the IDE interface, a natural language request for control code to be included in an industrial control program, wherein the natural language request specifies one or more requirements of the control code; a generative artificial intelligence (AI) component configured to, in response to receipt of the natural language request: generate control code inferred to satisfy the one or more requirements based on content of the natural language request and responses prompted from a generative AI model, generate natural language documentation for the control code based on the content of the natural language request and the responses prompted from a generative AI model, and embed the natural language documentation into the control code; and a project generation component configured to generate, based on the control code, an executable control program file that, in response to execution on an industrial controller, causes the industrial controller to monitor and control an industrial automation system in accordance with the control code.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1 of co-pending application No. 18/610,444. Herein the independent claims are shown mapped to claim 1 of the co-pending application. The dependent claims are ODP in view of dependent claims of claim 1 or in view of the prior art used in the art rejection below associated with that dependent claim.
Instant Application 18/497,191
App. No. 18/610,444
Claim 1A system, comprising: a memory that stores executable components and a generative artificial intelligence (AI) model; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to receive, as natural language input, a prompt comprising a request for control code for an industrial system project in development, wherein the request specifies one or more requirements of the control code; a generative AI component configured to perform contextual analysis on the industrial system project to determine at least one of a type of industrial application or an industrial vertical for which the industrial system project is being developed, and to generate, using the generative AI model, control code inferred to satisfy the one or more requirements based on analysis of the prompt and a result of the contextual analysis; and a project generation component configured to integrate the control code into the industrial system project.
Claim 1A system, comprising: a memory that stores executable components and one or more custom models; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to receive, via an integrated development environment (IDE) interface, a natural language query directed to industrial control code that, in response to execution on an industrial controller, causes the industrial controller to monitor and control an industrial automation system in accordance with the industrial control code; and a generative artificial intelligence (AI) component configured to, in response to receipt of the natural language query, generate a natural language answer to the natural language query based on analysis of the industrial control code, industry knowledge encoded in the one or more custom models, and a response prompted from a generative AI model comprising information used by the generative AI component to formulate the natural language answer, wherein the user interface component is configured to render the natural language answer on the IDE interface.
Claim 11A method, comprising: receiving, as natural language input by an industrial integrated development environment (IDE) system comprising a processor, a prompt comprising a request for control code for an industrial system project being developed, wherein the request specifies one or more requirements of the control code; performing, by the industrial IDE system using a generative artificial intelligence (AI) model, contextual analysis on the industrial system project to determine at least one of a type of industrial application or an industrial vertical for which the industrial system project is being developed; generating, by the industrial IDE system using the generative AI model, control code determined to satisfy the one or more requirements based on analysis of the prompt and a result of the contextual analysis; and integrating, by the industrial IDE system, the control code into the industrial system project.
Claim 1A system, comprising: a memory that stores executable components and one or more custom models; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to receive, via an integrated development environment (IDE) interface, a natural language query directed to industrial control code that, in response to execution on an industrial controller, causes the industrial controller to monitor and control an industrial automation system in accordance with the industrial control code; and a generative artificial intelligence (AI) component configured to, in response to receipt of the natural language query, generate a natural language answer to the natural language query based on analysis of the industrial control code, industry knowledge encoded in the one or more custom models, and a response prompted from a generative AI model comprising information used by the generative AI component to formulate the natural language answer, wherein the user interface component is configured to render the natural language answer on the IDE interface.
Claim 19A non-transitory computer-readable medium having stored thereon instructions that, in response to execution, cause an industrial integrated development environment (IDE) system comprising a processor to perform operations, the operations comprising:receiving a natural language prompt requesting control code for an industrial system project being developed, wherein the natural language prompt describes one or more requirements of the control code; performing, using a generative artificial intelligence (AI) model, contextual analysis on the industrial system project to determine at least one of a type of industrial application or an industrial vertical for which the industrial system project is being developed; generating, using the generative AI model, control code that satisfies the one or more requirements based on analysis of the prompt and a result of the contextual analysis; and integrating the control code into the industrial system project.
Claim 1A system, comprising: a memory that stores executable components and one or more custom models; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to receive, via an integrated development environment (IDE) interface, a natural language query directed to industrial control code that, in response to execution on an industrial controller, causes the industrial controller to monitor and control an industrial automation system in accordance with the industrial control code; and a generative artificial intelligence (AI) component configured to, in response to receipt of the natural language query, generate a natural language answer to the natural language query based on analysis of the industrial control code, industry knowledge encoded in the one or more custom models, and a response prompted from a generative AI model comprising information used by the generative AI component to formulate the natural language answer, wherein the user interface component is configured to render the natural language answer on the IDE interface.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1 of co-pending application No. 18/614,966. Herein the independent claims are shown mapped to claim 1 of the co-pending application. The dependent claims are ODP in view of dependent claims of claim 1 or in view of the prior art used in the art rejection below associated with that dependent claim.
Instant Application 18/497,191
App. No. 18/614,966
Claim 1A system, comprising: a memory that stores executable components and a generative artificial intelligence (AI) model; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to receive, as natural language input, a prompt comprising a request for control code for an industrial system project in development, wherein the request specifies one or more requirements of the control code; a generative AI component configured to perform contextual analysis on the industrial system project to determine at least one of a type of industrial application or an industrial vertical for which the industrial system project is being developed, and to generate, using the generative AI model, control code inferred to satisfy the one or more requirements based on analysis of the prompt and a result of the contextual analysis; and a project generation component configured to integrate the control code into the industrial system project.
