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 .
This Action is non-final and is in response to the claims filed October 8, 2024. Claims 1-18 are currently pending, of which claims 1-18 are currently rejected.
Examiner’s Note
The prior art rejections below cite particular paragraphs, columns, and/or line numbers in the references 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.
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 (i.e., changing from AIA to pre-AIA ) 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.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kannan et al. (U.S. Publication No. 2018/0129484; hereinafter, “Kannan”) and further in view of Nelson et al. (U.S. Publication No. 2019/0354358; hereinafter “Nelson”).
As per claim 1, Kannan teaches a method for facilitating creation of and modification of AI (artificial intelligence) agents, the method comprising:
generating an interface with a listing of resources that can be utilized as part of an AI agent knowledge base while processing instructions (See Kannan Figs. 2-5 and paras. [0027] and [0035-36]: domain-specific functions that can be designed as a dialog flow for an AI agent, where “the selection of response strings and/or presentation mode for such responses may be based upon the digital context chosen by the developer for the agent definition”);
presenting an instruction field for receiving instructions corresponding to actions to be performed by the AI agent (See Kannan Figs. 2-5 and paras. [0005] and [0040-44]: editing user interface that receives various flow instructions); and
detecting and parsing user input entered into the instruction field to identify the actions that the AI agent is instructed to perform while utilizing information included in the AI agent knowledge base (See Kannan Figs. 2-5 and paras. [0005], [0037], and [0040-44]: editing user interface that receives various flow instructions. This includes the specification of a domain, one or more intents (actions), etc. “The agent generator 128 may also acquire the schema template 132 and generate an updated schema 104 based on, for example, user input received via the U/I design module 130. Response/flow input from the response/flow design module 134, as well as localization input from the localization engine 138, may be used by the agent generator 128 to further update the schema template 132 and generate the updated schema 104”).
However, while Kannan explicitly teaches creating and generating AI event triggers and user triggers, Kannan does not explicitly teach selectable resources to add to the AI knowledge base.
Nelson teaches detecting user input selecting one or more of the resources to be included in the AI agent knowledge base and adding the selected one or more resources to the AI agent knowledge base (See Nelson Figs. 5D and 6C and paras. [0137-138] and [0141]: user can add new skills to the cognitive agent system, with various input fields and functions that can be selected).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine, with a reasonable expectation of success, the development tool and toolbox of Kannan with the new skills interface of Nelson. One would have been motivated to combine these references because both references disclose designing agentic assistant workflows and actions. Nelson further enhances the interface tools of Kannan by ensuring a smooth cross-platform unified service that allows for multiple complex interactions while constantly allowing the user to experiment and grow the assistant to suit their needs (See Nelson para. [0007]).
As per claim 2, Kannan/Nelson further teaches the method of claim 1, wherein the method further includes: presenting an interface control for associating the actions with a skill for the AI agent (See Kannan Figs. 2-6B and para. [0040]: toolbox with dialog tools that can be incorporated into the dialog flow).
However, while Kannan teaches a variety of options to incorporate into the dialog flow and various event triggers, as well as the option to edit events (See Kannan para. [0041]), Kannan does not explicitly identify new actions to be associated with a skill.
Nelson teaches presenting a listing of the actions within the user interface with a selectable object that, when selected, prompts the user to identify a new action to be associated with the skill and to be performed by the AI agent (See Nelson Figs. 5D and 6C and paras. [0137-141]: user can add or edit skills and add functions/actions associated with those skills and save them to the cognitive agent system).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Kannan with the teachings of Nelson for at least the same reasons as discussed above in claim 1.
As per claim 3, Kannan/Nelson further teaches the method of claim 1, wherein the method further includes: detecting new user input entered in the instruction field and parsing the new user input to identify a modified set of actions that the AI agent is instructed to perform based on the user input (See Kannan Figs. 2-5 and paras. [0041] and [0055]: modifying the dialog flow).
As per claim 4, Kannan/Nelson teaches the method of claim 1. However, while Kannan explicitly teaches creating and generating AI event triggers and user triggers, Kannan does not explicitly teach selectable new skill options.
Nelson teaches wherein the method further includes: presenting a selectable new skill control that, when selected, prompts the user to identify a new skill for the AI agent (See Nelson Figs. 5D and 6C and paras. [0137-141]: user can trigger a new skill window that can eventually add new skill details and save the skill to the cognitive agent system).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Kannan with the teachings of Nelson for at least the same reasons as discussed above in claim 1.
As per claim 5, Kannan/Nelson teaches the method of claim 4. However, while Kannan explicitly teaches creating and generating AI event triggers and user triggers, Kannan does not explicitly teach selectable new skill control.
Nelson teaches wherein the method further includes: associating a new skill for the AI agent in response to detecting new user input directed at the new skill control (See Nelson Figs. 5D and 6C and paras. [0137-141]: after triggering the new skill window, a user can add and save new skills to the cognitive agent).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Kannan with the teachings of Nelson for at least the same reasons as discussed above in claim 1.
As per claim 6, Kannan/Nelson teaches the method of claim 5. However, while Kannan explicitly teaches creating and generating AI event triggers and user triggers, Kannan does not explicitly teach selectable new skill control.
Nelson teaches wherein the method further includes: associating a new action with the new skill in response to detecting user input selecting a predefined action from the user interface (See Nelson Figs. 5D and 6C and paras. [0137-141]: user can save and add new skills, where a particular function/action is performed under that skill).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Kannan with the teachings of Nelson for at least the same reasons as discussed above in claim 1.
As per claim 7, Kannan/Nelson teaches the method of claim 5. However, while Kannan explicitly teaches creating and generating AI event triggers and user triggers, Kannan does not explicitly teach selectable new skill control.
Nelson teaches wherein the method further includes: presenting the instruction field with a listing of the new skill; and associating a new action with the new skill in response to detecting user input entered in the instruction field that instructs the AI agent to perform the new action with the new skill (See Nelson Figs. 5D and 6C and paras. [0137-141]: user can save and add new skills, where a particular function/action is performed under that skill).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Kannan with the teachings of Nelson for at least the same reasons as discussed above in claim 1.
As per claim 8, Kannan/Nelson further teaches the method of claim 1, wherein the method further includes: presenting a trigger control which, when selected, presents the user with options for setting controls that define when the AI agent will perform the actions (See Kannan Fig. 2 and para. [0041]: “a taskbar 203 that illustrates event triggers and user triggers that a developer may create and/or modify”).
As per claim 9, Kannan/Nelson further teaches the method of claim 1, wherein a system utilizes a machine learning model that is trained to identify actions that are associated with instructions to identify the actions based on the user input entered in the instruction field (See Kannan para. [0058]: “may train a language understanding model to identify user intent and extract corresponding slots 1302, if any, of user input 1301”).
As per claims 10-18, the claims are directed towards a computing system that implements the same features as the method of claims 1-9, respectively, and are therefore rejected for at least the same reasons therein. Furthermore, Kannan teaches a computing system for facilitating creation of and modification of AI (artificial intelligence) agents, the computing system comprising: one or more hardware processors; and one or more storage devices having stored computer-executable instructions which are executable by the one or more hardware processors for causing the computing system to perform a method that includes implementing said method (See Kannan paras. [0066-69]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Nicholas Klicos whose telephone number is (571)270-5889. The examiner can normally be reached Mon-Fri 9:00 AM-5:00 PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Scott Baderman can be reached at (571) 272-3644. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/NICHOLAS KLICOS/Primary Examiner, Art Unit 2118
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