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 Objections
Claim 10 is objected to because of the following informalities: “The method of claim 5…” should read “The method of claim 9…” since the “response generation prompt received by the foundational model” is first recited in claim 9, and not in claim 5. Appropriate correction is required.
Claim 14 is objected to because of the following informalities: “further comprising displaying…” should read “further comprising: displaying…”. Appropriate correction is required.
Claims 15-19 are further objected to for dependence, either directly or indirectly, on claim 14.
Claims 21-22 are objected to because of the following informalities: “generating/generate a one or more responses to the first input query” should read “generating/generate one or more responses to the first input query”. Appropriate correction is required.
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 15-16 and 18-19 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.
The term “preferred metrics” in claims 15-16 and 18-19 is a relative term which renders the claim indefinite. The term “preferred metrics” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. It is unclear whether the metrics are preferred by the user, or are preferred according to another criterion. The term “metrics” has been rendered indefinite by the term “preferred”.
Claim 17 is further rejected for dependency on claim 16.
Examiners Notes: For the purposes of examination, “preferred metrics” will be interpreted as any metric being ranked above other metrics.
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 1-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding Claim 1,
Claim 1 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 1 is directed to a method for generating a response to an input query, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“determining one or more of characteristics of the input query”
“selecting, from a plurality of response modules, one or more response modules based on the one or more characteristics of the input query and one or more metrics associated with each of the one or more response modules, wherein each response module of the plurality of response modules comprises a plurality of machine learning models for generating a response to the input query”
“generating one or more responses to the first input query”
As drafted, under their broadest reasonable interpretations, cover mental processes,
i.e., concepts performed in the human mind (including an observation, evaluation,
judgement, opinion). The above limitations in the context of this claim correspond to
mental processes, e.g., evaluation and judgement with assistance of pen and paper.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recites additional elements that are mere instructions to apply an exception for the abstract ideas (See MPEP 2106.05(f)), and insignificant extra-solution activity (See MPEP 2106.05(g)).
The limitations:
“…using the selected one or more response modules”
As drafted, are additional elements that amount to no more than mere instructions to apply an exception for the abstract ideas. See MPEP 2106.05(f).
The limitations:
“receiving a first input query”
As drafted, are additional elements that amount to no more than insignificant extra-solution activity. See MPEP 2106.05(g).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: 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, all of the additional elements are “mere instructions to apply an exception” and “insignificant extra-solution activity”. Specifically, the receiving limitation recites the well-understood, routine, and conventional activity of receiving and transmitting data over a network. MPEP 2106.05(d)(II); OIP Techs., Inc v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network). Mere instructions to apply an exception and insignificant extra-solution activity cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 2,
Claim 2 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 2 is directed to a method for generating a response to an input query, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: See corresponding analysis of claim 1.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are additional details that do not apply the exception in a meaningful way (See MPEP 2106.05(e)).
The limitations:
“wherein the one or more characteristics of the input query are associated with any one or more of a user, a user segment, or use case”
As drafted, are additional elements that do not apply an exception for the abstract ideas in a meaningful way. See MPEP 2106.05(e).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: 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 the integration of the abstract ideas into a practical application, all of the additional elements do not apply the exception in a meaningful way. Additional details that do not apply the exception in a meaningful way cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 3,
Claim 3 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 3 is directed to a method for generating a response to an input query, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: See corresponding analysis of claim 2.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are additional details that do not apply the exception in a meaningful way (See MPEP 2106.05(e)).
The limitations:
“wherein the one or more response modules are selected based on a user segment or use case associated with the input query”
As drafted, are additional elements that do not apply an exception for the abstract ideas in a meaningful way. See MPEP 2106.05(e).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: 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 the integration of the abstract ideas into a practical application, all of the additional elements do not apply the exception in a meaningful way. Additional details that do not apply the exception in a meaningful way cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 4,
Claim 4 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 4 is directed to a method for generating a response to an input query, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: See corresponding analysis of claim 1.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are additional details that do not apply the exception in a meaningful way (See MPEP 2106.05(e)).
The limitations:
“wherein the one or more responses to the first input query generated using the selected one or more response modules are tailored to a user segment and a use case”
As drafted, are additional elements that do not apply an exception for the abstract ideas in a meaningful way. See MPEP 2106.05(e).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: 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 the integration of the abstract ideas into a practical application, all of the additional elements do not apply the exception in a meaningful way. Additional details that do not apply the exception in a meaningful way cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 5,
Claim 5 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 5 is directed to a method for generating a response to an input query, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: See corresponding analysis of claim 1.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are additional details that do not apply the exception in a meaningful way (See MPEP 2106.05(e)).