Claim 1A system, comprising: a memory that stores executable components and one or more custom models; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to render an integrated development environment (IDE) interface and to receive, via interaction with the IDE interface, design input that defines aspects of an industrial system project; a project generation component configured to generate system project data based on the design input, the system project data comprising at least an industrial control program that, in response to execution on an industrial controller, causes the industrial controller to monitor and control an industrial automation system in accordance with the industrial control program; and a generative artificial intelligence (AI) component configured to formulate and send a prompt to a generative AI model in response to receipt of a natural language input, submitted via the IDE interface, comprising at least one of a request to generate a portion of the industrial system project or a question about the industrial system project, wherein the generative AI component formulates the prompt to obtain a response from the generative AI model comprising information used by the generative AI component to at least one of generate the portion of the industrial system project or generate a natural language answer to the question about the industrial system project, and the generative AI component formulates the prompt based on analysis of the natural language input and industry-specific information encoded in the one or more custom models.
Claim 11A method, comprising: receiving, as natural language input by an industrial integrated development environment (IDE) system comprising a processor, a prompt comprising a request for control code for an industrial system project being developed, wherein the request specifies one or more requirements of the control code; performing, by the industrial IDE system using a generative artificial intelligence (AI) model, contextual analysis on the industrial system project to determine at least one of a type of industrial application or an industrial vertical for which the industrial system project is being developed; generating, by the industrial IDE system using the generative AI model, control code determined to satisfy the one or more requirements based on analysis of the prompt and a result of the contextual analysis; and integrating, by the industrial IDE system, the control code into the industrial system project.
Claim 1A system, comprising: a memory that stores executable components and one or more custom models; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to render an integrated development environment (IDE) interface and to receive, via interaction with the IDE interface, design input that defines aspects of an industrial system project; a project generation component configured to generate system project data based on the design input, the system project data comprising at least an industrial control program that, in response to execution on an industrial controller, causes the industrial controller to monitor and control an industrial automation system in accordance with the industrial control program; and a generative artificial intelligence (AI) component configured to formulate and send a prompt to a generative AI model in response to receipt of a natural language input, submitted via the IDE interface, comprising at least one of a request to generate a portion of the industrial system project or a question about the industrial system project, wherein the generative AI component formulates the prompt to obtain a response from the generative AI model comprising information used by the generative AI component to at least one of generate the portion of the industrial system project or generate a natural language answer to the question about the industrial system project, and the generative AI component formulates the prompt based on analysis of the natural language input and industry-specific information encoded in the one or more custom models.
Claim 19A non-transitory computer-readable medium having stored thereon instructions that, in response to execution, cause an industrial integrated development environment (IDE) system comprising a processor to perform operations, the operations comprising:receiving a natural language prompt requesting control code for an industrial system project being developed, wherein the natural language prompt describes one or more requirements of the control code; performing, using a generative artificial intelligence (AI) model, contextual analysis on the industrial system project to determine at least one of a type of industrial application or an industrial vertical for which the industrial system project is being developed; generating, using the generative AI model, control code that satisfies the one or more requirements based on analysis of the prompt and a result of the contextual analysis; and integrating the control code into the industrial system project.
Claim 1A system, comprising: a memory that stores executable components and one or more custom models; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to render an integrated development environment (IDE) interface and to receive, via interaction with the IDE interface, design input that defines aspects of an industrial system project; a project generation component configured to generate system project data based on the design input, the system project data comprising at least an industrial control program that, in response to execution on an industrial controller, causes the industrial controller to monitor and control an industrial automation system in accordance with the industrial control program; and a generative artificial intelligence (AI) component configured to formulate and send a prompt to a generative AI model in response to receipt of a natural language input, submitted via the IDE interface, comprising at least one of a request to generate a portion of the industrial system project or a question about the industrial system project, wherein the generative AI component formulates the prompt to obtain a response from the generative AI model comprising information used by the generative AI component to at least one of generate the portion of the industrial system project or generate a natural language answer to the question about the industrial system project, and the generative AI component formulates the prompt based on analysis of the natural language input and industry-specific information encoded in the one or more custom models.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1 of co-pending application No. 18/610,486. Herein the independent claims are shown mapped to claim 1 of the co-pending application. The dependent claims are ODP in view of dependent claims of claim 1 or in view of the prior art used in the art rejection below associated with that dependent claim.
Instant Application 18/497,191
App. No. 18/610,486
Claim 1A system, comprising: a memory that stores executable components and a generative artificial intelligence (AI) model; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to receive, as natural language input, a prompt comprising a request for control code for an industrial system project in development, wherein the request specifies one or more requirements of the control code; a generative AI component configured to perform contextual analysis on the industrial system project to determine at least one of a type of industrial application or an industrial vertical for which the industrial system project is being developed, and to generate, using the generative AI model, control code inferred to satisfy the one or more requirements based on analysis of the prompt and a result of the contextual analysis; and a project generation component configured to integrate the control code into the industrial system project.
Claim 1A system, comprising: a memory that stores executable components and one or more custom models; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to receive, via an integrated development environment (IDE) interface, a natural language query directed to industrial control code that, in response to execution on an industrial controller, causes the industrial controller to monitor and control an industrial automation system in accordance with the industrial control code; and a generative artificial intelligence (AI) component configured to, in response to determining, based on analysis of the natural language query, that additional information will yield a response to the natural language query having a probability of satisfying the natural language query that exceeds a threshold, generate a first natural language response that prompts for the additional information and render the first natural language response via the user interface component, and in response to receipt, via the user interface component, of a natural language answer containing the additional information, generate a second natural language response to the natural language query based on analysis of the industrial control code, the natural language answer, industry knowledge encoded in the one or more custom models, and a response prompted from a generative AI model, wherein the response prompted from the generative AI model comprising information used by the generative AI component to formulate the second natural language response, wherein the user interface component is configured to render the second natural language response on the IDE interface.
Claim 11A method, comprising: receiving, as natural language input by an industrial integrated development environment (IDE) system comprising a processor, a prompt comprising a request for control code for an industrial system project being developed, wherein the request specifies one or more requirements of the control code; performing, by the industrial IDE system using a generative artificial intelligence (AI) model, contextual analysis on the industrial system project to determine at least one of a type of industrial application or an industrial vertical for which the industrial system project is being developed; generating, by the industrial IDE system using the generative AI model, control code determined to satisfy the one or more requirements based on analysis of the prompt and a result of the contextual analysis; and integrating, by the industrial IDE system, the control code into the industrial system project.
