DETAILED ACTION
Status of Claims:
Claims 1 – 20 are pending.
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 .
Information Disclosure Statement
The information disclosure statement (IDS) was submitted on 02/18/2025. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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.
Claim(s) 1 – 20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Bhamri (US 12317297).
As per claim 1, an artificial intelligence (AI) model processing method, comprising:
determining, by a first node, a first AI model (Generating a capability report indicating artificial intelligence enabled features of a first node … the capability report including: one or more supported AI model types, See Col. 18, Line 48 – Col. 19, Line 7); and
sending, by the first node, first information indicating model information of the first Al model and auxiliary information of the first Al model (The capability report (model information) including: one or more supported AI model types (auxiliary information) … Communicating the generated capability report to a second node, See Col. 18, Line 48 – Col. 19, Line 7).
As per claim 2, the method according to claim 1, wherein the auxiliary information of the first Al model comprises one or more of:
type information of the first Al model (The capability report including: one or more supported AI model types, See Col. 18, Line 48 – Col. 19, Line 7),
identification information of the first node (Alternative language “one or more of”, does not require prior art citation),
identification information of a receiving node of the first Al model (Alternative language “one or more of”, does not require prior art citation),
version information of the first Al model (Alternative language “one or more of”, does not require prior art citation),
time information for generating the first Al model (Alternative language “one or more of”, does not require prior art citation),
geographical location information for generating the first Al model (Alternative language “one or more of”, does not require prior art citation), or
distribution information, of local data, of the first node (Alternative language “one or more of”, does not require prior art citation).
As per claim 3, the method according to claim 1, wherein the model information, of the first Al model, is carried on a first transmission resource, and the auxiliary information, of the first Al model, is carried on a second transmission resource (An application mode, for instance, represents a mode in which an AI model (e.g., algorithm) is applied to radio frequency signal transmitted and/or received by a transceiver, such as to optimize signal quality of transmitted and/or received signal. The application mode notification 800 includes an application mode field 802 that is configurable to indicate different AI application modes that are supported or not supported, See Col. 12, Lines 19 - 49).
As per claim 4, the method according to claim 1, wherein the first AI model is associated with a node type of the first node (Generating a capability report indicating artificial intelligence enabled features of a first node … the capability report including: one or more supported AI model types, See Col. 18, Line 48 – Col. 19, Line 7).
As per claim 5, the method according to claim 4, wherein
the first AI model is associated with a second AI model and the node type of the first node; and
the second AI model is associated with one or more of:
local data (Federated learning utilizes training across multiple model nodes that contain local data, See Col. 11, Lines 4 - 27);
K pieces of information, wherein each of the K pieces of information indicates model information of an Al model of another node and auxiliary information of the Al model of the another node, and K is a positive integer (Alternative language “one or more of”, does not require prior art citation); or
the local data and the K pieces of information (Alternative language “one or more of”, does not require prior art citation).
As per claim 6, the method according to claim 5, wherein the node type comprises one or more of:
a node type of performing local training based on the local data (Federated learning utilizes training across multiple model nodes that contain local data, See Col. 11, Lines 4 - 27),
a node type of performing merging processing based on the AI model of the another node (Alternative language “one or more of”, does not require prior art citation), and
a node type of performing local training based on the local data and performing merging processing based on the AI model of the another node (Alternative language “one or more of”, does not require prior art citation).
As per claim 7, the method according to claim 4, further comprising: sending, by the first node, indication information indicating the node type of the first node (Generating a capability report indicating artificial intelligence enabled features of a first node … the capability report including: one or more supported AI model types, See Col. 18, Line 48 – Col. 19, Line 7 … Communicating the generated capability report to a second node, See Col. 18, Line 48 – Col. 19, Line 7).
As per claim 8, the method according to claim 4, further comprising: determining, by the first node, the node type of the first node based on one or more of: capability information and requirement information (Generating a capability report indicating artificial intelligence enabled features of a first node … the capability report including: one or more supported AI model types, See Col. 18, Line 48 – Col. 19, Line 7).
As per claim 9, the method according to claim 4, further comprising: receiving, by the first node, indication information indicating the node type of the first node (The communication manager 1604 and/or other device components may be configured as or otherwise support a means for wireless communication at a device, including generating a capability report indicating artificial intelligence enabled features of a first node, See Col. 18, Line 48 – Col. 19, Line 7).
As per claim 10, the method according to claim 1, wherein the first Al model can be understood by M nodes in a system in which the first node is located, and M is an integer greater than or equal to 2 (Accordingly, by enabling network nodes to share information pertaining to AI capabilities of the nodes, the implementations described in this disclosure enable AI feature capabilities to be propagated among the network nodes. For instance, using the described implementations, various network nodes can quickly and efficiently identify AI-enabled features that are supported and to implement instances of the supported AI-enabled features such as for optimizing various aspects of wireless communication among the nodes, See Col. 4, Line 65 – Col. 5, Line 6).
As per claim 11, a communication apparatus, comprising:
at least one logic circuit; and
an input/output interface operatively coupled to the at least one logic circuit, wherein operation of the input/output interface and the at least one logic circuit causes the communication apparatus to:
determine a first artificial intelligence (AI) model (Generating a capability report indicating artificial intelligence enabled features of a first node … the capability report including: one or more supported AI model types, See Col. 18, Line 48 – Col. 19, Line 7); and
output first information indicating model information of the first AI model and auxiliary information of the first Al model (The capability report (model information) including: one or more supported AI model types (auxiliary information) … Communicating the generated capability report to a second node, See Col. 18, Line 48 – Col. 19, Line 7).