The limitations:
“wherein the plurality of machine learning models in each respective response module comprises each of a foundational language model, one or more adapter models, one or more retrieval models, and a prompting optimization model”
As drafted, are additional elements that do not apply an exception for the abstract ideas in a meaningful way. See MPEP 2106.05(e).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: 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 the integration of the abstract ideas into a practical application, all of the additional elements do not apply the exception in a meaningful way. Additional details that do not apply the exception in a meaningful way cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 6,
Claim 6 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 6 is directed to a method for generating a response to an input query, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“modify an input to the foundational model”
As drafted, under their broadest reasonable interpretations, cover mental processes,
i.e., concepts performed in the human mind (including an observation, evaluation,
judgement, opinion). The above limitations in the context of this claim correspond to
mental processes, e.g., evaluation and judgement with assistance of pen and paper.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are mere instructions to apply an exception (See MPEP 2106.05(f)).
The limitations:
“wherein an adapter model of the one or more adapter models and a retrieval model of the one or more retrieval models are provided upstream of the foundational model to…”
As drafted, are additional elements that amount to no more than mere instructions to apply an exception for the abstract ideas. See MPEP 2106.05(f).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: 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 the integration of the abstract ideas into a practical application, all of the additional elements are “mere instructions to apply”. Mere instructions to apply an exception cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 7,
Claim 7 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 7 is directed to a method for generating a response to an input query, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“modify an output from the foundational model”
As drafted, under their broadest reasonable interpretations, cover mental processes,
i.e., concepts performed in the human mind (including an observation, evaluation,
judgement, opinion). The above limitations in the context of this claim correspond to
mental processes, e.g., evaluation and judgement with assistance of pen and paper.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are mere instructions to apply an exception (See MPEP 2106.05(f)).
The limitations:
“wherein an adapter model of the one or more adapter models and a retrieval model of the one or more retrieval models are provided downstream of the foundational model to…”
As drafted, are additional elements that amount to no more than mere instructions to apply an exception for the abstract ideas. See MPEP 2106.05(f).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: 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 the integration of the abstract ideas into a practical application, all of the additional elements are “mere instructions to apply”. Mere instructions to apply an exception cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 8,
Claim 8 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 8 is directed to a method for generating a response to an input query, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“modify the first input query using static prompting and dynamic prompting to generate a response generation prompt for the foundational language model”
As drafted, under their broadest reasonable interpretations, cover mental processes,
i.e., concepts performed in the human mind (including an observation, evaluation,
judgement, opinion). The above limitations in the context of this claim correspond to
mental processes, e.g., evaluation and judgement with assistance of pen and paper.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are mere instructions to apply an exception (See MPEP 2106.05(f)).
The limitations:
“wherein the prompting optimization model is configured to…”
As drafted, are additional elements that amount to no more than mere instructions to apply an exception for the abstract ideas. See MPEP 2106.05(f).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: 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 the integration of the abstract ideas into a practical application, all of the additional elements are “mere instructions to apply”. Mere instructions to apply an exception cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 9,
Claim 9 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 9 is directed to a method for generating a response to an input query, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“modify the response generation prompt generated by the prompting optimization model before the response generation prompt is received by the foundational model”
As drafted, under their broadest reasonable interpretations, cover mental processes,
i.e., concepts performed in the human mind (including an observation, evaluation,
judgement, opinion). The above limitations in the context of this claim correspond to
mental processes, e.g., evaluation and judgement with assistance of pen and paper.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are mere instructions to apply an exception (See MPEP 2106.05(f)).
The limitations:
“wherein an adapter model of the one or more adapter models is configured to…”
As drafted, are additional elements that amount to no more than mere instructions to apply an exception for the abstract ideas. See MPEP 2106.05(f).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: 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 the integration of the abstract ideas into a practical application, all of the additional elements are “mere instructions to apply”. Mere instructions to apply an exception cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 10,
Claim 10 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 10 is directed to a method for generating a response to an input query, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“modify an output of the foundational model, wherein the output of the foundational model is based on the response generation prompt received by the foundational model”
As drafted, under their broadest reasonable interpretations, cover mental processes,
i.e., concepts performed in the human mind (including an observation, evaluation,
judgement, opinion). The above limitations in the context of this claim correspond to
mental processes, e.g., evaluation and judgement with assistance of pen and paper.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are mere instructions to apply an exception (See MPEP 2106.05(f)).