Claim 1A system, comprising: a memory that stores executable components and one or more custom models; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to receive, via an integrated development environment (IDE) interface, a natural language query directed to industrial control code that, in response to execution on an industrial controller, causes the industrial controller to monitor and control an industrial automation system in accordance with the industrial control code; and a generative artificial intelligence (AI) component configured to, in response to determining, based on analysis of the natural language query, that additional information will yield a response to the natural language query having a probability of satisfying the natural language query that exceeds a threshold, generate a first natural language response that prompts for the additional information and render the first natural language response via the user interface component, and in response to receipt, via the user interface component, of a natural language answer containing the additional information, generate a second natural language response to the natural language query based on analysis of the industrial control code, the natural language answer, industry knowledge encoded in the one or more custom models, and a response prompted from a generative AI model, wherein the response prompted from the generative AI model comprising information used by the generative AI component to formulate the second natural language response, wherein the user interface component is configured to render the second natural language response on the IDE interface.
Claim 19A non-transitory computer-readable medium having stored thereon instructions that, in response to execution, cause an industrial integrated development environment (IDE) system comprising a processor to perform operations, the operations comprising:receiving a natural language prompt requesting control code for an industrial system project being developed, wherein the natural language prompt describes one or more requirements of the control code; performing, using a generative artificial intelligence (AI) model, contextual analysis on the industrial system project to determine at least one of a type of industrial application or an industrial vertical for which the industrial system project is being developed; generating, using the generative AI model, control code that satisfies the one or more requirements based on analysis of the prompt and a result of the contextual analysis; and integrating the control code into the industrial system project.
Claim 1A system, comprising: a memory that stores executable components and one or more custom models; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to receive, via an integrated development environment (IDE) interface, a natural language query directed to industrial control code that, in response to execution on an industrial controller, causes the industrial controller to monitor and control an industrial automation system in accordance with the industrial control code; and a generative artificial intelligence (AI) component configured to, in response to determining, based on analysis of the natural language query, that additional information will yield a response to the natural language query having a probability of satisfying the natural language query that exceeds a threshold, generate a first natural language response that prompts for the additional information and render the first natural language response via the user interface component, and in response to receipt, via the user interface component, of a natural language answer containing the additional information, generate a second natural language response to the natural language query based on analysis of the industrial control code, the natural language answer, industry knowledge encoded in the one or more custom models, and a response prompted from a generative AI model, wherein the response prompted from the generative AI model comprising information used by the generative AI component to formulate the second natural language response, wherein the user interface component is configured to render the second natural language response on the IDE interface.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1 of co-pending application No. 18/607,750. Herein the independent claims are shown mapped to claim 1 of the co-pending application. The dependent claims are ODP in view of dependent claims of claim 1 or in view of the prior art used in the art rejection below associated with that dependent claim.
Instant Application 18/497,191
App. No. 18/607,750
Claim 1A system, comprising: a memory that stores executable components and a generative artificial intelligence (AI) model; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to receive, as natural language input, a prompt comprising a request for control code for an industrial system project in development, wherein the request specifies one or more requirements of the control code; a generative AI component configured to perform contextual analysis on the industrial system project to determine at least one of a type of industrial application or an industrial vertical for which the industrial system project is being developed, and to generate, using the generative AI model, control code inferred to satisfy the one or more requirements based on analysis of the prompt and a result of the contextual analysis; and a project generation component configured to integrate the control code into the industrial system project.
Claim 1A system, comprising: a memory that stores executable components and one or more custom models; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to receive, via an integrated development environment (IDE) interface, a natural language request to generate new control code for inclusion in an industrial control program being developed using the IDE interface as part of an industrial control project, wherein the natural language request describes one or more requirements of the new control code; a generative artificial intelligence (AI) component configured to, in response to receipt of the natural language request, generate control code inferred to satisfy the one or more requirements based on based on analysis of the natural language request, industry-specific information encoded in the one or more custom models, and a response prompted from a generative AI model; and a project generation component is further configured to integrate the control code into the industrial control program and to generate an executable control program file that, in response to execution on an industrial controller, causes the industrial controller to monitor and control an industrial automation system in accordance with the industrial control program.
Claim 11A method, comprising: receiving, as natural language input by an industrial integrated development environment (IDE) system comprising a processor, a prompt comprising a request for control code for an industrial system project being developed, wherein the request specifies one or more requirements of the control code; performing, by the industrial IDE system using a generative artificial intelligence (AI) model, contextual analysis on the industrial system project to determine at least one of a type of industrial application or an industrial vertical for which the industrial system project is being developed; generating, by the industrial IDE system using the generative AI model, control code determined to satisfy the one or more requirements based on analysis of the prompt and a result of the contextual analysis; and integrating, by the industrial IDE system, the control code into the industrial system project.
Claim 1A system, comprising: a memory that stores executable components and one or more custom models; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to receive, via an integrated development environment (IDE) interface, a natural language request to generate new control code for inclusion in an industrial control program being developed using the IDE interface as part of an industrial control project, wherein the natural language request describes one or more requirements of the new control code; a generative artificial intelligence (AI) component configured to, in response to receipt of the natural language request, generate control code inferred to satisfy the one or more requirements based on based on analysis of the natural language request, industry-specific information encoded in the one or more custom models, and a response prompted from a generative AI model; and a project generation component is further configured to integrate the control code into the industrial control program and to generate an executable control program file that, in response to execution on an industrial controller, causes the industrial controller to monitor and control an industrial automation system in accordance with the industrial control program.
