DETAILED ACTION
Notice relating to Pre-AIA or AIA Status
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.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of the Claims
Applicant’s current amendment (dated 04 FEBRUARY 2026), has been entered. The status of the claims is as follows: Claims 1-20 are currently pending in the application.
Response to Arguments
Applicant's arguments filed 04 FEBRUARY 2026 have been fully considered but they are not persuasive. On pages 7-8 of Applicant’s remarks, Applicant argues (regarding at least claim 1) that the previously cited prior art combination of Vaishampayan (US 2020/0382616) and Liu (US 2023/0305680) does not disclose all the currently presented claim limitations. Specifically, Applicant argues that Liu does not disclose sharing functionality of the primary AI module with the second media device based on the configuration information. The Examiner respectfully disagrees that the combination of references, when taken together as a whole, does not disclose all of Applicant’s currently presented claim limitations. It is initially noted that Applicant is primarily arguing against the Liu reference for certain limitations, when the combination of Vaishampayan and Liu was used to address all the claim limitations fully. For instance, in the previous rejection, Vaishampayan was cited as disclosing (among other things) determining configuration information associated with the second media device (see Vaishampayan; device, i.e. first, can receive specific information from the other, i.e. second, device that includes needed model, name/ID, version, etc. of the machine learning that it would like to utilize and are required for its particular application, i.e. the required information interpreted as configuration information; page 18, paragraph 195, and determining whether conditions are satisfied for the requesting application, i.e. configuration(s); page 21, paragraph 217); and sharing functionality of the primary machine module with the second media device based on the configuration information (see Vaishampayan; based on the needed, i.e. configuration, information associated with the other device, the device can then provide/share the machine learning functionality; page 19, paragraphs 200-203, and pages 21-22, paragraphs 219-223). While it was noted that Vaishampayan did disclose limitations relating to machine learning functionalities (see above), Vaishampayan did not explicitly disclose an artificial intelligence (AI) module. The secondary prior art reference of Liu was then brought in to cure this remaining deficiency of Vaishampayan, in that Liu was cited as disclosing (among other things) an artificial intelligence (AI) module (device can include functionality such as AI module(s) for various operations to be performed; page 35, paragraphs 556 and 558). That is, with the primary reference of Vaishampayan already disclosing the majority of the claimed limitations, and even discussing machine learning, Liu was brought in to explicitly show how AI functionality could be a functionality/module that could be shared between devices (i.e. such as with the sharing already disclosed in Vaishampayan). In response to Applicant’s arguments about the configuration information, the Examiner again respectfully disagrees that the combination of references does not disclose such limitations. As was shown previously, the primary reference of Vaishampayan was already cited as disclosing the limitations related to the configuration information, with the secondary reference of Liu only cited as disclosing it for further support for such limitations. While applicant argues that capability information is not the same as configuration information, the Examiner notes a broad interpretation of “configuration information” as discussed in Applicant’s originally filed specification. For instance, while Applicant’s specification does include some example descriptions of the configuration information, it also broadly describes it as (see paragraph 3 of the originally filed specification) “the configuration information includes function information associated with the second media device.” This can lead to an interpretation of capability information associated with a particular device, i.e. functional capabilities, of the device.
Therefore, the combination of references, when taken together as a whole, does disclose all of Applicant’s currently presented claim limitations.
Applicant is suggested to provide more detail as to what they believe constitutes the true invention of the application. This could help distinguish over the prior art of record, alleviate misinterpretation issues, and serve to move prosecution forward on the application in a more expedited manner.
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 1-4, 6-11, 13-18, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Vaishampayan et al., US 2020/0382616 in view of Liu et al., US 2023/0305680.
