APPARATUS AND METHODS FOR MACHINE LEARNING WITH LOW TRAINING DELAY AND COMMUNICATION OVERHEAD

§101 §102 §103 §112

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 § 101 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Claim 1 Step 1: Is the claim to a process, machine, manufacture, or composition of matter? Yes. Claim 1 is drawn to a process. Step 2A, Prong One: Does the claim recite an abstract idea, law of nature, or natural phenomenon? Yes. Claim 1 recites the following abstract ideas: “determining an artificial intelligence or machine learning (AI/ML) model training capability of a first device, the AI/ML model training capability being indicative of a capability of the first device to contributively participate in an AI/ML model training process with at least a second device in a wireless communication network” - This constitutes a concept performed in the human mind, such as an observation, evaluation, judgement, and/or opinion. Furthermore, the courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). See MPEP 2106.04(a)(2). “the AI/ML model training capability being determined based on at least one of: i) a current processing capability of the first device; ii) a current volume of training data available for the AI/ML model training process at the first device; or iii) a sensing capacity of the first device to collect the training data for the AI/ML model training process.” – A human can make the claimed determination given this information, i.e. this constitutes a concept performed in the human mind, such as an observation, evaluation, judgement, and/or opinion. Furthermore, the courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). See MPEP 2106.04(a)(2). Step 2A, Prong Two: Does the claim recite additional elements that integrate the judicial exception into a practical application? No. Claim 1 recites the following additional elements: “transmitting the AI/ML model training capability to the second device” - This amounts to insignificant extra solution activity in the form of mere data gathering, see MPEP 2106.05(g) and MPEP 2106.05(d), II, (i), regarding receiving or transmitting data. Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. Claim 1 recites the following additional elements: “transmitting the AI/ML model training capability to the second device” - This amounts to insignificant extra solution activity in the form of mere data gathering, see MPEP 2106.05(g) and MPEP 2106.05(d), II, (i), regarding receiving or transmitting data. Claim 2 Step 1: Is the claim to a process, machine, manufacture, or composition of matter? Yes. Claim 2 is drawn to a process. Step 2A, Prong One: Does the claim recite an abstract idea, law of nature, or natural phenomenon? Yes. Claim 2 recites the following abstract ideas: “determining the AI/ML model training capability of the first device has changed” - This constitutes a concept performed in the human mind, such as an observation, evaluation, judgement, and/or opinion. Furthermore, the courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). See MPEP 2106.04(a)(2). Step 2A, Prong Two: Does the claim recite additional elements that integrate the judicial exception into a practical application? No. Claim 2 recites the following additional elements: “transmitting the AI/ML model training capability to the second device after the determining the AI/ML model training capability of the first device has changed” - This amounts to insignificant extra solution activity in the form of mere data gathering, see MPEP 2106.05(g) and MPEP 2106.05(d), II, (i), regarding receiving or transmitting data. Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. Claim 2 recites the following additional elements: “transmitting the AI/ML model training capability to the second device after the determining the AI/ML model training capability of the first device has changed” - This amounts to insignificant extra solution activity in the form of mere data gathering, see MPEP 2106.05(g) and MPEP 2106.05(d), II, (i), regarding receiving or transmitting data. Claim 3 Step 1: Is the claim to a process, machine, manufacture, or composition of matter? Yes. Claim 3 is drawn to a process. Step 2A, Prong One: Does the claim recite an abstract idea, law of nature, or natural phenomenon? Yes. Claim 3 recites the following abstract ideas: “determining the AI/ML model training capability of the first device has changed comprises identifying a change in at least one of: i) the current processing capability of the first device; ii) the current volume of the training data available for the AI/ML model training process at the first device; or iii) the sensing capacity of the first device to collect the training data for the AI/ML model training process.” - This constitutes a concept performed in the human mind, such as an observation, evaluation, judgement, and/or opinion. Furthermore, the courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). See MPEP 2106.04(a)(2). Step 2A, Prong Two: Does the claim recite additional elements that integrate the judicial exception into a practical application? No. Claim 3 does not recite any additional elements. Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. Claim 3 does not recite any additional elements. Claim 4 Step 1: Is the claim to a process, machine, manufacture, or composition of matter? Yes. Claim 4 is drawn to a process. Step 2A, Prong One: Does the claim recite an abstract idea, law of nature, or natural phenomenon? Yes. Claim 4 recites the following abstract ideas: the abstract ideas of claim 1 Step 2A, Prong Two: Does the claim recite additional elements that integrate the judicial exception into a practical application? No. Claim 4 recites the following additional elements: “receiving, from the second device, control signaling indicating a rule for determining, for an iteration of the AI/ML model training process, whether the first device is to participate in the iteration” - This amounts to insignificant extra solution activity in the form of mere data gathering, see MPEP 2106.05(g) and MPEP 2106.05(d), II, (i), regarding receiving or transmitting data. Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. Claim 4 recites the following additional elements: “receiving, from the second device, control signaling indicating a rule for determining, for an iteration of the AI/ML model training process, whether the first device is to participate in the iteration” - This amounts to insignificant extra solution activity in the form of mere data gathering, see MPEP 2106.05(g) and MPEP 2106.05(d), II, (i), regarding receiving or transmitting data. Claim 5 Step 1: Is the claim to a process, machine, manufacture, or composition of matter? Yes. Claim 5 is drawn to a process. Step 2A, Prong One: Does the claim recite an abstract idea, law of nature, or natural phenomenon? Yes. Claim 5 recites the following abstract ideas: the abstract ideas of claim 1 Step 2A, Prong Two: Does the claim recite additional elements that integrate the judicial exception into a practical application? No. Claim 5 recites the following additional elements: “an iteration of the AI/ML model training process is associated with a respective value of an iteration identifier (ID) such that the respective value of the iteration ID is incremented by one for each subsequent iteration; and the control signaling indicates to the first device to selectively participate in a given iteration based on the respective value of the iteration ID associated with the given iteration.” - This amounts to insignificant extra solution activity in the form of mere data gathering, see MPEP 2106.05(g) and MPEP 2106.05(d), II, (i), regarding receiving or transmitting data. Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. Claim 5 recites the following additional elements: “an iteration of the AI/ML model training process is associated with a respective value of an iteration identifier (ID) such that the respective value of the iteration ID is incremented by one for each subsequent iteration; and the control signaling indicates to the first device to selectively participate in a given iteration based on the respective value of the iteration ID associated with the given iteration.” - This amounts to insignificant extra solution activity in the form of mere data gathering, see MPEP 2106.05(g) and MPEP 2106.05(d), II, (i), regarding receiving or transmitting data. Claim 6 Step 1: Is the claim to a process, machine, manufacture, or composition of matter? Yes. Claim 6 is drawn to a process. Step 2A, Prong One: Does the claim recite an abstract idea, law of nature, or natural phenomenon? Yes. Claim 6 recites the following abstract ideas: the abstract ideas of claim 1 Step 2A, Prong Two: Does the claim recite additional elements that integrate the judicial exception into a practical application? No. Claim 6 recites the following additional elements: “transmission, from the second device, of data or control information for a given iteration of the AI/ML model training process is scheduled by first downlink control information (DCI), wherein a cyclic redundancy check (CRC) value of the first DCI is scrambled with a first radio network temporary identifier (RNTI), the method further comprising: receiving, from the second device, control signaling to indicate to the first device to monitor for the first DCI in accordance with a first monitoring periodicity” - This amounts to insignificant extra solution activity in the form of mere data gathering, see MPEP 2106.05(g) and MPEP 2106.05(d), II, (i), regarding receiving or transmitting data. Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. Claim 6 recites the following additional elements: “transmission, from the second device, of data or control information for a given iteration of the AI/ML model training process is scheduled by first downlink control information (DCI), wherein a cyclic redundancy check (CRC) value of the first DCI is scrambled with a first radio network temporary identifier (RNTI), the method further comprising: receiving, from the second device, control signaling to indicate to the first device to monitor for the first DCI in accordance with a first monitoring periodicity” - This amounts to insignificant extra solution activity in the form of mere data gathering, see MPEP 2106.05(g) and MPEP 2106.05(d), II, (i), regarding receiving or transmitting data. Claim 7 Step 1: Is the claim to a process, machine, manufacture, or composition of matter? Yes. Claim 7 is drawn to a process. Step 2A, Prong One: Does the claim recite an abstract idea, law of nature, or natural phenomenon? Yes. Claim 7 recites the following abstract ideas: “determine, for each iteration of the AI/ML model training process, whether the first device is to participate in the iteration” - This constitutes a concept performed in the human mind, such as an observation, evaluation, judgement, and/or opinion. Furthermore, the courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). See MPEP 2106.04(a)(2). Step 2A, Prong Two: Does the claim recite additional elements that integrate the judicial exception into a practical application? No. Claim 7 recites the following additional elements: “receiving an artificial intelligence or machine learning (AI/ML) model training capability from a first device, the AI/ML model training capability from the first device being indicative of a capability of the first device to contributively participate in an AI/ML model training process with at least a second device in a wireless communication network; and transmitting, based on the AI/ML model training capability received from the first device, information” - This amounts to insignificant extra solution activity in the form of mere data gathering, see MPEP 2106.05(g) and MPEP 2106.05(d), II, (i), regarding receiving or transmitting data. Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. Claim 7 recites the following additional elements: “receiving an artificial intelligence or machine learning (AI/ML) model training capability from a first device, the AI/ML model training capability from the first device being indicative of a capability of the first device to contributively participate in an AI/ML model training process with at least a second device in a wireless communication network; and transmitting, based on the AI/ML model training capability received from the first device, information” - This amounts to insignificant extra solution activity in the form of mere data gathering, see MPEP 2106.05(g) and MPEP 2106.05(d), II, (i), regarding receiving or transmitting data. Claim 8 Step 1: Is the claim to a process, machine, manufacture, or composition of matter? Yes. Claim 8 is drawn to a process. Step 2A, Prong One: Does the claim recite an abstract idea, law of nature, or natural phenomenon? Yes. Claim 8 recites the following abstract ideas: The abstract ideas of claim 7. Step 2A, Prong Two: Does the claim recite additional elements that integrate the judicial exception into a practical application? No. Claim 8 does not recite any additional elements but merely further describes what data is included in the AI/ML model training capability. Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. Claim 8 does not recite any additional elements but merely further describes what data is included in the AI/ML model training capability. Claim 9 Step 1: Is the claim to a process, machine, manufacture, or composition of matter? Yes. Claim 9 is drawn to a process. Step 2A, Prong One: Does the claim recite an abstract idea, law of nature, or natural phenomenon? Yes. Claim 9 recites the following abstract ideas: The abstract ideas of claim 7 Step 2A, Prong Two: Does the claim recite additional elements that integrate the judicial exception into a practical application? No. Claim 9 recites the following additional elements: “ receiving a respective AI/ML model training capability from each device of a plurality of devices, the plurality of devices including the first device; and wherein the transmitting, based on the AI/ML model training capability received from the first device, the information comprises: transmitting, based on the respective AI/ML model training capability received from each device of the plurality of devices, information enabling each device of the plurality of devices to determine, for the each iteration of the AI/ML model training process, whether the each device is to participate in the each iteration.” - This amounts to insignificant extra solution activity in the form of mere data gathering, see MPEP 2106.05(g) and MPEP 2106.05(d), II, (i), regarding receiving or transmitting data. Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. Claim 9 recites the following additional elements: “ receiving a respective AI/ML model training capability from each device of a plurality of devices, the plurality of devices including the first device; and wherein the transmitting, based on the AI/ML model training capability received from the first device, the information comprises: transmitting, based on the respective AI/ML model training capability received from each device of the plurality of devices, information enabling each device of the plurality of devices to determine, for the each iteration of the AI/ML model training process, whether the each device is to participate in the each iteration.” - This amounts to insignificant extra solution activity in the form of mere data gathering, see MPEP 2106.05(g) and MPEP 2106.05(d), II, (i), regarding receiving or transmitting data. Claim 10 Step 1: Is the claim to a process, machine, manufacture, or composition of matter? Yes. Claim 10 is drawn to a process. Step 2A, Prong One: Does the claim recite an abstract idea, law of nature, or natural phenomenon? Yes. Claim 10 recites the following abstract ideas: The abstract ideas of claim 7 Step 2A, Prong Two: Does the claim recite additional elements that integrate the judicial exception into a practical application? No. Claim 10 recites the following additional elements: “ transmitting control signaling for the each device of the plurality of devices to indicate to the each device of the plurality of devices with a respective device-specific rule for determining, for the each iteration of the AI/ML model training process, whether the each device is to participate in the each iteration.” - This amounts to insignificant extra solution activity in the form of mere data gathering, see MPEP 2106.05(g) and MPEP 2106.05(d), II, (i), regarding receiving or transmitting data. Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. Claim 10 recites the following additional elements: “ transmitting control signaling for the each device of the plurality of devices to indicate to the each device of the plurality of devices with a respective device-specific rule for determining, for the each iteration of the AI/ML model training process, whether the each device is to participate in the each iteration.” - This amounts to insignificant extra solution activity in the form of mere data gathering, see MPEP 2106.05(g) and MPEP 2106.05(d), II, (i), regarding receiving or transmitting data. Claim 11 Step 1: Is the claim to a process, machine, manufacture, or composition of matter? Yes. Claim 11 is drawn to a process. Step 2A, Prong One: Does the claim recite an abstract idea, law of nature, or natural phenomenon? Yes. Claim 11 recites the following abstract ideas: The abstract ideas of claim 7 Step 2A, Prong Two: Does the claim recite additional elements that integrate the judicial exception into a practical application? No. Claim 11 recites the following additional elements: “ transmitting first downlink control information (DCI) containing first scheduling information for scheduling transmission of data or control information for a given iteration of the AI/ML model training process, wherein a cyclic redundancy check (CRC) value of the first DCI is scrambled with a first radio network temporary identifier (RNTI); and transmitting control signaling to indicate to the first device to monitor for the first DCI in accordance with a first monitoring periodicity.” - This amounts to insignificant extra solution activity in the form of mere data gathering, see MPEP 2106.05(g) and MPEP 2106.05(d), II, (i), regarding receiving or transmitting data. Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. Claim 11 recites the following additional elements: “transmitting first downlink control information (DCI) containing first scheduling information for scheduling transmission of data or control information for a given iteration of the AI/ML model training process, wherein a cyclic redundancy check (CRC) value of the first DCI is scrambled with a first radio network temporary identifier (RNTI); and transmitting control signaling to indicate to the first device to monitor for the first DCI in accordance with a first monitoring periodicity.” - This amounts to insignificant extra solution activity in the form of mere data gathering, see MPEP 2106.05(g) and MPEP 2106.05(d), II, (i), regarding receiving or transmitting data. Claims 12-21 Claims 12-21 are ineligible for the same reasons as their counterpart claims of claims 1-11. The additional elements of “a device” and “at least one processor coupled with a memory storing processor-executable instructions that, when executed, cause the device to perform operations” do not integrate the abstract idea(s) into a practical application or provide simply more because they constitute mere instructions to implement the abstract idea on a computer, i.e. to ”apply it”, see MPEP 2106.05(f). 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 1-21 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. Regarding claims 1, 7, 12, and 17 “contributively participate” renders the claim indefinite because it is unclear what level of participation constitutes “contributive” participation. For examination purposes any participation at any amount or level above “none” or “zero” is considered “contributive”. Claims 2-6, 8-11, 13-16, and 18-21 are indefinite by virtue of dependency on an indefinite 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)(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. Claim(s) 1-4, 7-10, 12-15, and 17-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Nishio (T. Nishio and R. Yonetani, "Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge," ICC 2019 - 2019 IEEE International Conference on Communications (ICC), Shanghai, China, 2019, pp. 1-7, doi: 10.1109/ICC.2019.8761315.) Regarding claim 1, Nishio teaches a method, comprising: determining an artificial intelligence or machine learning (AI/ML) model training capability of a first device, the AI/ML model training capability being indicative of a capability of the first device to contributively participate in an AI/ML model training process with at least a second device in a wireless communication network (Protocol 2, reproduced below, Steps 2-3, Resource Request and Client Selection, which further includes “First, the new Resource Request step asks random clients to inform the MEC of their resource information such as wireless channel states, computational capacities (e.g., if they can spare CPUs or GPUs for updating models)…[determining an artificial intelligence or machine learning (AI/ML) model training capability of a first device, the AI/ML model training capability being indicative of a capability of the first device to contributively participate in an AI/ML model training process]” ““Federated learning with Client Selection” […to contributively participate in an AI/ML model training process with at least a second device], see Figure 1, reproduced below, “Base station” and “Cellular network” [in a wireless communication network], the AI/ML model training capability being determined based on at least one of: i) a current processing capability of the first device (§III, B, “First, the new Resource Request step asks random clients to inform the MEC of their resource information such as wireless channel states, computational capacities (e.g., if they can spare CPUs or GPUs for updating models)…[current processing capability of the first device]”); ii) a current volume of training data available for the AI/ML model training process at the first device (§III, B, “…and the size of data resources relevant to the current training task (e.g., if the server is going to train a ‘god-vs-cat’ classifier, the number of images containing dogs or cats) [a current volume of training data available for the AI/ML model training process at the first device]); or iii) a sensing capacity of the first device to collect the training data for the AI/ML model training process; and transmitting the AI/ML model training capability to the second device (Protocol 2, step 2). PNG media_image1.png 822 802 media_image1.png Greyscale PNG media_image2.png 542 826 media_image2.png Greyscale Regarding claim 2, Nishio teaches all of the limitations of claim 1, wherein the transmitting the AI/ML model training capability to the second device comprises: determining the