Claim 19A non-transitory computer-readable medium having stored thereon instructions that, in response to execution, cause an industrial integrated development environment (IDE) system comprising a processor to perform operations, the operations comprising:receiving a natural language prompt requesting control code for an industrial system project being developed, wherein the natural language prompt describes one or more requirements of the control code; performing, using a generative artificial intelligence (AI) model, contextual analysis on the industrial system project to determine at least one of a type of industrial application or an industrial vertical for which the industrial system project is being developed; generating, using the generative AI model, control code that satisfies the one or more requirements based on analysis of the prompt and a result of the contextual analysis; and integrating the control code into the industrial system project.
Claim 1A system, comprising: a memory that stores executable components and one or more custom models; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: a user interface component configured to receive, via an integrated development environment (IDE) interface, a natural language request to generate new control code for inclusion in an industrial control program being developed using the IDE interface as part of an industrial control project, wherein the natural language request describes one or more requirements of the new control code; a generative artificial intelligence (AI) component configured to, in response to receipt of the natural language request, generate control code inferred to satisfy the one or more requirements based on based on analysis of the natural language request, industry-specific information encoded in the one or more custom models, and a response prompted from a generative AI model; and a project generation component is further configured to integrate the control code into the industrial control program and to generate an executable control program file that, in response to execution on an industrial controller, causes the industrial controller to monitor and control an industrial automation system in accordance with the industrial control program.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention recites a judicial exception, is directed to that judicial exception, an abstract idea, as it has not been integrated into practical application and the claims further do not recite significantly more than the judicial exception. Examiner has evaluated the claims under the framework provided in the 2019 Patent Eligibility Guidance published in the Federal Register 01/07/2019 and has provided such analysis below.
Step 1: Claims 1-10 are directed to systems and fall within the statutory category of machines; Claims 11-18 are directed to methods and fall within the statutory category of processes; and Claims 19-20 are directed to media and fall withing the statutory category of manufactures. Therefore, “Are the claims to a process, machine, manufacture or composition of matter?” Yes.
In order to evaluate the Step 2A inquiry “Is the claim directed to a law of nature, a natural phenomenon or an abstract idea?” we must determine, at Step 2A Prong 1, whether the claim recites a law of nature, a natural phenomenon or an abstract idea and further whether the claim recites additional elements that integrate the judicial exception into a practical application.
Step 2A Prong 1:
Claims 1, 11 and 19 as drafted, recite a process that, under its broadest reasonable interpretation, covers steps that could reasonably be performed in the mind, including with the aid of pen and paper, but for the recitation of generic computer components. That is, the limitations: a) “” – Mental processes (see MPEP 2106.04(a)(2), III), this limitation can be reasonable performed by a human using pen and paper, wherein a person can have a prompt in natural language comprising a request.
b) “” – Mental processes (see MPEP 2106.04(a)(2), III), this limitation can be reasonable performed by a human mind, where a person may analyze the provided prompt to determine any adjustment/modification of code/data. c) “ - Mental processes (see MPEP 2106.04(a)(2), III), this limitation can be reasonable performed by a human mind, wherein a person using pen and paper can add/integrate code modification into a system project. That is, nothing in the claim elements precludes the step from practically being performed in the mind or with a pen and paper, (i.e., “receive”, “analyze” and, “integrate”) can be performed in the human mind through observation, evaluation, judgment, opinion. Thus, these limitations fall within the “Mental Processes” grouping of abstract ideas.
Therefore, Yes, claims 1, 11 and 19 recite judicial exceptions.
The claims have been identified to recite judicial exceptions, Step 2A Prong 2 will evaluate whether the claims are directed to the judicial exception.
Step 2A Prong 2:
This judicial exception is not integrated into a practical application. The claims recite the following additional elements: “a system”, “a memory”, “a processor”, “a user interface component”, “a generative AI component”, “a project generation component”, “an industrial integrated development environment (IDE)” and “A non-transitory computer-readable medium”. The additional elements are merely instructions to implement an abstract idea on a computer, or merely using a generic computer or computer components as a tool to perform the abstract idea (see MPEP 2106.05(f)). Accordingly, the additional elements recited in the claims do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea, thus failing to integrate the abstract idea into a practical application. These elements in the claim call/use an Artificial Intelligence via a model/agent/module/component: a) “a generative artificial intelligence (AI) model”.
b) “a generative AI component”. However as drafted, these elements are considered a field of use and technological environment (see MPEP 2106.05(h). “As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.”
Therefore, “Do the claims recite additional elements that integrate the judicial exception into a practical application? No, these additional elements do not integrate the abstract idea into a practical application and they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
After having evaluating the inquires set forth in Steps 2A Prong 1 and 2, it has been concluded that claims 1, 11 and 19 not only recites a judicial exception but that the claim is directed to the judicial exception as the judicial exception has not been integrated into practical application.
Step 2B:
As discussed above with respect to integration of the abstract idea into a practical application, the additional elements “a system”, “a memory”, “a processor”, “a user interface component”, “a generative AI component”, “a project generation component”, “an industrial integrated development environment (IDE)” and “A non-transitory computer-readable medium” are generic computer components used as tools to perform the abstract idea. Accordingly, the additional elements recited in the claims cannot provide an inventive concept. In addition, after further evaluation the claim as a whole doesn’t improve any function of a computer or to any other technology or technical field. Thus, the claims are not patent eligible.
Therefore, “Do the claims recite additional elements that amount to significantly more than the judicial exception? No, these additional elements, alone or in combination, do not amount to significantly more than the judicial exception.
