DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
1. Claims 1-20 are presented for examination.
Drawings Objection
2. The drawings are objected to under 37 CFR 1.83(a). The drawings must show every feature of the invention specified in the claims. Therefore, the “generate, based at least on one or more sensory servers in one or more input interaction channels” must be shown or the feature(s) canceled from the claim(s). No new matter should be entered.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
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.
3. Claims 13-15 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.
The statement “wherein the one or more processors are further to one or more corresponding calls” in claims 13-15 renders the claim indefinite because it is not clear what Applicant intended to claim.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
4. Claim(s) 1-5, 7-13, and 15-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Cheng et al., (hereafter, “Cheng”), US 2024/0303473 A1.
Regarding claim 1, Cheng teaches one or more processors comprising processing circuitry to:
generate, based at least on one or more sensory servers in one or more input interaction channels, one or more incoming interaction modeling events representing one or more detected user actions using a standardized schema (i.e., data interface may take a form as an application programming interface (API) installed at the enterprise server…the data interface provides a normalized request/response communication mechanism across different vendors when different LLMs may be called upon by enterprise server, page 2 paragraph [0027] and page 7 paragraph [0064[);
generate, based at least on an interaction manager processing the one or more incoming interaction modeling events, one or more outgoing interaction modeling events specifying one or more responsive agent actions or one or more scene actions associated with an interactive agent using the standardized schema (i.e., Cheng, in Fig. 6 and page 4 paragraph [0057], discloses invoke an LLM generate handler(s) to generate a post message (e.g., API call) for LLM service(s) to generate a response based on the provided prompt. Cheng, in page 3 paragraph [0039], also discloses generate a LLM prompt that instructs a task to be complete); and
based at least on one or more action servers, in one or more output interaction channels mapping the one or more outgoing interaction modeling events from the standardized schema into one or more corresponding calls, generate and output the one or more responsive agent actions or the one or more scene actions (i.e., generate API call for LLM service(s) to generate a response based on the provided prompt and parameter, page 4 paragraph ]0057]).
Regarding claim 2, Cheng teaches the one or more processors of claim 1, wherein the mapping further comprises each action server of a plurality of action servers including the one or more action servers handling a corresponding interaction modality of a plurality of mutually exclusive interaction modalities (i.e., (i.e., interact with different LLMs located on different external servers, page 4 paragraph [0054]).
Regarding claim 3, Cheng teaches the one or more processors of claim 1, wherein processing circuitry is further to provide the one or more incoming interaction modeling events from the one or more sensory servers to the interaction manager via one or more event gateways, and provide the one or more outgoing interaction modeling events from the interaction manager to the one or more action servers via the one or more event gateways (i.e., LLM prompt may be sent out via the AI gateway to one or more IA models, page 3 paragraph [0039]).
Regarding claim 4, Cheng teaches the one or more processors of claim 1, wherein the mapping comprises at least one individual action server of the one or more action servers using one or more action handlers for each agent action supported by the interaction manager in a corresponding interaction modality (i.e., LLM Generate Handlers 612-615, Fig. 6 and page 4 paragraph [0057]).
Regarding claim 5, Cheng teaches the one or more processors of claim 1, wherein the processing circuitry is further to execute the one or more corresponding calls based at least on a first action server of the one or more action servers interfacing with a chat service that handles all interaction modeling events that instruct utterances of the interactive agent (i.e., page 2 paragraph [0031]).
Regarding claim 7, Cheng teaches the one or more processors of claim 1, wherein the processing circuitry is further to execute the one or more corresponding calls based at least on a first action server of the one or more action servers interfacing with a graphical user interface service that handles all interaction modeling events that instruct an overlay of visual content supplementing a conversation with the interactive agent (i.e., page 3 paragraph [0040 and page 8 paragraphs [0081]-[0082]).
