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 .
DETAILED ACTION
This office action is in response to the application filed on 01/04/2024.
Claims 1-13, 21-24 are currently pending.
Claims 14-20, 25-27 are canceled in a preliminary amendment.
Claims 1-13, 21-24 are amended via the preliminary amendment.
Claims 1, 4, 7, 9, 21 are rejected.
Claims 2-3, 5-6, 8, 10-13, 22-24 are objected to for depending from rejected base claims.
Claim Analysis - 35 USC § 101
Claim 1 recites the limitation to perform at least network decision generation.
When the claim is evaluated “as an ordered combination, without ignoring the requirements of the individual steps,” it becomes apparent that since the network decision generation is undertaken within the context of AI, the broadest reasonable conclusion is that the claimed network decision generation cannot be considered a mental step (i.e., an abstract idea).
A similar rationale is applied to the “data acquisition and report” limitation in claims 9 and 21, respectively.
According, Examiner believes that no rejection under 35 U.S.C. 101 is necessary at this time.
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.
Claims 4 and 7 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.
Claim 4 recites a “corresponding processor”. It is not clear from the claim if the “corresponding processor” is the same as or different from the preceding first processor. Therefore, claim 4 is rejected for being vague and indefinite.
Claim 7 recites the limitation "the second task requirement" in lines 14-16. There is insufficient antecedent basis for this limitation in the claim.
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)(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.
Claims 1, 9 ,21 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by HUNG- Qiaoyu Li et al (US 20230397172 A1).
Independent Claims 1, 9, 21 of the instant application are directed to a base station, comprising: a memory for storing instructions; a first processor configured to execute the instructions to: perform at least one of Artificial Intelligence (Al) task control for a terminal, Al task execution, network decision generation, or data management by interacting with the terminal, the method shown in FIG. 4.
PNG
media_image1.png
258
296
media_image1.png
Greyscale
The Li reference is concerned with Methods, systems, and devices for signaling of compressed gradient vectors in a machine learning system that utilizes federated learning. A base station may configure a UE with one or more parameters for quantizing a local stochastic gradient, and for reporting the quantized local stochastic gradient in a set of compressed gradient vectors, and multiple reports from multiple UEs may be aggregated in a federated learning procedure associated with a machine learning algorithm. The system is shown in FIG. 5.
PNG
media_image2.png
548
356
media_image2.png
Greyscale
For Claim 1, Li discloses a base station, comprising: a memory for storing instructions; a first processor configured to execute the instructions to (Li teaches, in ¶ 0019, lines 1-5, an apparatus for wireless communication at a base station is described. The apparatus may include a processor, memory in electronic communication with the processor, and instructions stored in the memory. The instructions may be executable by the processor): perform at least one of Artificial Intelligence (Al) task control for a terminal, Al task execution, network decision generation, or data management by interacting with the terminal (Li teaches, in FIG. 5, that At 510, the base station 105-c may transmit configuration information to the UE 115-c that configures the multi-stage compression procedure and, in some cases, may configure one or more other aspects for reporting (e.g., one or more CG-PUSCH allocations). At 535, the UE 115-c may transmit the local stochastic gradient vectors to the base station 105-c. At 545, the base station 105-c may transmit global model update information to the UE 115-c. And At 550, the UE 115-c may update the NN model based on the update information from the base station 105-c).
For Claim 9, Li discloses a terminal, comprising: a memory for storing instructions; a first processor configured to execute the instructions to (Li teaches, in ¶ 0007, lines 1-5, an apparatus for wireless communication at a UE is described. The apparatus may include a processor, memory in electronic communication with the processor): perform at least one of Artificial Intelligence (AI) task control for the terminal, data acquisition and report, or Al task execution by interacting with a base station (Li teaches, in FIG. 5, that At 510, the base station 105-c may transmit configuration information to the UE 115-c that configures the multi-stage compression procedure and, in some cases, may configure one or more other aspects for reporting (e.g., one or more CG-PUSCH allocations). At 535, the UE 115-c may transmit the local stochastic gradient vectors to the base station 105-c. At 545, the base station 105-c may transmit global model update information to the UE 115-c. And At 550, the UE 115-c may update the NN model based on the update information from the base station 105-c).
For Claim 21, Li discloses An Artificial Intelligence (Al) task control method, applied to a terminal, comprising: performing, by a first processor of the terminal (Li teaches, in ¶ 0007, lines 1-5, an apparatus for wireless communication at a UE is described. The apparatus may include a processor, memory in electronic communication with the processor), at least one of Al task control for the terminal, data acquisition and report, or Al task execution by interacting with a base station (Li teaches, in FIG. 5, that At 510, the base station 105-c may transmit configuration information to the UE 115-c that configures the multi-stage compression procedure and, in some cases, may configure one or more other aspects for reporting (e.g., one or more CG-PUSCH allocations). At 535, the UE 115-c may transmit the local stochastic gradient vectors to the base station 105-c. At 545, the base station 105-c may transmit global model update information to the UE 115-c. And At 550, the UE 115-c may update the NN model based on the update information from the base station 105-c).
Allowable Subject Matter
Claims 2-3, 5-6, 8, 10-13, 22-24 are objected to as being dependent upon rejected base claims, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter:
Claims 2-3, 5-6, 8, 10-13, 22-24 are considered allowable because the prior art does not teach limitations including:
“determine, one or more configurations of configurations comprising a first Al model and algorithm required to be used, data acquisition requirement, data preprocessing mode, Al task configuration, and Al model evaluation indexes, and configure the one or more configurations to at least one the terminal or a local position, and receive at least a data acquisition result or Al model evaluation result sent by the terminal; generate a corresponding execution result based on the data acquisition result according to the first Al model and algorithm; generate network decision according to the execution result; or maintain at least one of a task queue of Al tasks, an Al model and algorithm library, [[and]]or an acquired data set,” in addition to other claim limitations as recited in dependent claims 2, 10, 22.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. HUANGFU (US 20230179490 A1) teaches that an artificial intelligence-based communication method, whereby a first communication apparatus obtains a first artificial intelligence (AI) model corresponding to a first task. The first communication apparatus obtains first data corresponding to a first feature, where the first feature is a feature of data processed by using the first AI model, and the first data is used for drawing inferences for decision-making of the first task.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOHAMED A KAMARA whose telephone number is (571)270-5629. The examiner can normally be reached M-F 9AM-4PM.
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, CHARLES JIANG can be reached on 5712707191. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/MOHAMED A KAMARA/Primary Examiner, Art Unit 2412