Regarding claim 1, Vaishampayan discloses a system comprising:
one or more processors (system with at least a processor; page 2, paragraph 21, and page 13, paragraph 166, and page 14, paragraph 168, and page 22, paragraph 229); and
logic encoded in one or more non-transitory computer-readable storage media for execution by the one or more processors (instructions/logic on non-transitory media, for execution by at least a processor; page 14, paragraph 168, and page 22, paragraph 229) and when executed operable to perform operations (executable operations; page 22, paragraph 229) comprising:
detecting, by a first media device, a presence of a second media device (with specific, i.e. first device; Fig. 6, element 604, and page 16, paragraph 184, and including at least a media type device, such as a tablet computer, laptop computer, smartphone, etc.; page 16, paragraph 185, and determining that another, i.e. second, device is in proximity of the specific/first device; page 17, paragraph 191, and page 18, paragraph 194, and page 21, paragraph 214-215, and wherein with second device; Fig. 6, element 602, and page 16, paragraph 184, and other device also includes at least a media type device, such as a smartphone, tablet, etc.; page 16, paragraph 184), wherein the first media device comprises a primary machine module (device can include at least a machine learning model; Fig. 6, element 610, and page 16, paragraph 187, and page 21, paragraph 214, and with modules; page 12, paragraph 134, and including various hardware/software/circuits; page 4, paragraph 32);
establishing communication between the first media device and the second media device (establish a communication connection; page 18, paragraphs 195 and 199, and page 21, paragraph 216);
determining configuration information associated with the second media device (device, i.e. first, can receive specific information from the other, i.e. second, device that includes needed model, name/ID, version, etc. of the machine learning that it would like to utilize and are required for its particular application, i.e. the required information interpreted as configuration information; page 18, paragraph 195, and determining whether conditions are satisfied for the requesting application, i.e. configuration(s); page 21, paragraph 217); and
sharing functionality of the primary machine module with the second media device based on the configuration information (based on the needed, i.e. configuration, information associated with the other device, the device can then provide/share the machine learning functionality; page 19, paragraphs 200-203, and pages 21-22, paragraphs 219-223).
Vaishampayan does not explicitly disclose an artificial intelligence (AI) module.
In a related art, Liu does disclose an artificial intelligence (AI) module (device can include functionality such as AI module(s) for various operations to be performed; page 35, paragraphs 556 and 558); and
configuration information of a second media device (particular device can request and receive capability/configuration information about a secondary device/terminal; page 32, paragraph 516).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the prior art of Vaishampayan and Liu by allowing the already present machine learning operations of Vaishampayan to also include various AI capabilities, in order to provide an improved system and method for invoking a capability of another device, so that a user can use a function of another device on one device, which improves a degree of intelligence of the electronic device, and improves user experience (Liu; page 1, paragraph 4).
Regarding claim 2, Vaishampayan in view of Liu disclose the configuration information comprises function information associated with the second media device (Vaishampayan; information includes application requirements, i.e. application functionality of the requesting device; page 18, paragraph 195, and Liu; capability/configuration information about a secondary device/terminal, such as functions/functionality; page 5, paragraph 57, and page 32, paragraph 516, and page 35, paragraph 557).
Regarding claim 3, Vaishampayan in view of Liu disclose accessing one or more functions of the second media device (Vaishampayan; accessing/using at least the application of the device; pages 19-20, paragraphs 200-208); and
enhancing the one or more functions of the second media device using the primary AI module of the first media device (Vaishampayan; enhancing the function of the application on the device with the use of the machine learning from the other device; pages 19-20, paragraphs 200-208, and Liu; with functionality such as AI module(s) for various operations to be performed; page 35, paragraphs 556 and 558, and for improving efficiency; page 33, paragraph 525).
Regarding claim 4, Vaishampayan in view of Liu discloses the configuration information comprises input/output port information associated with the second media device (Vaishampayan; system utilizes port information for establishing a connection; page 19, paragraph 200, and Liu; information can include port information as well; page 47, paragraph 731, and page 49, paragraph 753, and page 58, paragraph 883, and page 69, paragraph 1045).
Regarding claim 6, Vaishampayan in view of Liu discloses the configuration information comprises setup information associated with the second media device (Vaishampayan ; information from the other, i.e. second, device that includes needed model, name/ID, version, etc. of the machine learning that it would like to utilize and are required for its particular application, i.e. the required information interpreted as configuration information for setting up the application operations; page 18, paragraph 195, and page 19, paragraphs 200-203, and pages 21-22, paragraphs 219-223, and Liu; information can include at least port information for setting up the connection(s) between the devices, i.e. including at least the second device; page 47, paragraph 731, and page 49, paragraph 753, and page 58, paragraph 883, and page 69, paragraph 1045, and capability/configuration information about a secondary device/terminal, which will be used to setup connection/communication for performing the requested operations; page 32, paragraph 516).
Regarding claim 7, Vaishampayan in view of Liu discloses accessing the configuration information associated with the second media device (Vaishampayan; receiving, i.e. accessing information from the other, i.e. second, device that includes needed model, name/ID, version, etc. of the machine learning that it would like to utilize and are required for its particular application, i.e. the required information interpreted as configuration information for setting up the application operations; page 18, paragraph 195, and Liu; received, i.e. accessed, capability/configuration information about a secondary device/terminal; page 32, paragraph 516); and
configuring the second media device using the primary AI module of the first media device (Vaishampayan; setting up the applications/functions and performing operations based on the communicated information; pages 19-20, paragraphs 200-208, and pages 21-22, paragraphs 219-223, and again with machine learning model; Fig. 6, element 610, and page 16, paragraph 187, and page 21, paragraph 214, and Liu; performing/configuring the device to utilize the function(s) of the other device; page 60, paragraphs 900-905, and again with functionality such as AI module(s) for various operations to be performed; page 35, paragraphs 556 and 558).