The limitations:
“wherein an adapter model of the one or more adapter models is configured to…”
As drafted, are additional elements that amount to no more than mere instructions to apply an exception for the abstract ideas. See MPEP 2106.05(f).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: 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 the integration of the abstract ideas into a practical application, all of the additional elements are “mere instructions to apply”. Mere instructions to apply an exception cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 11,
Claim 11 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 11 is directed to a method for generating a response to an input query, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: See corresponding analysis of claim 1.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are additional details that do not apply the exception in a meaningful way (See MPEP 2106.05(e)).
The limitations:
“wherein the first input query is a natural language request to generate a response”
As drafted, are additional elements that do not apply an exception for the abstract ideas in a meaningful way. See MPEP 2106.05(e).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: 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 the integration of the abstract ideas into a practical application, all of the additional elements do not apply the exception in a meaningful way. Additional details that do not apply the exception in a meaningful way cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 12,
Claim 12 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 12 is directed to a method for generating a response to an input query, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: See corresponding analysis of claim 1.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are additional details that do not apply the exception in a meaningful way (See MPEP 2106.05(e)).
The limitations:
“wherein a generated response of the one or more responses is a natural language response to the first input query”
As drafted, are additional elements that do not apply an exception for the abstract ideas in a meaningful way. See MPEP 2106.05(e).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: 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 the integration of the abstract ideas into a practical application, all of the additional elements do not apply the exception in a meaningful way. Additional details that do not apply the exception in a meaningful way cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 13,
Claim 13 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 13 is directed to a method for generating a response to an input query, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: See corresponding analysis of claim 1.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are additional details that do not apply the exception in a meaningful way (See MPEP 2106.05(e)).
The limitations:
“wherein the one or more metrics associated with each of the one or more response modules are based on one or more interactions of one or more users with one or more previous responses generated by one or more response modules of the plurality of response modules”
As drafted, are additional elements that do not apply an exception for the abstract ideas in a meaningful way. See MPEP 2106.05(e).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: 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 the integration of the abstract ideas into a practical application, all of the additional elements do not apply the exception in a meaningful way. Additional details that do not apply the exception in a meaningful way cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 14,
Claim 14 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 14 is directed to a method for generating a response to an input query, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: See corresponding analysis of claim 1.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recites additional elements that are insignificant extra-solution activity (See MPEP 2106.05(g)).
The limitations:
“displaying the one or more generated responses to one or more users”
“recording one or more interactions of the one or more users with the one or more generated responses”
As drafted, are additional elements that amount to no more than insignificant extra-solution activity. See MPEP 2106.05(g).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: 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, all of the additional elements are “insignificant extra-solution activity”. Specifically, the displaying limitation recites the well-understood, routine, and conventional activity of receiving and transmitting data over a network. MPEP 2106.05(d)(II); OIP Techs., Inc v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network). Further, the recording limitation recites the well-understood, routine, and conventional activity of storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015). Insignificant extra-solution activity cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 15,
Claim 15 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 15 is directed to a method for generating a response to an input query, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“determining one or more preferred metrics associated with the one or more generated responses based on the one or more recorded interactions with the one or more generated responses”
As drafted, under their broadest reasonable interpretations, cover mental processes,
i.e., concepts performed in the human mind (including an observation, evaluation,
judgement, opinion). The above limitations in the context of this claim correspond to
mental processes, e.g., evaluation and judgement with assistance of pen and paper.
Step 2A Prong Two Analysis: See corresponding analysis of claim 14.
Step 2B Analysis: See corresponding analysis of claim 14.
Regarding Claim 16,
Claim 16 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 16 is directed to a method for generating a response to an input query, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: See corresponding analysis of claim 15.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are mere instructions to apply an exception (See MPEP 2106.05(f)).