AI/ML model training capability of the first device has changed; and transmitting the AI/ML model training capability to the second device after the determining the AI/ML model training capability of the first device has changed (Protocol 2, Step 7, where Steps 2-3 are repeated and therefore an instance where capability has changed between iterations the methodology of claim 2 results). Regarding claim 3, Nishio teaches all of the limitations of claim 1, wherein the determining the AI/ML model training capability of the first device has changed comprises identifying a change in at least one of: i) the current processing capability of the first device (§III, B, “First, the new Resource Request step asks random clients to inform the MEC of their resource information such as wireless channel states, computational capacities (e.g., if they can spare CPUs or GPUs for updating models” – This could change between iterations in Nishio) ii) the current volume of the training data available for the AI/ML model training process at the first device (§III, B, “…and the size of data resources relevant to the current training task (e.g., if the server is going to train a ‘god-vs-cat’ classifier, the number of images containing dogs or cats)” - This could change between iterations in Nishio); or iii) the sensing capacity of the first device to collect the training data for the AI/ML model training process. Regarding claim 4, Nishio teaches all of the limitations of claim 1, further comprising: receiving, from the second device, control signaling indicating a rule for determining, for an iteration of the AI/ML model training process, whether the first device is to participate in the iteration (Protocol 2, step 3). Regarding claim 7, Nishio teaches a method, comprising: receiving an artificial intelligence or machine learning (AI/ML) model training capability from a first device, the AI/ML model training capability from the first device being indicative of a capability of the first device to contributively participate in an AI/ML model training process with at least a second device in a wireless communication network (Protocol 2, reproduced below, Steps 2-3, Resource Request and Client Selection, which further includes “First, the new Resource Request step asks random clients to inform the MEC of their resource information such as wireless channel states, computational capacities (e.g., if they can spare CPUs or GPUs for updating models); and transmitting, based on the AI/ML model training capability received from the first device, information enabling the first device to determine, for each iteration of the AI/ML model training process, whether the first device is to participate in the iteration (Protocol 2, Steps 3-4). Regarding claim 8, Nishio teaches all of the limitations of claim 7, wherein the AI/ML model training capability comprises at least one of: i) a current processing capability of the first device (§III, B, “First, the new Resource Request step asks random clients to inform the MEC of their resource information such as wireless channel states, computational capacities (e.g., if they can spare CPUs or GPUs for updating models)…[current processing capability of the first device]”); ii) a current volume of training data available for the AI/ML model training process at the first device (§III, B, “…and the size of data resources relevant to the current training task (e.g., if the server is going to train a ‘god-vs-cat’ classifier, the number of images containing dogs or cats) [a current volume of training data available for the AI/ML model training process at the first device]); or iii) a sensing capacity of the first device to collect the training data for the AI/ML model training process; Regarding claim 9, Nishio teaches all of the limitations of claim 7, wherein the receiving the AI/ML model training capability from the first device comprises: receiving a respective AI/ML model training capability from each device of a plurality of devices, the plurality of devices including the first device (Protocol 2, Steps 2-3); and wherein the transmitting, based on the AI/ML model training capability received from the first device, the information comprises: transmitting, based on the respective AI/ML model training capability received from each device of the plurality of devices, information enabling each device of the plurality of devices to determine, for the each iteration of the AI/ML model training process, whether the each device is to participate in the each iteration (Protocol 2, Steps 4-7). Regarding claim 10, Nishio teaches all of the limitations of claim 9, wherein the transmitting the information enabling the each device to determine, for the each iteration of the AI/ML model training process, whether the each device is to participate in the each iteration comprises: transmitting control signaling for the each device of the plurality of devices to indicate to the each device of the plurality of devices with a respective device-specific rule for determining, for the each iteration of the AI/ML model training process, whether the each device is to participate in the each iteration (Protocol 2, Steps 3-4). Regarding claim 12, Nishio teaches a device comprising: at least one processor coupled with a memory storing processor-executable instructions that, when executed, cause the device to perform operations (§IV, “As a proof-of-concept scenario to show how our protocol works effectively, we simulated a MEC environment and conducted experiments of realistic ML tasks using publicly available large-scale datasets…on a single workstation with GPUs”) and further teaches the claimed operations (see rejection of claim 1). Regarding claims 13-15, Nishio teaches all of the limitations of claims 13-15 (see rejections of claims 2-4 coupled with the hardware disclosed in the rejection of claim 12). Regarding claims 17-20, Nishio teaches the claimed operations (see rejections of claims 7-10) and the claimed hardware (see rejection of claim 12). 