Having concluded analysis within the provided framework, Claims 1, 11 and 19 do not recite patent eligible subject matter under 35 U.S.C. § 101. With regards to claim 2 (and similar for claims 12 and 20), it recites “wherein the generative AI component is configured to generate the control code further based on content of one or more libraries, the one or more libraries comprising at least one of a program instruction library, a library of control code samples, a library of user-defined data types, a library of industrial device product manuals, a help file library, a library of customer-specific training manuals, a library of industrial standard definitions, or a library of customer-specific plant standards.” as drafted, the claim recites mere instructions to apply an exception (See MPEP 2106.05(f)). Moreover, claim 2 does not recite any other additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 2 also fails both Step 2A prong 2, thus the claim is directed to the judicial exception as it has not been integrated into practical application, and fails Step 2B as not amounting to significantly more Therefore, Claim 2 does not recite patent eligible subject matter under 35 U.S.C. § 101. With regards to claim 3 (and similar for claim 13), it recites “wherein the prompt specifies at least one of a control function to be performed by the control code, a type of equipment to be controlled by the control code, or a format for the control code.” as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind and/or using pen and paper. For example, a person can read/evaluate the prompt having specific instructions or commands. Moreover, claim 3 does not recite any other additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 3 also fails both Step 2A prong 2, thus the claim is directed to the judicial exception as it has not been integrated into practical application, and fails Step 2B as not amounting to significantly more Therefore, Claim 3 does not recite patent eligible subject matter under 35 U.S.C. § 101. With regards to claim 4 (and similar for claim 14), it recites “wherein the generative AI component is further configured to generate, using the generative AI model, natural language implementation details relating to the control code based on the analysis of the prompt and the result of the contextual analysis, and the user interface component is configured to render the control code and the natural language implementation details.” as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind and/or using pen and paper. For example, a person can read/evaluate/analyze the prompt to determine a response. Moreover, claim 4 does not recite any other additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 4 also fails both Step 2A prong 2, thus the claim is directed to the judicial exception as it has not been integrated into practical application, and fails Step 2B as not amounting to significantly more Therefore, Claim 4 does not recite patent eligible subject matter under 35 U.S.C. § 101. With regards to claim 5 (and similar for claim 15), it recites “wherein the generative AI component is configured to generate the control code to align with at least one of an industrial standard or a customer-specific standard.” as drafted, the claim is mere instructions to apply an exception (See MPEP 2106.05(f)). Moreover, claim 5 does not recite any other additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 5 also fails both Step 2A prong 2, thus the claim is directed to the judicial exception as it has not been integrated into practical application, and fails Step 2B as not amounting to significantly more Therefore, Claim 5 does not recite patent eligible subject matter under 35 U.S.C. § 101.
With regards to claim 6 (and similar for claim 16), it recites “wherein the industrial vertical is at least one of food and beverage, pharmaceuticals, automotive, textiles, mining, aerospace, marine, or die casting.” as drafted, the claim recites a field of use (See MPEP 2106.05(h)). Moreover, claim 6 does not recite any other additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 6 also fails both Step 2A prong 2, thus the claim is directed to the judicial exception as it has not been integrated into practical application, and fails Step 2B as not amounting to significantly more Therefore, Claim 6 does not recite patent eligible subject matter under 35 U.S.C. § 101.
With regards to claim 7 (and similar for claim 17), it recites “wherein the prompt is a first prompt, the user interface component is further configured to receive, as another natural language input, a second prompt requesting an edit to the control code, and the generative AI component is configured to modify, using the generative AI model, the control code in accordance with the edit.” as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind and/or using pen and paper. For example, a person analyze/read/receive a prompt with instructions to identify further interactions to generate proper response through another prompt. Moreover, claim 7 does not recite any other additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 7 also fails both Step 2A prong 2, thus the claim is directed to the judicial exception as it has not been integrated into practical application, and fails Step 2B as not amounting to significantly more Therefore, Claim 7 does not recite patent eligible subject matter under 35 U.S.C. § 101.
With regards to claim 8 (and similar for claim 18), it recites “wherein the prompt is a first prompt, the user interface component is further configured to receive, as another natural language input, a second prompt asking a question about previously written control code included as part of the industrial system project, and the generative AI component is further configured to generate, using the generative AI model, an answer to the question based on analysis of the previously written control code and the result of the contextual analysis.” as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind and/or using pen and paper. For example, a person analyze/read/receive a prompt with instructions to identify further interactions to generate proper response through another prompt. Moreover, claim 8 does not recite any other additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 8 also fails both Step 2A prong 2, thus the claim is directed to the judicial exception as it has not been integrated into practical application, and fails Step 2B as not amounting to significantly more Therefore, Claim 8 does not recite patent eligible subject matter under 35 U.S.C. § 101.
With regards to claim 9, it recites “wherein the prompt is a first prompt, the user interface component is further configured to receive, as another natural language input, a second prompt requesting a proposed modification to the industrial system project that will address a performance issue specified in the second prompt, the generative AI component is further configured to generate, using the generative AI model, one or more proposed modifications to the industrial system project designed to address the performance issue based on analysis of the industrial system project and the result of the contextual analysis, and the user interface component is configured to render the one or more proposed modifications as natural language descriptions.” as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind and/or using pen and paper. For example, a person analyze/read/receive a prompt with instructions to identify further interactions to generate proper response through another prompt. Moreover, claim 9 does not recite any other additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claim 9 also fails both Step 2A prong 2, thus the claim is directed to the judicial exception as it has not been integrated into practical application, and fails Step 2B as not amounting to significantly more Therefore, Claim 9 does not recite patent eligible subject matter under 35 U.S.C. § 101.
Therefore, Claims 1-20 do not recite patent eligible subject matter under 35 U.S.C. § 101.
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.
The factual inquiries 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 1-3, 5-6,10-13, 15-16 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Stump et al. (US Pub. No. 2021/0096827 – hereinafter Stump – IDS 06/06/225) in view of Heiko Koziolek et al. (“ChatGPT for PLC/DCS Control Logic Generation” – hereinafter Koziolek – IDS 06/06/2025).