The limitations:
“updating one or more response modules of the selected one or more response modules, based on the preferred metrics, by updating one or more trained machine learning models of the response modules”
As drafted, are additional elements that amount to no more than mere instructions to apply an exception for the abstract ideas. See MPEP 2106.05(f).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: 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 the integration of the abstract ideas into a practical application, all of the additional elements are “mere instructions to apply”. Mere instructions to apply an exception cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 17,
Claim 17 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 17 is directed to a method for generating a response to an input query, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“determining one or more characteristics of the second input query”
“respectively generating … one or more respective responses to the second input query based on the characteristics of the second input query”
As drafted, under their broadest reasonable interpretations, cover mental processes,
i.e., concepts performed in the human mind (including an observation, evaluation,
judgement, opinion). The above limitations in the context of this claim correspond to
mental processes, e.g., evaluation and judgement with assistance of pen and paper.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recites additional elements that are mere instructions to apply an exception for the abstract ideas (See MPEP 2106.05(f)), and insignificant extra-solution activity (See MPEP 2106.05(g)).
The limitations:
“by each of the one or more updated response modules”
As drafted, are additional elements that amount to no more than mere instructions to apply an exception for the abstract ideas. See MPEP 2106.05(f).
The limitations:
“receiving a second input query”
As drafted, are additional elements that amount to no more than insignificant extra-solution activity. See MPEP 2106.05(g).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: 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, all of the additional elements are “mere instructions to apply an exception” and “insignificant extra-solution activity”. Specifically, the receiving limitation recites the well-understood, routine, and conventional activity of receiving and transmitting data over a network. MPEP 2106.05(d)(II); OIP Techs., Inc v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network). Mere instructions to apply an exception and insignificant extra-solution activity cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 18,
Claim 18 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 18 is directed to a method for generating a response to an input query, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“selecting, based on the preferred metrics, one or more different response modules from the plurality of response modules”
As drafted, under their broadest reasonable interpretations, cover mental processes,
i.e., concepts performed in the human mind (including an observation, evaluation,
judgement, opinion). The above limitations in the context of this claim correspond to
mental processes, e.g., evaluation and judgement with assistance of pen and paper.
Step 2A Prong Two Analysis: See corresponding analysis of claim 15.
Step 2B Analysis: See corresponding analysis of claim 15.
Regarding Claim 19,
Claim 19 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 19 is directed to a method for generating a response to an input query, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“determining one or more characteristics of the second input query”
“constructing, based on the preferred metrics and the one or more characteristics of the second input query, one or more response modules for generating a response to the second input query”
As drafted, under their broadest reasonable interpretations, cover mental processes,
i.e., concepts performed in the human mind (including an observation, evaluation,
judgement, opinion). The above limitations in the context of this claim correspond to
mental processes, e.g., evaluation and judgement with assistance of pen and paper.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recites additional elements that are insignificant extra-solution activity (See MPEP 2106.05(g)).
The limitations:
“receiving a second input query”
As drafted, are additional elements that amount to no more than insignificant extra-solution activity. See MPEP 2106.05(g).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: 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, all of the additional elements are “insignificant extra-solution activity”. Specifically, the receiving limitation recites the well-understood, routine, and conventional activity of receiving and transmitting data over a network. MPEP 2106.05(d)(II); OIP Techs., Inc v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network). Insignificant extra-solution activity cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 20,
Claim 20 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 20 is directed to a method for generating a response to an input query, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: See corresponding analysis of claim 1.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recited additional elements that are additional details that do not apply the exception in a meaningful way (See MPEP 2106.05(e)).
The limitations:
“wherein a response of the one or more generated responses comprises any one or more of a natural language request for a second input query, a description of a person, a description of a product, a description of a location, and a description of an event”
As drafted, are additional elements that do not apply an exception for the abstract ideas in a meaningful way. See MPEP 2106.05(e).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: 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 the integration of the abstract ideas into a practical application, all of the additional elements do not apply the exception in a meaningful way. Additional details that do not apply the exception in a meaningful way cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 21,
Claim 21 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 21 is directed to a system for generating a response to an input query, comprising: one or more processors; a memory; and one or more programs, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“determining one or more characteristics of the input query”
“selecting, from a plurality of response modules, one or more response modules based on the one or more characteristics of the input query, wherein each response module of the plurality of response modules comprises a plurality of machine learning models for generating a response to the input query”
“generating a one or more responses to the first input query”
As drafted, under their broadest reasonable interpretations, cover mental processes,
i.e., concepts performed in the human mind (including an observation, evaluation,
judgement, opinion). The above limitations in the context of this claim correspond to
mental processes, e.g., evaluation and judgement with assistance of pen and paper.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recites additional elements that are mere instructions to apply an exception for the abstract ideas (See MPEP 2106.05(f)), and insignificant extra-solution activity (See MPEP 2106.05(g)).
