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. This is in response to communication filed on 4/16/25 in which claims 1-21 are pending.
Specification
2. Applicant is reminded of the proper content of an abstract of the disclosure.
A patent abstract is a concise statement of the technical disclosure of the patent and should include that which is new in the art to which the invention pertains. The abstract should not refer to purported merits or speculative applications of the invention and should not compare the invention with the prior art.
If the patent is of a basic nature, the entire technical disclosure may be new in the art, and the abstract should be directed to the entire disclosure. If the patent is in the nature of an improvement in an old apparatus, process, product, or composition, the abstract should include the technical disclosure of the improvement. The abstract should also mention by way of example any preferred modifications or alternatives.
Where applicable, the abstract should include the following: (1) if a machine or apparatus, its organization and operation; (2) if an article, its method of making; (3) if a chemical compound, its identity and use; (4) if a mixture, its ingredients; (5) if a process, the steps.
Extensive mechanical and design details of an apparatus should not be included in the abstract. The abstract should be in narrative form and generally limited to a single paragraph within the range of 50 to 150 words in length.
See MPEP § 608.01(b) for guidelines for the preparation of patent abstracts.
Claim Rejections - 35 USC § 102
3. 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.
4. Claims 1-6, 8-12, 15-16 and 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by U.S. Publication No. 2023/0199746 to Vannithamby et al.
a. As per claim 1, Vannithamby et al teaches a computer-implemented method in a first device, comprising: transmitting situational context information to a network, the situational context information representing at least one of a present situational context of the first device or a semantic requirement of a software application of the first device (See paragraph [0066-0067 and 0144], Syntactic information may include non-contextual information with respect to the received raw data and its content); responsive to transmitting the situational context information, receiving from the network, an indication of a first neural network (See paragraph [0087]);
implementing the first neural network at the first device (See paragraph [0087]); receiving, from a second device in the network, a first signal representative of a semantic code, the semantic code representing at least one semantic meaning of application data (See paragraph [0067 and 0151]; processing the first signal by at least the first neural network of the first device to generate a representation of the at least one semantic meaning (See paragraph [0056] ; and controlling an operation of the software application executing at the first device based on the at least one semantic meaning (See paragraph [0087]).
b. As per claim 2, Vannithamby et al teaches the claimed invention as described above. Furthermore, Vannithamby et al teaches wherein processing the first signal further comprises: processing the first signal at a second neural network of the first device to generate a second signal that is a channel decoded representation of the first signal (See paragraph [0043 and 0149]); and processing the second signal at the first neural network to generate the representation of the at least one semantic meaning (See paragraph [0087]).
c. As per claim 3, Vannithamby et al teaches the claimed invention as described above. Furthermore, Vannithamby et al teaches wherein the first neural network is jointly trained with the second neural network (See paragraph [0087, 0100-0101], The processor 300 may provide the received raw data to an input of the AI/ML. The AI/ML may include a trained AI/ML. The AI/ML may be configured to provide an output including the extracted semantic information which the processor 300 may schedule for the transmission as provided in this disclosure).
d. As per claim 4, Vannithamby et al teaches the claimed invention as described above. Furthermore, Vannithamby et al teaches wherein the first neural network and the second neural network are jointly trained with at least a third neural network implemented at the second device (See paragraph [0087, 0100-0101]).
e. As per claim 5, Vannithamby et al teaches the claimed invention as described above. Furthermore, Vannithamby et al teaches wherein processing the first signal at the second neural network further comprises: processing sensor data from one or more sensors of the first device at the second neural network concurrent with processing the first signal at the second neural network (See paragraph [0051]).
f. As per claim 6, Vannithamby et al teaches the claimed invention as described above. Furthermore, Vannithamby et al teaches wherein the situational context information includes at least one of: present capabilities of the first device; an application type of the software application; a semantic communication capability of the software application; a present location of the first device; a network condition of the first device; a processing bandwidth of the first device; a memory bandwidth of the first device; a power status of the first device; or a network condition of a network channel between the first device and the second device (See paragraph [0066-0067]).
g. As per claim 8, Vannithamby et al teaches the claimed invention as described above. Furthermore, Vannithamby et al teaches wherein the indication of the first neural network comprises at least one of: an identifier of one of a plurality of candidate neural networks accessible by the first device; or data representing a neural network architectural configuration of the first neural network (See paragraph [0066 and 0121]).
h. As per claim 9, Vannithamby et al teaches the claimed invention as described above. Furthermore, Vannithamby et al teaches wherein the first signal is an output of processing of the application data by a third neural network at the second device that is connected to the first device via a network channel, the third neural network being jointly trained with the first neural network (See paragraph [0087, 0100-0101, 0107 and 0113]).
i. As per claim 10, Vannithamby et al teaches the claimed invention as described above. Furthermore, Vannithamby et al teaches wherein controlling the operation of the software application includes controlling the software application to present the at least one semantic meaning to a user of the first device (See paragraph [0054-0055]).
