DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1-20 are presented for examination.
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.
As to claims 1-20, the claimed invention is directed to an abstract idea without significantly more. Under the 2019 Patent Eligibility Guidance (PEG), the analysis for independent claim 1 proceeds as follows:
Step
Analysis
1: Statutory category?
Yes. Claim 1 recites a series of steps and, therefore, is a process.
2A - Prong 1: Judicial Exception Recited?
Yes. Claim 1 generally recites receiving a natural language request, decomposing into one or more tasks, generating instructions corresponding to tasks, which are steps, that under BRI, could be performed in the human mind, but for the recitation of generic computer components. That is, other than reciting a computing device, nothing in the claim precludes the determining step from practically being performed in the human mind. Thus, this limitation is considered a mental process.
2A - Prong 2: Integrated into a Practical Application?
No. Claim 1 recites an additional element of a computing device, which executes jobs and/or the job definition in response to an incident. However, this computing device is generic and does not recite an improvement to how computers operate. Therefore, the additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The executing of the computing device is merely a field-of-use limitation, which is insufficient to impose a meaningful limit on the abstract idea.
2B: Claim provides an Inventive Concept?
No. The additional element of a computing device, which executes jobs and/or the job definition in response to an incident, amount to no more than well-understood, routine, and conventional activities previously known in the field. The claim merely implements the abstract idea using a generic computing device to perform basic functions of receiving, processing (decomposing, generating), and executing data. For these reasons, there is no inventive concept in the claim, and thus Claim 1 is ineligible.
As to claims 2-4, they are also ineligible as they relate to an abstract idea without significantly more because they merely add generic computer implementation details such as a language model, data transmission, and input validation/notification to the abstract idea identified in claim 1, without integrating the exception into a practical application or providing significantly more than the well-understood, routine, and conventional activities.
As to claim 5, it is also ineligible as it merely adds generic user interface functions such as displaying and modifying information to the abstract idea identified in claim 1, without integrating the exception into a practical application or providing significantly more than the well-understood, routine, and conventional activities.
As to claim 6, it is also ineligible as it merely adds generic data gathering in the form of receiving the updated instruction from the user, which does not integrate the abstract idea into a practical application or provide significantly more than the well-understood, routine, and conventional activities.
As to claim 7, it is also ineligible as it merely adds the use of a protocol as descriptor to perform a task, which does not integrate the abstract idea into a practical application or provide significantly more than the well-understood, routine, and conventional activities.
As to independent claims 8 and 15, they are rejected for the same reasons as stated in the rejection of claim 1.
As to dependent claims 9-14 and 16-20, they are rejected for the same reasons as stated in the rejections of claims 2-7.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over STEVENS (US 2025/0156303 A1) in view of Xu et al. (hereinafter XU) (US 2025/0086402 A1).
As to claim 1, STEVENS teaches a method, comprising:
receiving a natural language request (receive user input in the form of natural language instructions; Receiver NLP 110) to generate a job definition (natural language instructions describing actions to be performed, etc.), wherein the natural language request includes a natural language description of a job executable by a computing device (receiving written instructions in natural language and translating the written instructions into software actions or machine code) ([0005]; [0081]; Figs. 1, 5, and 22-23);
decomposing the natural language description of the job into one or more tasks, wherein each task of the one or more tasks is a natural language description of a portion of the job (generating a list of each step required to perform the instruction and the translation of natural language steps, which are software actions to be performed) ([0006]; [0118]);
generating the job definition comprising one or more instructions, wherein at least one instruction of the one or more instructions corresponds to a task of the one or more tasks, such that performance of the at least one instruction accomplishes the task (the one or more natural language processing model or neural network processes the written or verbal instruction, generates a list of each step required to perform the instruction, translates instruction steps into executable software actions or machine code; mapping teach element of the instruction to corresponding software actions; commands are executed with diligence, and the system's state is altered in accordance with the user's original directive ) ([0006]; [0121]-[0122]); and
executing, by the computing device, the job definition to perform the job in response to an incident (performing remediation as a response to a cyber remediation request or from a security incident) ([0044]-[0045]; [0250]-[0253]; Fig. 11).
The Examiner notes that STEVENS discloses generating a list of each step required to perform the instruction and the translation of natural language steps, which are software actions to be performed ([0006]; [0118]). Although STEVENS’s teaching is implied, it does not explicitly teach decomposing the natural language description of the job into one or more tasks, wherein each task of the one or more tasks is a natural language description of a portion of the job.
XU explicitly discloses the ability to decompose (Decompose natural language input 420) the natural language input (Natural language input 415) into a set of multiple elements and a set of multiple connectors, wherein the elements could correspond to actions and tasks (Abstract; [0016]; [0036]; [0041]-[0044]; Fig. 4).