The limitations:
“A system for generating a response to an input query, comprising: one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for:…”
“…using the selected one or more response modules”
As drafted, are additional elements that amount to no more than mere instructions to apply an exception for the abstract ideas. See MPEP 2106.05(f).
The limitations:
“receiving a first input query”
As drafted, are additional elements that amount to no more than insignificant extra-solution activity. See MPEP 2106.05(g).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: 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, all of the additional elements are “mere instructions to apply an exception” and “insignificant extra-solution activity”. Specifically, the receiving limitation recites the well-understood, routine, and conventional activity of receiving and transmitting data over a network. MPEP 2106.05(d)(II); OIP Techs., Inc v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network). Mere instructions to apply an exception and insignificant extra-solution activity cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 22,
Claim 22 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 22 is directed to a non-transitory computer readable storage medium storing one or more programs, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“determine one or more characteristics of the input query”
“select, from a plurality of response modules, one or more response modules based on the one or more characteristics of the input query, wherein each response module of the plurality of response modules comprises a plurality of machine learning models for generating a response to the input query”
“generate a one or more responses to the first input query”
As drafted, under their broadest reasonable interpretations, cover mental processes,
i.e., concepts performed in the human mind (including an observation, evaluation,
judgement, opinion). The above limitations in the context of this claim correspond to
mental processes, e.g., evaluation and judgement with assistance of pen and paper.
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recites additional elements that are mere instructions to apply an exception for the abstract ideas (See MPEP 2106.05(f)), and insignificant extra-solution activity (See MPEP 2106.05(g)).
The limitations:
“A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by one or more processors of an electronic device, cause the electronic device to:”
“…using the selected one or more response modules”
As drafted, are additional elements that amount to no more than mere instructions to apply an exception for the abstract ideas. See MPEP 2106.05(f).
The limitations:
“receiving a first input query”
As drafted, are additional elements that amount to no more than insignificant extra-solution activity. See MPEP 2106.05(g).
Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: 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, all of the additional elements are “mere instructions to apply an exception” and “insignificant extra-solution activity”. Specifically, the receiving limitation recites the well-understood, routine, and conventional activity of receiving and transmitting data over a network. MPEP 2106.05(d)(II); OIP Techs., Inc v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network). Mere instructions to apply an exception and insignificant extra-solution activity cannot provide an inventive concept. The claim is not patent eligible.
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.
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.
Claims 1-4 and 11-22 are rejected under 35 U.S.C. 103 as being unpatentable over Li et al. (U.S. Patent Publication No. 2023/0153348) (“Li”) in view of Gray et al. (U.S. Patent No. 11,769,017) (“Gray”).
Regarding claim 1, Li teaches a method for generating a response to an input query (Li [0016] “FIG. 6 illustrates an example of a method for generating a response to a query in accordance with aspects of the present disclosure.”; Li provides a method for generating a response to a query.), the method comprising: receiving a first input query (Li [0062] “Following start operation 602, the method 600 begins with receive operation 604, which receives a query. In aspects, the receive operation 604 receives the query from a bot (e.g., the bot 108 as shown in FIG. 1), which received the query from a user using the client device (e.g., the client device 102 as shown in FIG. 1) in a dialog with the bot.” Li provides a receive operation 604 which receives the query from a bot, which received the query from a user using the client device (e.g., the client device 102 as shown in FIG. 1) in a dialog with the bot.); determining one or more of characteristics of the input query (Li [0063] “An extract operation 606 extracts one or more entities from the query. In aspects, the extract operation 606 may include one or more natural language processors, including a natural language understanding system, a knowledge management system, and a natural language generating system. In aspects, the extract operation 606 extracts the one or more entities from the query for determining contexts and semantics of a dialog associated with a particular task” Li provides extracting entities from a query for determining contexts and semantics, thus determining characteristics of the input query.) selecting, from a plurality of response modules, one or more response modules based on the one or more characteristics of the input query (Li [0034] “The response generator 170 determines and/or generates a response to the received query. In aspects, the response generator 107 selects a response from the ranked list of candidate responses. In aspects, candidate responses may be ranked according to a likelihood of being a correct response to the query. The ranking may be based on a combination of rules and/or conditions associated with a specific task and dialog history data across tasks.”; [0068] “A determine operation 616 determines and/or generates the response to the query. In aspects, the determine operation 616 may select a response from the list of candidate responses.” Li provides the response generator 107 selects a response from the ranked list of candidate responses based on a likelihood of being a correct response to the query, thus selecting a response based on characteristics of the input query.) and one or more metrics associated with each of the one or more response modules (Li [0034] “The response generator 170 determines and/or generates a response to the received query. In aspects, the response generator 107 selects a response from the ranked list of candidate responses. In aspects, candidate responses may be ranked according to a likelihood of being a correct response to the query. The ranking may be based on a combination of rules and/or conditions associated with a specific task and dialog history data across tasks.” Li provides ranking the responses according to a likelihood of being a correct response to a query, thus providing one or more metrics associated with the responses.) …and generating one or more responses to the first input query using the selected one or more response modules (Li [0034] “In aspects, the response generator 107 selects a response from the ranked list of candidate responses.”; [0068] “A determine operation 616 determines and/or generates the response to the query… The determine operation 616 may use a natural language processor to generate the response in text in a natural language form.” Li provides generating the response to the query using a selected response.).