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. 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. Claim(s) 5, 16, and 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Nishio (T. Nishio and R. Yonetani, "Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge," ICC 2019 - 2019 IEEE International Conference on Communications (ICC), Shanghai, China, 2019, pp. 1-7, doi: 10.1109/ICC.2019.8761315.) in view of Sirdey (US20200394518A1). Regarding claims 5, 16, and 21, Nishio teaches all of the limitations of claims 4, 15, and 20 but does not teach wherein: an iteration of the AI/ML model training process is associated with a respective value of an iteration identifier (ID) such that the respective value of the iteration ID is incremented by one for each subsequent iteration; and the control signaling indicates to the first device to selectively participate in a given iteration based on the respective value of the iteration ID associated with the given iteration. Sirdey teaches wherein: an iteration of the AI/ML model training process is associated with a respective value of an iteration identifier (ID) such that the respective value of the iteration ID is incremented by one for each subsequent iteration (¶73-80, where “t” is established and at step 360 of Figure 3 “t” is updated to “t+1”, see ¶80); and the control signaling indicates to the first device to selectively participate in a given iteration based on the respective value of the iteration ID associated with the given iteration (¶81, where if a predetermined number of iterations T is reached, training stops and therefore any participation would cease). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Nishio to include “wherein: an iteration of the AI/ML model training process is associated with a respective value of an iteration identifier (ID) such that the respective value of the iteration ID is incremented by one for each subsequent iteration; and the control signaling indicates to the first device to selectively participate in a given iteration based on the respective value of the iteration ID associated with the given iteration.” in order to allow the system to determine when to stop training. Claim(s) 6 and 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Nishio (T. Nishio and R. Yonetani, "Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge," ICC 2019 - 2019 IEEE International Conference on Communications (ICC), Shanghai, China, 2019, pp. 1-7, doi: 10.1109/ICC.2019.8761315.) in view of Babaei (US20190149380A1). Regarding claims 6 and 11, Nishio teaches all of the limitations of claims 1 and 7, but does not teach wherein: transmission, from the second device, of data or control information for a given iteration of the AI/ML model training process is scheduled by first downlink control information (DCI), wherein a cyclic redundancy check (CRC) value of the first DCI is scrambled with a first radio network temporary identifier (RNTI), the method further comprising: receiving, from the second device, control signaling to indicate to the first device to monitor for the first DCI in accordance with a first monitoring periodicity. Babaei teaches wherein: transmission, from the second device, of data or control information for a given iteration of the AI/ML model training process is scheduled by first downlink control information (DCI) (Figure 21, “DCI”), wherein a cyclic redundancy check (CRC) value of the first DCI is scrambled with a first radio network temporary identifier (RNTI) (¶509, “[0509] FIG. 29 is a flow diagram of an aspect of an embodiment of the present disclosure. At 2910, a wireless device may receive configuration parameters. The configuration parameters may comprise a radio network temporary identifier. At 2920, a downlink control information and a cyclic redundancy check corresponding to the downlink control information may be received. The cyclic redundancy check may be based on a first value of a format identifier field in the downlink control information indicating a format of the downlink control information. The cyclic redundancy check may be based the radio network temporary identifier. At 2930, the wireless device may determine, the format based on the on the downlink control information and the cyclic redundancy check.”), the method further comprising: receiving, from the second device, control signaling to indicate to the first device to monitor for the first DCI in accordance with a first monitoring periodicity (Figure 21, “Monitoring perio[d]icity 1st parameter”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Nishio to include “wherein: transmission, from the second device, of data or control information for a given iteration of the AI/ML model training process is scheduled by first downlink control information (DCI), wherein a cyclic redundancy check (CRC) value of the first DCI is scrambled with a first radio network temporary identifier (RNTI), the method further comprising: receiving, from the second device, control signaling to indicate to the first device to monitor for the first DCI in accordance with a first monitoring periodicity.” in order to provide standardized communication over the wireless network. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to SCHYLER S SANKS whose telephone number is (571)272-6125. The examiner can normally be reached 06:30 - 15:30 Central Time, M-F. 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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. /SCHYLER S SANKS/Primary Examiner, Art Unit 2129