j. As per claim 11, Vannithamby et al teaches the claimed invention as described above. Furthermore, Vannithamby et al teaches wherein at least one of :the application data is an image and the at least one semantic meaning is an identifier of a subject represented in the image ;the application data is a video and the at least one semantic meaning is a synopsis or summary of content of the video; the application data is audio data and the at least one semantic meaning is a synopsis or summary of a content of the audio data; or the application data is text and the at least one semantic meaning is a synopsis or summary of a topic of the text (See paragraph [0064 and 0103]).
k. As per claim 12, Vannithamby et al teaches a computer-implemented method in a second device in a network, comprising: receiving, from a first device, situational context information representing at least one of a present situational context of the first device or a semantic requirement of a software application of the first device (See paragraph [0067 and 0145]);
transmitting an indication of a first neural network to the first device responsive to the situational context information (See paragraph [0092, 0107 and 0109]); processing application data by at least a third neural network of the second device to generate a first signal representing a semantic code, the semantic code representing at least one semantic meaning of the application data (See paragraph [[0147 and 0149]); and transmitting the first signal for receipt by the second device (See paragraph [0147]).
l. As per claim 15, Vannithamby et al teaches the claimed invention as described above. Furthermore, Vannithamby et al teaches wherein processing the application data further based on processing sensor data from one or more sensors of the second device at the third neural network (See paragraph [0048-0049]).
m. As per claim 16, Vannithamby et al teaches a first device comprising:
a network interface (See paragraph [0060 and 0118]); at least one processor coupled to the network interface (See paragraph [0060]); and a non-transitory computer-readable medium storing a set of instructions, the set of instructions configured to manipulate one or both of the at least one processor or the network interface to: transmit situational context information to a network, the situational context information representing at least one of a present situational context of the first device or a semantic requirement of a software application of the first device (See paragraph [0066-0067 and 0144], Syntactic information may include non-contextual information with respect to the received raw data and its content); responsive to transmitting the situational context information, receive from the network, an indication of a first neural network (See paragraph [0087]); implement the first neural network at the first device (See paragraph [0087]); receive, from a second device in the network, a first signal representative of a semantic code, the semantic code representing at least one semantic meaning of application data (See paragraph [0067 and 0151]); process the first signal by at least the first neural network of the first device to generate a representation of the at least one semantic meaning (See paragraph [0056]); and control an operation of the software application executing at the first device based on the at least one semantic meaning (See paragraph [0087]).
n. As per claim 20, Vannithamby et al teaches a second device comprising: a network interface (See paragraph [0060]); at least one processor coupled to the network interface (See paragraph [0045]); and a non-transitory computer-readable medium storing a set of instructions, the set of instructions configured to manipulate one or both of the at least one processor or the network interface to: receive, from a first device of the network, situational context information representing at least one of a present situational context of the first device or a semantic requirement of a software application of the first device (See paragraph [0067]); transmit an indication of a first neural network to the first device responsive to the situational context information (See paragraph [0090-0091]); process application data by at least a third neural network of the second device to generate a first signal representing a semantic code, the semantic code representing at least one semantic meaning of the application data (See paragraph [0087 and 0106-0107]); and transmit the first signal for receipt by the first device (See paragraph [0090]).
Claim Rejections - 35 USC § 103
5. 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 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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
6. Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over U.S. Publication No. 2023/0199746 to Vannithamby et al in view of U.S. Publication No. 2025/0267296 to Crabtree et al.
a. As per claim 7, Vannithamby et al teaches the claimed invention as described above. However, Vannithamby et al fails to teach wherein the semantic requirement comprises at least one of: a semantic quantization level; a perceptional evaluation of speech quality (PESQ) score requirement; an image similarity metric; or a Fifth Generation quality of service identifier (SQI) requirement.
Crabtree et al teaches wherein the semantic requirement comprises at least one of: a semantic quantization level; a perceptional evaluation of speech quality (PESQ) score requirement; an image similarity metric; or a Fifth Generation quality of service identifier (SQI) requirement (See paragraph [0362, 0371 and 0375]).
It would have been obvious to one with ordinary skill in the art to incorporate the teaching of Crabtree et al in the claimed invention of Vannithamby et al in order to adjust quantization parameters.
Allowable Subject Matter
7. Claims 17-19 are allowed.
8. Claims 13-14, 21 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
9. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
U.S. Publication No. 2023/0016827 to Wu et al teaches Adaptive Offloading of Federated Learning.
U.S. Publication No. 2023/0094234 to Roessel et al teaches Channel-Aware Semantic Coding.
10. Any inquiry concerning this communication or earlier communications from the examiner should be directed to DJENANE BAYARD whose telephone number is (571)272-3878. The examiner can normally be reached 9-5.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, John Follansbee can be reached at (571)272-3964. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DJENANE M BAYARD/Primary Examiner, Art Unit 2444
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