Li fails to teach …wherein each response module of the plurality of response modules comprises a plurality of machine learning models for generating a response to the input query.
However, Gray teaches …wherein each response module of the plurality of response modules comprises a plurality of machine learning models for generating a response to the input query (Gray Col 6 lines 38-42 “FIG. 5 depicts a flowchart illustrating an example method of selecting none, one, or multiple generative model(s) to utilize in generating response(s) to render responsive to a query, and using the selected generative model(s), if any, in generating response(s) to the query.” Gray provides selecting multiple generative models to utilize in generating responses to render responsive to a query, corresponding to a plurality of machine learning models for generating a response to the input query.).
Li and Gray are both considered to be analogous to the claimed invention because they are in the same field of artificial intelligence and more specifically applied to generating natural language responses to a user input query. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Li with the above teachings of Gray. Doing so would allow for improving information retrieval by the LLM that does not rely on hard to codify experience of prompt engineering (Gray Col 3 lines 51-55 “Augmenting LLM prompts based on search result(s), as proposed by various implementations disclosed herein, provides an objective basis to improve information retrieval by the LLM that does not rely on hard to codify experience of prompt engineering.”).
Regarding claim 2, Li in view of Gray teaches wherein the one or more characteristics of the input query are associated with any one or more of a user, a user segment, or use case (Li [0062] “In aspects, the receive operation 604 receives the query from a bot (e.g., the bot 108 as shown in FIG. 1), which received the query from a user using the client device (e.g., the client device 102 as shown in FIG. 1) in a dialog with the bot.”; [0063] “An extract operation 606 extracts one or more entities from the query. In aspects, the extract operation 606 may include one or more natural language processors, including a natural language understanding system, a knowledge management system, and a natural language generating system. In aspects, the extract operation 606 extracts the one or more entities from the query for determining contexts and semantics of a dialog associated with a particular task.” Li provides extracting entities from a query for determining contexts and semantics, thus determining characteristics of the input query, which are received from a user and therefore associated with a user.).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Li in view of Gray for the same reasons disclosed above in the rejection of claim 1.
Regarding claim 3, Li in view of Gray teaches wherein the one or more response modules are selected based on a user segment or use case associated with the input query (Li [0027] “The entity extractor 120 extracts from the query one or more entities, rules, and conditions associated with the query. In particular, the entity extractor 120 extracts at least an entity 126, properties 124, and one or more available actions 122. In aspects, the entity 126 indicates an attribute associated with a specific task (e.g., making a reservation at a restaurant).”; [0034] “In aspects, the response generator 107 selects a response from the ranked list of candidate responses. In aspects, candidate responses may be ranked according to a likelihood of being a correct response to the query. The ranking may be based on a combination of rules and/or conditions associated with a specific task and dialog history data across tasks.” Li provides selecting responses based on a ranking, which is determined based on a combination of rules and/or conditions associated with a specific task (e.g., making a reservation at a restaurant) extracted from a user query, thus selecting a response based on a use case associated with the input query, wherein making a reservation at a restaurant corresponds to a use case associated with an input query.).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Li in view of Gray for the same reasons disclosed above in the rejection of claim 2.
