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 .
Claim Rejections - 35 USC § 102
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.
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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 5, 8, 12, 15 and 19 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by US 2023/0282218 to Moynihan et al..
As per claim 1, Moynihan et al. teach a computer-implemented method for controlling peripheral devices using an artificial intelligence system (paragraph 141, “a weak supervision machine learning model”, notice that ML is a subset of the AI field), the method comprising:
processing audio or video data captured by one or more microphones or one or more cameras (paragraph 128, “at a first time the meeting attendee 620 utters the natural language utterance 602—“the sales number in July were higher than expected . . .” in response to the detection of the natural language utterance, various functionality may automatically occur”);
determining, based on the processed audio data or video data, at least one of
a first desire of at least one participant; or
contextual information associated with the processed audio data or video data (paragraph 128, “In response to determining that a particular email is ranked the highest or is otherwise the most optimal or suitable to present”); and causing one or more peripheral devices to act based on the first desire or information (Fig. 6, 604, “the presentation component 220 automatically causes presentation, during the meeting, of the window 604, along with embedded indicia and corresponding link 606—“Here is a link to an email you sent on 08/03 that discusses the sales numbers Alek just referenced.””).
As per claim 5, Moynihan et al. teach the computer-implemented method as defined in claim 1, wherein causing the one or more peripheral devices to act comprises presenting, via the one or more peripheral devices, accompanying context (Fig. 6, 604) for causing the one or more peripheral devices to act.
As per claim 8, it comprises similar limitations to those in claim 1 and it is therefore rejected for similar reasons.
As per claim 12, it comprises similar limitations to those in claim 5 and it is therefore rejected for similar reasons.
As per claim 15, it comprises similar limitations to those in claim 1 and it is therefore rejected for similar reasons.
As per claim 19, it comprises similar limitations to those in claim 5 and it is therefore rejected for similar reasons.
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 2-4, 9-11 and 16-18 are rejected under 35 U.S.C. 103 as being unpatentable over US 2023/0282218 to Moynihan et al.; in view of US 2021/0076002 to Peters et al.
As per claim 2, Moynihan et al. teach the computer-implemented method as defined in claim 1.
Moynihan et al. do not teach noting sentiment of the at least one participant of the one or more actions taken; and updating a deep reinforcement learning model with the noted sentiment.
Peters et al. teach noting sentiment of the at least one participant of the one or more actions taken (paragraph 307, “The techniques discussed above can be used to determine the emotional and cognitive state of a person in a video conference or remote interaction); and updating a deep reinforcement learning model (paragraph 378, “a reinforcement learning model that can be used to gradually learn relationships as patterns and trends are observed in different communication sessions”) with the noted sentiment (paragraphs 327-328, “The collected data can be used to training models to facilitate human/human interaction and machine/human interaction”).
It would have been obvious to one of ordinary skill in the art, to modify the device of Moynihan et al., by noting sentiment of the at least one participant of the one or more actions taken; and updating a deep reinforcement learning model with the noted sentiment, such as taught by Peters et al., for the purpose of improving model accuracy.
As per claim 3, Moynihan and Peters et al. teach the computer-implemented method as defined in claim 2, further comprising inferring at least one second desire based on applying the updated deep reinforcement learning model (Peters, Fig. 12C, “Philip seems to have a question to ask”).
As per claim 4, Moynihan and Peters et al. teach the computer-implemented method as defined in claim 2, wherein audio data or video data is processed to determine the noted sentiment (Peters, paragraph 67, “the video conference moderator system monitors, processes, and determines the level and quality of participation of each participant based on factors such as speaking time and the emotional elements of the participants based on facial expression recognition and audio feature recognition”).
As per claim 9, it comprises similar limitations to those in claim 2 and it is therefore rejected for similar reasons.
As per claim 10, it comprises similar limitations to those in claim 3 and it is therefore rejected for similar reasons.
As per claim 11, it comprises similar limitations to those in claim 4 and it is therefore rejected for similar reasons.
As per claim 16, it comprises similar limitations to those in claim 2 and it is therefore rejected for similar reasons.
As per claim 17, it comprises similar limitations to those in claim 3 and it is therefore rejected for similar reasons.
As per claim 18, it comprises similar limitations to those in claim 4 and it is therefore rejected for similar reasons.
Claims 6, 7, 13, 14 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over US 2023/0282218 to Moynihan et al.; in view of US 2020/0193989 to Jeong.
As per claim 6, Moynihan et al. teach the computer-implemented method as defined in claim 1, wherein causing the one or more peripheral devices to act comprises presenting, via the one or more peripheral devices, supplemental context (Moynihan et al., Fig. 6, 604).
Moynihan et al. do not teach wherein the supplemental context is different from an accompanying context for causing the peripheral devices to act.
Jeong teaches wherein the supplemental context is different from an accompanying context for causing the peripheral devices to act (Figs. 4, 5 and 7-9, non-natural language of participants is used to infer a desired behavior, such as temperature control, for example).
It would have been obvious to one of ordinary skill in the art, to modify the device of Moynihan et al., so that the supplemental context is different from an accompanying context for causing the peripheral devices to act, such as taught by Jeong, for the purpose of improving the user experience.
As per claim 7, Moynihan et al. teach the computer-implemented method as defined in claim 1, wherein causing the one or more peripheral devices to act comprises presenting supplemental context (Moynihan et al., Fig. 6, 604).
Moynihan et al. do not teach accompanying context for the one or more actions taken via different portions of a user interface.
Jeong teaches accompanying context for the one or more actions (Figs. 4, 5 and 7-9, non-natural language of participants is used to infer a desired behavior, such as temperature control, for example) taken via different portions of a user interface (paragraph 50, “Data (for example, audio, video, image, and the like) is obtained by the input unit 120 and may be analyzed and processed by controller 180 according to device parameters, user commands, and combinations thereof”).
It would have been obvious to one of ordinary skill in the art, to modify the device of Moynihan et al., by including accompanying context for the one or more actions taken via different portions of a user interface, such as taught by Jeong, for the purpose of improving the user experience.
As per claim 13, it comprises similar limitations to those in claim 6 and it is therefore rejected for similar reasons.
As per claim 14, it comprises similar limitations to those in claim 7 and it is therefore rejected for similar reasons.
As per claim 20, it comprises similar limitations to those in claim 6 or claim 7 and it is therefore rejected for similar reasons.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOSE R SOTO LOPEZ whose telephone number is (571)270-5689. The examiner can normally be reached Monday-Friday, from 8 am - 5 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Patrick Edouard can be reached at (571) 272-7603. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JOSE R SOTO LOPEZ/Primary Examiner, Art Unit 2622
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