With respect to claim 1, Stump teaches a system (See figures 1-11 and 15-16), comprising: a memory that stores executable components (See figure 15, system memory 1506) and a generative artificial intelligence (AI) model (See abstract and paragraph [0042], “The industrial IDE can apply analytics (e.g., artificial intelligence, machine learning, etc.) to project data submitted by developers across multiple industrial enterprises to identify commonly used control code, visualizations, device configurations, or control system architectures that are frequently used for a given industrial function, machine, or application.”) and a processor (See figure 15, processing unit 1504), operatively coupled to the memory (See figure 15, bus 1508), that executes the executable components (See figures 2, 5, 7-10, IDE system 202 with plurality of components, i.e. executable components), the executable components comprising: a project generation component configured to integrate the control code into the industrial system project (See figures 2, 5, 7-10, IDE system 202 and paragraphs [0003]-[0005], [0039], [0055], [0085], development integration with industrial system/project). Stump is silent to disclose, however in an analogous art, Koziolek teaches: a user interface component configured to receive, as natural language input, a prompt comprising a request for control code for an industrial system project in development, wherein the request specifies one or more requirements of the control code (See abstract, “Large language models (LLMs) providing generative AI have become popular to support software engineers in creating, summarizing, optimizing, and documenting source code. It is still unknown how LLMs can support control engineers using typical control programming languages in programming tasks. Researchers have explored GitHub CoPilot or DeepMind AlphaCode for source code generation but did not yet tackle control logic programming. A key contribution of this paper is an exploratory study, for which we created 100 LLM prompts in 10 representative categories to analyze control logic generation for of PLCs and DCS from natural language. We tested the prompts by generating answers with ChatGPT using the GPT-4 LLM. It generated syntactically correct IEC 61131-3 Structured Text code in many cases and demonstrated useful reasoning skills that could boost control engineer productivity. Our prompt collection is the basis for a more formal LLM benchmark to test and compare such models for control logic generation.”. Furthermore, see “I. INTRODUCTION” on page 1, right-hand column, 2nd paragraph, “A key contribution of this paper is a collection of 100 prompts that can be used to test an LLMs’ ability to generate correct and useful control logic for industrial automation. These prompts are the result of an exploratory study. The prompt collection is i) comprehensive and systematically structured, covering different aspects of control engineering, ii) independent of any particular LLM, and iii) publicly available for independent testing and refinement by other researchers. The prompt collection is a pre-cursor for a more formal LLM benchmark for quality assessment and comparison of future LLMs specifically for control logic generation.”. Examiner notes: using natural language prompts to control/generate logic for industrial automation). a generative AI component configured to perform contextual analysis on the industrial system project to determine at least one of a type of industrial application or an industrial vertical for which the industrial system project is being developed, and to generate, using the generative AI model, control code inferred to satisfy the one or more requirements based on analysis of the prompt and a result of the contextual analysis (See “I. INTRODUCTION” on page 1, right-hand column, 3rd paragraph, “we have fed the prompts to OpenAI’s popular ChatGPT with the GPT-4 LLM and analyzed the generated answers. We found that ChatGPT can often generate sophisticated, syntactically correct IEC 61131-3 code given natural language prompts. In addition, we perceived interesting reasoning skills and a vast amount of domain knowledge retrievable from GPT-4.”. Also, see page 4, right column “PLC Programming Tasks” for a type of industrial application, e.g., “TAFFIC CONTROL” or “ELEVATOR CONTROL” ). Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify Stump’s teaching, which uses an industrial integrated development environment (IDE) including a training component that improves the IDE's automated design tools over time based on analysis of aggregated project data submitted by developers over time, by receiving, as natural language input, a prompt comprising a request for control code for an industrial system project in development, performing contextual analysis on the industrial system project to determine a type of industrial application and to generate control code as suggested by Koziolek, as Koziolek would provide a mechanism to analyze control logic generation for of PLCs and DCS from natural language (see abstract).
With respect to claim 2, Stump teaches further based on content of one or more libraries, the one or more libraries comprising at least one of a program instruction library, a library of control code samples, a library of user-defined data types, a library of industrial device product manuals, a help file library, a library of customer-specific training manuals, a library of industrial standard definitions, or a library of customer-specific plant standards (See paragraph [0041], “Embodiments of the industrial IDE can include a library of modular code and visualizations that are specific to industry verticals and common industrial applications within those verticals. These code and visualization modules can simplify development and shorten the development cycle, while also supporting consistency and reuse across an industrial enterprise.”. See paragraph [0055], “These automation objects 222 provide a common data structure across the IDE system 202 and can be stored in an object library (e.g., part of memory 220) for reuse. The object library can store predefined automation objects 222 representing various classifications of real-world industrial assets 402, including but not limited to pumps, tanks, values, motors, motor drives (e.g., variable frequency drives), industrial robots, actuators (e.g., pneumatic or hydraulic actuators), or other such assets. Automation objects 222 can represent elements at substantially any level of an industrial enterprise, including individual devices, machines made up of many industrial devices and components (some of which may be associated with their own automation objects 222), and entire production lines or process control systems.”. See paragraph [0065], “the IDE system 202 can maintain a library of guardrail templates 506 for different internal and external standards and certifications, including customized user-specific guardrail templates 506. These guardrail templates 506 can be classified according to industrial vertical, type of industrial application, plant facility (in the case of custom in-house guardrail templates 506) or other such categories. During development, project generation component 206 can select and apply a subset of guardrail templates 506 determined to be relevant to the project currently being developed, based on a determination of such aspects as the industrial vertical to which the project relates, the type of industrial application being programmed (e.g., flow control, web tension control, a certain batch process, etc.), or other such aspects”).
