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 .
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 1-17, 19-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to judicial exception(s) without significantly more.
[STEP 1] The claim recites at least one step or structure. Thus, the claim is to a process or product, which is one of the statutory categories of invention (Step 1: YES).
[STEP2A PRONG I] The claim(s) 1 and 17 recite(s):
A method for agent training using generative artificial intelligence and machine learning, the method comprising:
retrieving, by a computing system, original training content for contact center agents;
analyzing, by the computing system, the original training content using machine learning based on agent characteristics of a particular agent to determine target content characteristics for training content customized to the particular agent;
generating, by the computing system, custom agent training content using a generative artificial intelligence system based on the original training content and the target content characteristics;
providing, by the computing system, a virtual training session for the particular agent using the generated custom agent training content;
receiving, by the computing system, results data associated with the particular agent's completion of the virtual training session; and
updating, by the computing system, an artificial intelligence model leveraged by the machine learning based on the results data.
The non-highlighted aforementioned limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation between people but for the recitation of generic computer components. That is, other than reciting “computing system”, “generative artificial intelligence” and “machine learning” nothing in the claim element precludes the step from practically being performed between people. For example, but for the recited language, the step in the context of this claim encompasses a teacher observing students’ behaviors and adjusting its instruction/lecture level accordingly.
If a claim limitation, under its broadest reasonable interpretation, covers managing interactions between people, then it falls within the “Organization of Human Activity” grouping of abstract ideas.
Accordingly, the claim recites a judicial exception, and the analysis must therefore proceed to Step 2A Prong Two.
[STEP2A PRONG II] This judicial exception is not integrated into a practical application. In particular, the claim only recites the additional element(s) – “computing system”, “generative artificial intelligence” and “machine learning”.
The “computing system”, “generative artificial intelligence” and “machine learning”in the aforementioned steps are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component.
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea and the claim is therefore directed to the judicial exception. (Step 2A: YES).
[STEP2B] The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor to perform the aforementioned steps amounts to no more than mere instructions to apply the exception using a generic computer component, which cannot provide an inventive concept (for example, see paragraph 42-43 and 58).
As noted previously, the claim as a whole merely describes how to generally “apply” the aforementioned concept in a computer environment. Thus, even when viewed as a whole, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea.
The claim is not patent eligible. (Step 2B: NO).
Claim(s) 2-16 and 18-20 are dependent on supra claim(s) and includes all the limitations of the claim(s). Therefore, the dependent claim(s) recite(s) the same abstract idea. For example, claims 2-4 and 18-19 are directed toward type input directed to the neural networks (a technological environment), claims 5-16 and 20 are directed to the training content and determining the type training content to be presented to the user (abstract idea). These claims recite no additional limitations. Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea and the claim is therefore directed to the judicial exception. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Thus, even when viewed as a whole, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea.
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 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Truong US 20200111377
Claims 1 and 17: The Truong reference provides a teaching of a method for agent training using generative artificial intelligence and machine learning (see col. 2:20-30 LLM), the method comprising:
The Truong reference provides a teaching of retrieving, by a computing system, original training content for contact center agents (see paragraph 121);
analyzing, by the computing system, the original training content using machine learning based on agent characteristics of a particular agent to determine target content characteristics for training content customized to the particular agent (see paragraph 72);
generating, by the computing system, custom agent training content using a generative artificial intelligence system based on the original training content and the target content characteristics (see paragraph 69);
providing, by the computing system, a virtual training session for the particular agent using the generated custom agent training content; receiving, by the computing system, results data associated with the particular agent’s completion of the virtual training session (see paragraph 85);
and updating, by the computing system, an artificial intelligence model leveraged by the machine learning based on the results data (see paragraph 83)
Claim 4: The Truong reference provides a teaching of receiving, by the computing system, additional results data associated with a plurality of other agents’ completion of respective virtual training sessions (see paragraph 85); and
wherein updating the artificial intelligence model leveraged by the machine learning comprises updating the artificial intelligence model leveraged by the machine learning based on the results data and the additional results data.
Claim Rejections - 35 USC § 103
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.
Claims 2-3 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Truong US 20200111377 and in view of Stoops 20230080724
Claims 2-3 and 18: The Truong reference is silent on the teaching of wherein to analyze the original training content using machine learning comprises to analyze the original training content using a neural network; wherein to update the artificial intelligence model leveraged by the machine learning comprises to update weights of the neural network based on the results data; and wherein each of the agent characteristics is an input for the neural network.
However, the Stoops reference provides a teaching of wherein to analyze the original training content using machine learning comprises to analyze the original training content using a neural network (see paragraph 74); wherein to update the artificial intelligence model leveraged by the machine learning comprises to update weights of the neural network based on the results data (see paragraph 70); and wherein each of the agent characteristics is an input for the neural network (see paragraph 71).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the Truong module with the feature of wherein to analyze the original training content using machine learning comprises to analyze the original training content using a neural network; wherein to update the artificial intelligence model leveraged by the machine learning comprises to update weights of the neural network based on the results data; and wherein each of the agent characteristics is an input for the neural network, as taught by Stoops reference, in order to provide the user with a realistic training environment.
Claims 5 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Truong US 20200111377 and in view of Kasaba US 11582424
Claims 5 and 19: The Truong reference is silent on the teaching of wherein to generate the custom agent training content using the generative artificial intelligence system comprises to: generate textual content with tags based on the analysis of the original training content using the machine learning; select a vocal avatar based on the agent characteristics of the particular agent; and perform text-to-speech processing on the textual content with tags to generate audio content based on the selected vocal avatar.
However, the Kasaba reference provide a teaching of wherein to generate the custom agent training content using the generative artificial intelligence system comprises to:
generate textual content with tags based on the analysis of the original training content using the machine learning (see col. 28:20-25)
select a vocal avatar based on the agent characteristics of the particular agent (see col. 14:22-30)
perform text-to-speech processing on the textual content with tags to generate audio content based on the selected vocal avatar (see col. 13:30-40)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the with the feature of teaching of wherein to generate the custom agent training content using the generative artificial intelligence system comprises to: generate textual content with tags based on the analysis of the original training content using the machine learning; select a vocal avatar based on the agent characteristics of the particular agent; and perform text-to-speech processing on the textual content with tags to generate audio content based on the selected vocal avatar, as taught by Kasaba reference, in order to provide the user with a realistic training environment.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ROBERT J UTAMA whose telephone number is (571)272-1676. The examiner can normally be reached 9:00 - 17:30 Monday - Friday.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kang Hu can be reached at (571)270-1344. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ROBERT J UTAMA/Primary Examiner, Art Unit 3715
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