Regarding claim 4, Li in view of Gray teaches wherein the one or more responses to the first input query generated using the selected one or more response modules are tailored to a user segment and a use case (Li [0027] “The entity extractor 120 extracts from the query one or more entities, rules, and conditions associated with the query. In particular, the entity extractor 120 extracts at least an entity 126, properties 124, and one or more available actions 122. In aspects, the entity 126 indicates an attribute associated with a specific task (e.g., making a reservation at a restaurant). The properties 124 may indicate one or more properties associated with the specific task (e.g., date, time, number in party, indoor or patio, etc.) to be satisfied in a response.”; [0034] “In aspects, the response generator 107 selects a response from the ranked list of candidate responses. In aspects, candidate responses may be ranked according to a likelihood of being a correct response to the query. The ranking may be based on a combination of rules and/or conditions associated with a specific task and dialog history data across tasks.” Li provides selecting a response based on rules and conditions associated with an input query received from a user, which includes properties 124 and entities 126, respectively corresponding to a user segment and a use case.).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Li in view of Gray for the same reasons disclosed above in the rejection of claim 1.
Regarding claim 11, Li in view of Gray teaches wherein the first input query is a natural language request to generate a response (Li [0061] “FIG. 6 illustrates an example of a method for generating a response to a query in a dialog in accordance with aspects of the present disclosure.”; [0062] “In aspects, the receive operation 604 receives the query from a bot (e.g., the bot 108 as shown in FIG. 1), which received the query from a user using the client device (e.g., the client device 102 as shown in FIG. 1) in a dialog with the bot.”; [0063] “An extract operation 606 extracts one or more entities from the query. In aspects, the extract operation 606 may include one or more natural language processors, including a natural language understanding system, a knowledge management system, and a natural language generating system.” Li provides receiving a query from a user to generate a response, which is a natural language request to generate a response.).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Li in view of Gray for the same reasons disclosed above in the rejection of claim 1.
Regarding claim 12, Li in view of Gray teaches wherein a generated response of the one or more responses is a natural language response to the first input query (Li [0068] “A determine operation 616 determines and/or generates the response to the query. In aspects, the determine operation 616 may select a response from the list of candidate responses… The determine operation 616 may use a natural language processor to generate the response in text in a natural language form.” Li provides generating the responses in natural language form.).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Li in view of Gray for the same reasons disclosed above in the rejection of claim 1.
Regarding claim 13, Li in view of Gray teaches wherein the one or more metrics associated with each of the one or more response modules are based on one or more interactions of one or more users with one or more previous responses generated by one or more response modules of the plurality of response modules (Li [0028] “The dialog retriever 130 retrieves rules and conditions associated with the received query for the specific task… The last action 134 indicates at least an action performed by a previous response in the specific task as performed by the bot.”; [0033] “The normalizer 160 may rank the candidate responses in the combined first and second sets of candidate responses based on a weighted sum and/or softmax of parameters associated with respective candidate responses… In aspects, the normalizer 160 may weigh the rules and conditions associated with the particular task as a gold rule over candidate responses as generated based on a dialog corpora using the transformer-based dialog embedding 146.”; [0034] “The ranking may be based on a combination of rules and/or conditions associated with a specific task and dialog history data across tasks.” Li provides ranking responses based on rules and conditions associated with a specific task, corresponding to the one or more metrics, which include previous response considerations to determine the ranking, thus being based on one or more interactions of one or more users with one or more previous responses.).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Li in view of Gray for the same reasons disclosed above in the rejection of claim 1.
Regarding claim 14, Li in view of Gray teaches further comprising displaying the one or more generated responses to one or more users (Li [0035] “The response transmitter 180 transmits the response to the bot 108. The bot 108 may transmit the response to the client device 104A over the network as a response to a previously received query.”; [0077] “In various aspects, the output elements include the display 805 for showing a graphical user interface (GUI)” Li provides transmitting responses to a user client device 104, which includes a display.); and recording one or more interactions of the one or more users with the one or more generated responses (Li [0038] “The dialog history 214 includes data associated with dialogs that have taken place. The dialog history includes dialog data from multiple bots across tasks.”; [0042] “The dialog history 302 includes data associated with dialogs held in the past between bots and users across tasks. For example, dialog history 302 includes a conversation between a user and a system (i.e., a bot): User: “I would like to find an expensive restaurant that serves Chinese food.” System: “Sure. Which area do you prefer?” User: “How about in the north part of town.” System: “The Peony Kitchen is a great place.””; Li provides maintaining a dialog history, which are stored interactions between users and the generated responses, thus recording interactions between users and the generated responses.).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Li in view of Gray for the same reasons disclosed above in the rejection of claim 1.