Stump is silent to disclose, however in an analogous art, Koziolek teaches wherein the generative AI component is configured to generate the control code (See “I. INTRODUCTION” on page 1, right-hand column, 3rd paragraph, “we have fed the prompts to OpenAI’s popular ChatGPT with the GPT-4 LLM and analyzed the generated answers. We found that ChatGPT can often generate sophisticated, syntactically correct IEC 61131-3 code given natural language prompts. In addition, we perceived interesting reasoning skills and a vast amount of domain knowledge retrievable from GPT-4.”). Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify Stump’s teaching, which uses an industrial integrated development environment (IDE) including a training component that improves the IDE's automated design tools over time based on analysis of aggregated project data submitted by developers over time, by generating the control code using a library as suggested by Koziolek, as Koziolek would provide a mechanism to analyze control logic generation for of PLCs and DCS from natural language (see abstract). With respect to claim 3, Stump is silent to disclose, however in an analogous art, Koziolek teaches wherein the prompt specifies at least one of a control function to be performed by the control code, a type of equipment to be controlled by the control code, or a format for the control code (See page 2, right-hand column, 1st paragraph, “we decided to create a comprehensive collection of 100 prompts in 10 different categories that cover multiple aspects of control logic engineering (e.g., PLC programming tasks, sequential control logic, or interlocks.)”. See page 2, right-hand column, 2nd paragraph, “we entered the generated code into a PLC programming environment and checked successful compilation.”. Furthermore, see “IV. Prompt Collection” on pages 3-6, table 1 and figures 1-5, which discloses type of prompts (e.g., functions/tasks). Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify Stump’s teaching, which uses an industrial integrated development environment (IDE) including a training component that improves the IDE's automated design tools over time based on analysis of aggregated project data submitted by developers over time, by specifying using a prompt a control function to be performed by the control code, a type of equipment to be controlled by the control code, or a format for the control code as suggested by Koziolek, as Koziolek would provide a mechanism for analyze control logic generation for of PLCs and DCS from natural language (see abstract). With respect to claim 5, Stump is silent to disclose, however in an analogous art, Koziolek teaches wherein the generative AI component is configured to generate the control code to align with at least one of an industrial standard or a customer-specific standard (See at least figures 1-4). Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify Stump’s teaching, which uses an industrial integrated development environment (IDE) including a training component that improves the IDE's automated design tools over time based on analysis of aggregated project data submitted by developers over time, by generating control code to align an industrial standard or a customer-specific standard as suggested by Koziolek, as Koziolek would provide a mechanism to analyze control logic generation for of PLCs and DCS from natural language (see abstract). With respect to claim 6, Stump teaches wherein the industrial vertical is at least one of food and beverage, pharmaceuticals, automotive, textiles, mining, aerospace, marine, or die casting (See paragraph [0059], “These visualizations 510 can be classified according to industry or industrial vertical (e.g., automotive, food and drug, oil and gas, pharmaceutical, etc.), type of industrial asset (e.g., a type of machine or industrial device), a type of industrial application (e.g., batch processing, flow control, web tension control, sheet metal stamping, water treatment, etc.), or other such categories.”). With respect to claim 10, Stump teaches wherein the user interface component is configured to render the control code in both a text format and a graphical format (See paragraphs [0030], [0033], [0036], [0057], [0064], [0096] and figure 5, “Example display screens can visualize present states of industrial systems or their associated devices using graphical representations of the processes that display metered or calculated values, employ color or position animations based on state, render alarm notifications, or employ other such techniques for presenting relevant data to the operator. Data presented in this manner is read from industrial controllers 118 by HMIs 114 and presented on one or more of the display screens according to display formats chosen by the HMI developer.”). With respect to claims 11-13 and 15-16, the claims are directed to a method that corresponds to the system recited in claims 1-3 and 5-6, respectively (see the rejection of claims 1-3 and 5-6 above). With respect to claims 19-20, the claims are directed to a non-transitory computer-readable medium that corresponds to the system recited in claims 1-2, respectively (see the rejection of claims 1-2 above, wherein Stump also teaches such medium in paragraph [0051]).
Claims 4 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Stump et al. (US Pub. No. 2021/0096827 – hereinafter Stump – IDS 06/06/225) in view of Heiko Koziolek et al. (“ChatGPT for PLC/DCS Control Logic Generation” – hereinafter Koziolek – IDS 06/06/2025) and further in view of Rieken et al. (US Pub. No. 2025/0117195 – hereinafter Rieken). With respect to claim 4, Stump in view of Koziolek is silent to disclose, however in an analogous art, Rieken teaches wherein the generative AI component is further configured to generate, using the generative AI model, natural language implementation details relating to the control code based on the analysis of the prompt and the result of the contextual analysis, and the user interface component is configured to render the control code and the natural language implementation details (See figures 5-6 (and related text) and paragraph [0069], AI Prompts 540, recommendation logic 520, recommendation 574, code modification AI prompt 560, text field 606 receives the AI prompt recommendation/implementation). Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify the combination of Stump and Koziolek, by generating natural language implementation details relating to the control code based on the analysis of the prompt and the result of the contextual analysis, and the user interface component is configured to render the control code and the natural language implementation details as suggested by Rieken, as Rieken would provide a mechanism to use artificial intelligence (AI) to modify code that is being developed in context of a developer tool so that the modified code can be suggested to a developer of the code in the context of the developer tool (see paragraph [0002]).
With respect to claim 14, the claim is directed to a method that corresponds to the system recited in claim 4, respectively (see the rejection of claim 4 above).