As per claim 12, the communication apparatus according to claim 11, wherein the auxiliary information of the first Al model comprises one or more of:
type information of the first Al model (The capability report including: one or more supported AI model types, See Col. 18, Line 48 – Col. 19, Line 7),
identification information of a node corresponding to the communication apparatus (Alternative language “one or more of”, does not require prior art citation),
identification information of a receiving node of the first Al model (Alternative language “one or more of”, does not require prior art citation),
version information of the first Al model, time information for generating the first AT model (Alternative language “one or more of”, does not require prior art citation),
geographical location information for generating the first AT model (Alternative language “one or more of”, does not require prior art citation), or
distribution information, of local data, of the node corresponding to the communication apparatus (Alternative language “one or more of”, does not require prior art citation).
As per claim 13, the communication apparatus according to claim 11, wherein the model information, of the first Al, model is carried on a first transmission resource, and the auxiliary information, of the first Al model, is carried on a second transmission resource (An application mode, for instance, represents a mode in which an AI model (e.g., algorithm) is applied to radio frequency signal transmitted and/or received by a transceiver, such as to optimize signal quality of transmitted and/or received signal. The application mode notification 800 includes an application mode field 802 that is configurable to indicate different AI application modes that are supported or not supported, See Col. 12, Lines 19 - 49).
As per claim 14, the communication apparatus according to claim 11, wherein the first Al model is associated with a node type corresponding to the communication apparatus (Generating a capability report indicating artificial intelligence enabled features of a first node … the capability report including: one or more supported AI model types, See Col. 18, Line 48 – Col. 19, Line 7).
As per claim 15, the communication apparatus according to claim 14, wherein the first Al model is associated with a second AI model and the node type; and
the second Al model is associated with one or more of local data (Federated learning utilizes training across multiple model nodes that contain local data, See Col. 11, Lines 4 - 27);
K pieces of information, wherein each of the K pieces of information indicates model information of an Al model of another node and auxiliary information of the Al model of the another node, and K is a positive integer (Alternative language “one or more of”, does not require prior art citation); or
the local data and the K pieces of information (Alternative language “one or more of”, does not require prior art citation).
As per claim 16, the communication apparatus according to claim 15, wherein the node type comprises one or more of:
a node type of performing local training based on the local data (Federated learning utilizes training across multiple model nodes that contain local data, See Col. 11, Lines 4 - 27),
a node type of performing merging processing based on the Al model of the another node (Alternative language “one or more of”, does not require prior art citation), and
a node type of performing local training based on the local data and performing merging processing based on the AI model of the another node (Alternative language “one or more of”, does not require prior art citation).
As per claim 17, the communication apparatus according to claim 14, wherein the communication apparatus is further caused to send indication information indicating the node type corresponding to the apparatus (Generating a capability report indicating artificial intelligence enabled features of a first node … the capability report including: one or more supported AI model types, See Col. 18, Line 48 – Col. 19, Line 7 … Communicating the generated capability report to a second node, See Col. 18, Line 48 – Col. 19, Line 7).
As per claim 18, the communication apparatus according to claim 14, wherein the communication apparatus is further caused to:
determine, based on capability information and/or requirement information (Generating a capability report indicating artificial intelligence enabled features of a first node … the capability report including: one or more supported AI model types, See Col. 18, Line 48 – Col. 19, Line 7),
the node type of the node corresponding to the communication apparatus (Alternative language “one or more of”, does not require prior art citation); or
receive indication information indicating the node type of the node corresponding to the communication apparatus (Alternative language “one or more of”, does not require prior art citation).
As per claim 19, the communication apparatus according to claim 11, wherein the first AI model can be understood by M nodes in a system in which the node corresponding to the communication apparatus is located, and M is an integer greater than or equal to 2 (Accordingly, by enabling network nodes to share information pertaining to AI capabilities of the nodes, the implementations described in this disclosure enable AI feature capabilities to be propagated among the network nodes. For instance, using the described implementations, various network nodes can quickly and efficiently identify AI-enabled features that are supported and to implement instances of the supported AI-enabled features such as for optimizing various aspects of wireless communication among the nodes, See Col. 4, Line 65 – Col. 5, Line 6).
As per claim 20, a non-transitory computer-readable storage medium storing instructions that, when executed by a computer, cause the computer to provide execution comprising:
determining a first artificial intelligence (AI) model (Generating a capability report indicating artificial intelligence enabled features of a first node … the capability report including: one or more supported AI model types, See Col. 18, Line 48 – Col. 19, Line 7); and
sending first information indicating model information of the first Al model and auxiliary information of the first Al model (The capability report (model information) including: one or more supported AI model types (auxiliary information) … Communicating the generated capability report to a second node, See Col. 18, Line 48 – Col. 19, Line 7).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NAZIA NAOREEN whose telephone number is (571)270-7282. The examiner can normally be reached M-F: 9:00 - 6:00.
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/NAZIA NAOREEN/ Primary Examiner, Art Unit 2458
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