Claim 8, which discloses a non-transitory computer-readable storage medium, is analyzed with respect to the citations and/or rationale provided in the rejection of similar claim 1. The following additional limitations are also disclosed:
a non-transitory computer-readable storage medium with program instructions (Vaishampayan; can include non-transitory medium with stored executable instructions; page 22, paragraph 229).
Claim 9, which discloses a computer-readable storage medium, is analyzed with respect to the citations and/or rationale provided in the rejection of similar claim 2.
Claim 10, which discloses a computer-readable storage medium, is analyzed with respect to the citations and/or rationale provided in the rejection of similar claim 3.
Claim 11, which discloses a computer-readable storage medium, is analyzed with respect to the citations and/or rationale provided in the rejection of similar claim 4.
Claim 13, which discloses a computer-readable storage medium, is analyzed with respect to the citations and/or rationale provided in the rejection of similar claim 6.
Claim 14, which discloses a computer-readable storage medium, is analyzed with respect to the citations and/or rationale provided in the rejection of similar claim 7.
Claim 15, which discloses a method, is analyzed with respect to the citations and/or rationale provided in the rejection of similar claim 1.
Claim 16, which discloses a method, is analyzed with respect to the citations and/or rationale provided in the rejection of similar claim 2.
Claim 17, which discloses a method, is analyzed with respect to the citations and/or rationale provided in the rejection of similar claim 3.
Claim 18, which discloses a method, is analyzed with respect to the citations and/or rationale provided in the rejection of similar claim 4.
Claim 20, which discloses a method, is analyzed with respect to the citations and/or rationale provided in the rejection of similar claim 6.
Claims 5, 12, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Vaishampayan et al., US 2020/0382616 in view of Liu et al., US 2023/0305680 and further in view of Jassal et al., US 2020/0366326.
Regarding claim 5, Vaishampayan in view of Liu discloses all the claimed limitations of claim 1, as well as accessing one or more input/output ports of the second media device (Vaishampayan; system can access and utilize specific port(s) of the devices, i.e. including at least the second device, for the communications/operations between the devices; page 19, paragraph 200, and Liu; accessing specific port(s) for the communications; page 47, paragraph 731, and page 49, paragraph 753, and page 58, paragraph 883, and page 69, paragraph 1045);
one or more input/output ports of the second media device (Vaishampayan; again, utilizing port(s) of the specific device(s), i.e. including at least the second; page 19, paragraph 200, and Liu; page 47, paragraph 731, and page 49, paragraph 753, and page 58, paragraph 883, and page 69, paragraph 1045); and
the primary AI module of the first media device (Vaishampayan; machine learning model; Fig. 6, element 610, and page 16, paragraph 187, and page 21, paragraph 214, and Liu; with functionality such as AI module(s) for various operations to be performed; page 35, paragraphs 556 and 558).
Vaishampayan in view of Liu does not explicitly disclose enhancing operability of one or more input/output ports using AI.
In a related art, Jassal does disclose enhancing operability of one or more input/output ports using AI (can utilize AI in system to provide enhancement to port operations, such as optimal port configuration(s); page 6, paragraphs 84-87 and 89, and page 7, paragraphs 93-94).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the prior art of Vaishampayan, Liu, and Jassal, by allowing the already present machine learning/AI of Vaishampayan in view of Liu to be utilized for optimizing port performance, in order to provide an improved system and method for configuring an artificial intelligence (AI) module to perform at least one task for wireless communications and performing the at least one task using the configured AI module (Jassal; page 1, paragraph 10).
Claim 12, which discloses a computer-readable storage medium, is analyzed with respect to the citations and/or rationale provided in the rejection of similar claim 5.
Claim 19, which discloses a method, is analyzed with respect to the citations and/or rationale provided in the rejection of similar claim 5.
Conclusion
THIS ACTION IS MADE FINAL. 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RANDY A FLYNN whose telephone number is (571)270-5680. The examiner can normally be reached Monday - Thursday, 6:00am - 3:00pm ET.
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/RANDY A FLYNN/Primary Examiner, Art Unit 2424