Claims 7-8 and 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over Stump et al. (US Pub. No. 2021/0096827 – hereinafter Stump – IDS 06/06/225) in view of Heiko Koziolek et al. (“ChatGPT for PLC/DCS Control Logic Generation” – hereinafter Koziolek – IDS 06/06/2025) and further in view of Schaefer et al. (US Pub. No. 2024/0311582 – hereinafter Schaefer). With respect to claim 7, Koziolek teaches wherein the prompt is a first prompt (See at least the abstract, first prompt). Stump in view of Koziolek is silent to disclose, however in an analogous art, Schaefer teaches the user interface component is further configured to receive, as another natural language input, a second prompt requesting an edit to the control code, and the generative AI component is configured to modify, using the generative AI model, the control code in accordance with the edit (See figures 2-3 (and related text), plurality of prompts with request and edits of code (i.e., control code). Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify the combination of Stump and Koziolek, by receiving, as another natural language input, a second prompt requesting an edit to the control code, and the generative AI component is configured to modify, using the generative AI model, the control code in accordance with the edit as suggested by Schaefer, as Schaefer would provide a mechanism to perform test generation in a series of steps, where in each step, the large language model performs a specific task given a prompt (see paragraph [0006]). With respect to claim 8, Koziolek teaches wherein the prompt is a first prompt (See at least the abstract, first prompt). Koziolek is silent to disclose, however in an analogous art, Stump teaches industrial system project (See figures 2, 5, 7-10, IDE system 202 and paragraphs [0003]-[0005], [0039], [0055], [0085], development integration with industrial system/project). Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify Koziolek’s teaching which analyze control logic generation for of PLCs and DCS from natural language, by interacting with an industrial system project as suggested by Stump, as Stump would provide a mechanism to automatically add suitable control code, visualizations, or configuration data to new control projects being developed based on an inference of the developer's design goals and knowledge of how these goals have been implemented by other developers (see abstract). Stump in view of Koziolek is silent to disclose, however in an analogous art, Schaefer teaches the user interface component is further configured to receive, as another natural language input, a second prompt asking a question about previously written control code (See figures 2-3 (and related text), plurality of prompts with questions and answers). Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify the combination of Stump and Koziolek, by receiving, as another natural language input, a second prompt asking a question about previously written control code and generating, using the generative AI model, an answer to the question based on analysis of the previously written control code and the result of the contextual analysis as suggested by Schaefer, as Schaefer would provide a mechanism to perform test generation in a series of steps, where in each step, the large language model performs a specific task given a prompt (see paragraph [0006]).
With respect to claims 17-18, the claims are directed to a method that corresponds to the system recited in claims 7-8, respectively (see the rejection of claims 7-8 above).
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Stump et al. (US Pub. No. 2021/0096827 – hereinafter Stump – IDS 06/06/225) in view of Heiko Koziolek et al. (“ChatGPT for PLC/DCS Control Logic Generation” – hereinafter Koziolek – IDS 06/06/2025) and further in view of Zhang et al. (US Pub. No. 2024/0256423 – hereinafter Zhang).
With respect to claim 9, Koziolek teaches wherein the prompt is a first prompt (See at least the abstract, first prompt). Koziolek is silent to disclose, however in an analogous art, Stump teaches industrial system project (See figures 2, 5, 7-10, IDE system 202 and paragraphs [0003]-[0005], [0039], [0055], [0085], development integration with industrial system/project). Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify Koziolek’s teaching which analyze control logic generation for of PLCs and DCS from natural language, by interacting with an industrial system project as suggested by Stump, as Stump would provide a mechanism to automatically add suitable control code, visualizations, or configuration data to new control projects being developed based on an inference of the developer's design goals and knowledge of how these goals have been implemented by other developers (see abstract). Stump in view of Koziolek is silent to disclose, however in an analogous art, Zhang teaches the user interface component is further configured to receive, as another natural language input, a second prompt requesting a proposed modification (See abstract, paragraphs [0042], [0045]-[0046], [0055], [0064] and figures 3-7 (and related text), “In some embodiments which include the semantic phase code transformer, the semantic prompt dataset 910 includes a task description 706 in a natural language.”, “In some embodiments which include the semantic phase code transformer, the second version 212 of the source code in which the semantic error has been mitigated 204 has improved performance over the syntactically correct version of the source code which contains a semantic error, the improved performance measured with respect to at least one of the following performance metrics 314: execution time, volatile memory usage, nonvolatile memory usage, bandwidth usage, or electric power consumption.” Examiner notes: multimodal prompt for enhanced performance in code). Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify the combination of Stump and Koziolek, by receiving a second prompt requesting a proposed modification that will address a performance issue specified in the second prompt and generating, using the generative AI model, one or more proposed modifications designed to address the performance issue and rendering proposed modifications as natural language descriptions as suggested by Zhang, as Zhang would provide a mechanism to generate prompts and submit them in queries to a language model trained on code to perform automated program repair. (see abstract).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Canedo et al. (US Pub. No. 2022/0276628) discloses that applications of artificial intelligence (AI) in industrial automation have focused mainly on the runtime phase due to the availability of large volumes of data from sensors and introduces methods, systems, and apparatus that can use machine learning or artificial intelligence (AI) to complete automation engineering tasks. (see abstract).
Tomonaga et al. (US Pub. No. 2022/0198113) discloses a design support device including an operation reception unit that receives an operation from a user, a program creation unit that creates a ladder program in accordance with the operation received by the operation reception unit, and a circuit block extraction unit that extracts a circuit block from the ladder program when the circuit block is formed and a predetermined condition is satisfied. The circuit block is formed by detecting that one end of a circuit including a plurality of program elements is connected to one of two power rails included in the ladder program and that another end of the circuit is connected to another one of the two power rails. Further, there is a circuit block memory that stores configuration information of the circuit block extracted by the circuit block extraction unit. There is also a notification unit. (see abstract). Beiqi Zhang et al. (“Practices and Challenges of Using GitHub Copilot: An Empirical Study”) searched and manually collected 169 SO posts and 655 GitHub discussions related to the usage of Copilot. Zhang identified the programming languages, IDEs, technologies used with Copilot, functions implemented, benefits, limitations, and challenges when using Copilot. (see abstract).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANIBAL RIVERACRUZ whose telephone number is (571)270-1200. The examiner can normally be reached Monday-Friday 9:30 AM-6:00 PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Hyung S Sough can be reached at 5712726799. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/ANIBAL RIVERACRUZ/Primary Examiner, Art Unit 2192