Regarding claim 8, Cheng teaches the one or more processors of claim 1, wherein the one or more processors are comprised in at least one of:
a control system for an autonomous or semi-autonomous machine;
a perception system for an autonomous or semi-autonomous machine;
a system for performing simulation operations;
a system for performing digital twin operations;
a system for performing light transport simulation;
a system for performing collaborative content creation for 3D assets;
a system for performing deep learning operations;
a system for performing remote operations;
a system for performing real-time streaming;
a system for generating or presenting one or more of augmented reality content, virtual reality content, or mixed reality content;
a system implemented using an edge device;
a system implemented using a robot;
a system for performing conversational AI operations;
a system implementing one or more language models;
a system implementing one or more large language models (LLMs);
a system implementing one or more vision language models (VLMs);
a system implementing one or more multimodal language models;
a system for generating synthetic data;
a system for generating synthetic data using AI;
a system incorporating one or more virtual machines (VMs);
a system implemented at least partially in a data center; or
a system implemented at least partially using cloud computing resources (i.e., Large Language Models (LLM), page 1 paragraph [0022]).
Regarding claim 9, Cheng teaches a system comprising one or more processors to:
generate, based at least on one or more incoming interaction modeling events in a standardized schema generated by one or more sensory servers in one or more input interaction channels (i.e., a data gateway may transforms the one or more prompts into a normalized API request, page 12 paragraph [0126]), one or more outgoing interaction modeling events in the standardized schema instructing one or more action servers in one or more output interaction channels to generate one or more corresponding calls to generate and output of execute one or more responsive agent actions or one or more responsive scene actions associated with an interactive agent (i.e., Cheng, in Fig. 6 and page 4 paragraph [0057], discloses invoke an LLM generate handler(s) to generate a post message (e.g., API call) for LLM service(s) to generate a response based on the provided prompt. Cheng, in page 3 paragraph [0039], also discloses generate a LLM prompt that instructs a task to be complete).
Please note: the statement “to generate one or more corresponding calls to generate and output one or more responsive agent actions or one or more responsive scene action associated with an interactive agent” in line 5-7 of claim 9 would be interpreted to be statement of intended use since no actual generate and output are claimed.
Regarding claim 10, Cheng teaches the system of claim 9, wherein the one or more processors are further to handle, using each action server of a plurality of action servers including the one or more action servers, a corresponding interaction modality of a plurality of mutually exclusive interaction modalities (i.e., interact with different LLMs located on different external servers, page 4 paragraph [0054]).
Regarding claim 11, Cheng teaches the system of claim 9, wherein the one or more processors are further to receive the one or more incoming interaction modeling events from the one or more sensory servers via one or more event gateways (i.e., the AI gateway may receive a task request, page 4 paragraph [0055]), and transmit the one or more outgoing interaction modeling events to the one or more action servers via the one or more event gateways (i.e., LLM gateway 130 may in turn invoke an LLM generate handler(s) to generate a post message for LLM service(s) to generate a response, page 4 paragraph [0057]).
Regarding claim 12, Cheng teaches the system of claim 9, wherein at least one individual each action server of the one or more action servers includes one or more action handlers for each agent action supported by an interaction manager in a corresponding interaction modality (i.e., LLM Generate Handlers 612-615, Fig. 6 and page 4 paragraph [0057]).
Regarding claim 13, Cheng teaches the system of claim 9, wherein the one or more processors are further to one or more corresponding calls based at least on a first action server of the one or more action servers interfacing with a chat service that handles all interaction modeling events that instruct utterances of the interactive agent (i.e., page 2 paragraph [0031]).
Regarding claim 15, Cheng teaches the system of claim 9, wherein the one or more processors are further to one or more corresponding calls based at least on a first action server of the one or more action servers interfacing with a graphical user interface service that handles all interaction modeling events that instruct an overlay of visual content supplementing a conversation with the interactive agent.
Regarding claim 16, Cheng teaches the system of claim 9, wherein the system is comprised in at least one of:
a control system for an autonomous or semi-autonomous machine;
a perception system for an autonomous or semi-autonomous machine;
a system for performing simulation operations;
a system for performing digital twin operations;
a system for performing light transport simulation;
a system for performing collaborative content creation for 3D assets;
a system for performing deep learning operations;
a system for performing remote operations;
a system for performing real-time streaming;
a system for generating or presenting one or more of augmented reality content, virtual reality content, or mixed reality content;
a system implemented using an edge device;
a system implemented using a robot;
a system for performing conversational Al operations;
a system implementing one or more language models;
a system implementing one or more large language models (LLMs);
a system implementing one or more vision language models (VLMs);
a system implementing one or more multimodal language models;
a system for generating synthetic data;
a system for generating synthetic data using AI;
a system incorporating one or more virtual machines (VMs);
a system implemented at least partially in a data center; or
a system implemented at least partially using cloud computing resources (i.e., Large Language Models (LLM), page 1 paragraph [0022]).