It would have been obvious to one of ordinary skill in the art before the effective date of the application to apply the teaching of XU’s decomposing the natural language description of the job into one or more tasks, wherein each task of the one or more tasks is a natural language description of a portion of the job to STEVENS’s natural language processing model. The suggestion/motivation for doing so would have been to provide the predicted result of allowing for process flows to be generated based on natural language input, which may improve flow-generation efficiency as the process flows may be generated more quickly than when the flow generation service relies on user instructions alone. In addition, the techniques described herein may simplify the flow-building experience by enabling interactions between the flow generation service and the LLM, thus making the flow generation service more accessible to non-technical users. This may encourage novice users to generate more complicated, efficient process flows. In some examples, the LLM may enable generative AI-enabled flow creation, which may reduce error rates that may be associated with manually generating process flows (XU – [0018]). Therefore, it would have been obvious to one of ordinary skill in the art to combine the teachings of STEVENS and XU to obtain the broadest reasonable interpretation of claim 1.
As to claim 2, STEVENS teaches wherein the decomposing of the natural language request comprises: transmitting the natural language description (NLP) of the job and training data to a language model (machine learning algorithms adapt and learn from data) ([0006]; [0048]; [0052]; [0081]); and receiving the one or more tasks from the language model ([0006]; [0118]; [0125]).
As to claim 3, STEVENS teaches wherein the generating the job definition comprises (generates a list of each step required to perform the instruction) ([0006]): transmitting the one or more tasks and training data to a language model (machine learning algorithms adapt and learn from data; neural network training data; AI model) ([0052]; [0062]); and receiving, from the language model, the job definition (translates instruction steps into executable software actions or machine code, executes the software actions locally or on a separate node via communications interface, and receives software action result data.) ([0006]; [0121]; [0258]-[0259]).
As to claim 4, STEVENS teaches wherein the natural language request is a first natural language request, the method further comprising: receiving a second natural language request (receiving a written or verbal instruction via embedded prompt or chatbot prompt) ([0006]); determining that the second natural language request is invalid (failure result or Error) ([0279]; [0132]-[0133]; Fig. 6); and responsive to determining that the second natural language request is invalid, notifying a user (feedback mechanism of communicating the outcome of the actions back to the user, detailing not only the success or failure of the task but also providing insights into any challenges encountered and the steps taken during execution; notifying via delivery of action report) ([0130]; [0253]).
As to claim 5, STEVENS teaches the method of claim 1, further comprising: displaying (via user interface 400) the job definition to a user; and modifying the job definition to include an updated instruction (user interface ensures real-time interaction with end-users, allowing them to input instructions and view outputs seamlessly) ([0047]; [0049]; [0204]; [0279]-[0280]; Fig. 18).
As to claim 6, STEVENS teaches the method of claim 5, wherein the modifying the job definition comprises: receiving the updated instruction from the user (user interface ensures real-time interaction with end-users, allowing them to input instructions and view outputs seamlessly) ([0211]; [0115]; [0275]; [0047]; [0049]; [0204]; [0279]-[0280]; Figs. 18-19).
As to claim 7, STEVENS ([0067]; [0109]; [0252]) and XU ([0036]-[0037]; [0043]-[0045]) teach the method of claim 1, wherein a task of the one or more tasks includes a protocol, wherein the protocol describes a mechanism used to perform the task.
As to claim 8, it is rejected for the same reasons as stated in the rejection of claim 1.
As to claim 9, it is rejected for the same reasons as stated in the rejection of claim 2.
As to claim 10, it is rejected for the same reasons as stated in the rejection of claim 3.
As to claim 11, it is rejected for the same reasons as stated in the rejection of claim 4.
As to claim 12, it is rejected for the same reasons as stated in the rejection of claim 5.
As to claim 13, it is rejected for the same reasons as stated in the rejection of claim 6.
As to claim 14, it is rejected for the same reasons as stated in the rejection of claim 7.
As to claim 15, it is rejected for the same reasons as stated in the rejection of claim 1.
As to claim 16, it is rejected for the same reasons as stated in the rejection of claim 2.
As to claim 17, it is rejected for the same reasons as stated in the rejection of claim 3.
As to claim 18, it is rejected for the same reasons as stated in the rejection of claim 4.
As to claim 19, it is rejected for the same reasons as stated in the rejections of claims 5 and 6.
As to claim 20, it is rejected for the same reasons as stated in the rejection of claim 7.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KENNETH TANG whose telephone number is (571)272-3772. The examiner can normally be reached Monday-Friday 7AM-3PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Bradley Teets can be reached at 571-272-3338. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/KENNETH TANG/Primary Examiner, Art Unit 2197