Regarding claim 17, Cheng teaches a method comprising:
generating, based at least on one or more incoming interaction modeling events with a standardized schema generated in one or more input interaction channels (i.e., a data gateway may transforms the one or more prompts into a normalized API request, page 12 paragraph [0126]), one or more outgoing interaction modeling events in the standardized schema instructing one or more output interaction channels to translate the one or more outgoing interaction modeling events into one or more corresponding calls to generate and output one or more responsive agent actions or one or more responsive scene actions associated with an interactive agent (i.e., Cheng, in Fig. 6 and page 4 paragraph [0057], discloses invoke an LLM generate handler(s) to generate a post message (e.g., API call) for LLM service(s) to generate a response based on the provided prompt. Cheng, in page 3 paragraph [0039], also discloses generate a LLM prompt that instructs a task to be complete).
Please note: the statement “to translate the one or more outgoing interaction modeling events into one or more corresponding calls to generate and output one or more responsive agent actions or one or more responsive scene actions associated with an interactive agent” in claim 17 would be interpreted to be statement of intended use since no actual translate, generate, and output are claimed.
Regarding claim 18, Cheng teaches the method of claim 17, wherein the one or more output interaction channels include a plurality of action servers that control a plurality of corresponding mutually exclusive interaction modalities (i.e., Fig. 5 and page 4 paragraph [0054]).
Regarding claim 19, Cheng teaches the method of claim 17, further comprising: providing the one or more incoming interaction modeling events from one or more sensory servers in the in one or more input interaction channels to an interaction manager via one or more event gateways, and providing the one or more outgoing interaction modeling events generated by the interaction manager to one or more action servers in the one or more output interaction channels via the one or more event gateways (i.e., Figs 5-6 and page 4 paragraph [0054]-[0057].
Regarding claim 20, Cheng teaches the method of claim 17, wherein the method is performed by at least one of:
a control system for an autonomous or semi-autonomous machine;
a perception system for an autonomous or semi-autonomous machine;
a system for performing simulation operations;
a system for performing digital twin operations;
a system for performing light transport simulation;
a system for performing collaborative content creation for 3D assets;
a system for performing deep learning operations;
a system for performing remote operations;
a system for performing real-time streaming;
a system for generating or presenting one or more of augmented reality content, virtual reality content, or mixed reality content;
a system implemented using an edge device;
a system implemented using a robot;
a system for performing conversational Al operations;
a system implementing one or more language models;
a system implementing one or more large language models (LLMs);
a system implementing one or more vision language models (VLMs);
a system implementing one or more multimodal language models;
a system for generating synthetic data;
a system for generating synthetic data using AI;
a system incorporating one or more virtual machines (VMs);
a system implemented at least partially in a data center; or
a system implemented at least partially using cloud computing resources (i.e., Large Language Model (LLMs), page 1 paragraph [0022]).
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.
5. Claim(s) 6 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Cheng, in view of Froelich, US 2017/0256259 A1.
Regarding claim 6, Cheng teaches the one or more processors of claim 1, wherein the processing circuitry is further to execute the one or more corresponding calls based at least on a first action server of the one or more action servers (i.e., Fig. 8, and page 3 paragraph [0039] and page 8 paragraphs [0080]- [0083]).
Cheng does not explicitly teach interfacing with an animation service that handles all interaction modeling events that instruct gestures of the interactive agent.
Froelich teaches interfacing with an animation service that handles all interaction modeling events that instruct gestures of the interactive agent (i.e., page 7 paragraph [0110]).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the teachings of Cheng to interface with an animation service that handles all interaction modeling events that instruct gestures of the interactive agent, as taught by Froelich, in order to provide human-like responses to input from the user (i.e., Froelich, page 1 paragraph [0004]).
Regarding claim 14, this claim recites limitation that is similar to claim 6, same rationale of rejections is applied.
Response to Arguments
6. Applicant’s arguments with respect to claim(s) 1-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
7. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
8. Any inquiry concerning this communication or earlier communications from the examiner should be directed to OANH DUONG whose telephone number is (571)272-3983. The examiner can normally be reached Maxiflex Mon-Fri 6:00am-5:00pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Tonia Dollinger can be reached at (571) 272-4170. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/OANH DUONG/Primary Examiner, Art Unit 2441