Regarding claim 15, Li in view of Gray teaches further comprising: determining one or more preferred metrics associated with the one or more generated responses based on the one or more recorded interactions with the one or more generated responses (Li [0034] “The response generator 170 determines and/or generates a response to the received query. In aspects, the response generator 107 selects a response from the ranked list of candidate responses. In aspects, candidate responses may be ranked according to a likelihood of being a correct response to the query. The ranking may be based on a combination of rules and/or conditions associated with a specific task and dialog history data across tasks.” Li provides ranking responses based on rules and conditions associated with the dialog history, wherein the ranking of responses corresponds to the preferred metrics associated with the generated responses, and the dialog history corresponds to the recorded interactions with the generated responses.)
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Li in view of Gray for the same reasons disclosed above in the rejection of claim 14.
Regarding claim 16, Li in view of Gray teaches further comprising: updating one or more response modules of the selected one or more response modules, based on the preferred metrics, by updating one or more trained machine learning models of the response modules (Li [0050] “The task-specific classification layer 402 includes a task-specific fine-tuner 404. The task-specific fine-tuner trains the classification model based on a task-specific rules and conditions 406.”; [0053] “In aspects, the pre-training and/or the fine-tuning may take place off-line, non-synchronous to bots interacting with users. The pre-training may be more resource intensive than the fine-tuning. The fine-tuning may take place when a user modifies a dialog associated with a task. By separating timings of the pre-training and the fine-tuning, the present disclosure efficiently combines a user-driven, classification model that accommodates frequent updates in dialogs with a data-driven, generative model that includes dialog corpora that cover multiple tasks.” Li provides fine-tuning a classification model by training based on task-specific rules and conditions, which determine the ranking of responses, to update the classification model that is already pre-trained, thus updating a trained machine learning model based on the preferred metrics.).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Li in view of Gray for the same reasons disclosed above in the rejection of claim 15.
Regarding claim 17, Li in view of Gray teaches further comprising: receiving a second input query (Li [0062] “Following start operation 602, the method 600 begins with receive operation 604, which receives a query. In aspects, the receive operation 604 receives the query from a bot (e.g., the bot 108 as shown in FIG. 1), which received the query from a user using the client device (e.g., the client device 102 as shown in FIG. 1) in a dialog with the bot.” Li provides receiving queries as part of a dialog with a user, which includes more than one user query, thus receiving a second input query.); determining one or more characteristics of the second input query (Li [0063] “An extract operation 606 extracts one or more entities from the query. In aspects, the extract operation 606 may include one or more natural language processors, including a natural language understanding system, a knowledge management system, and a natural language generating system. In aspects, the extract operation 606 extracts the one or more entities from the query for determining contexts and semantics of a dialog associated with a particular task” Li provides extracting entities from a query for determining contexts and semantics, thus determining characteristics of the input query.); respectively generating, by each of the one or more updated response modules, one or more respective responses to the second input query based on the characteristics of the second input query (Li [0034] “The response generator 170 determines and/or generates a response to the received query. In aspects, the response generator 107 selects a response from the ranked list of candidate responses. In aspects, candidate responses may be ranked according to a likelihood of being a correct response to the query. The ranking may be based on a combination of rules and/or conditions associated with a specific task and dialog history data across tasks.”; [0068] “A determine operation 616 determines and/or generates the response to the query. In aspects, the determine operation 616 may select a response from the list of candidate responses.” Li provides generating the response to the query using a selected response according to a likelihood of being a correct response to the query, thus generating a response based on query characteristics.).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Li in view of Gray for the same reasons disclosed above in the rejection of claim 16.
Regarding claim 18, Li in view of Gray teaches further comprising: selecting, based on the preferred metrics, one or more different response modules from the plurality of response modules (Li [0034] “The response generator 170 determines and/or generates a response to the received query. In aspects, the response generator 107 selects a response from the ranked list of candidate responses. In aspects, candidate responses may be ranked according to a likelihood of being a correct response to the query. The ranking may be based on a combination of rules and/or conditions associated with a specific task and dialog history data across tasks.”; [0068] “A determine operation 616 determines and/or generates the response to the query. In aspects, the determine operation 616 may select a response from the list of candidate responses.” Li provides the response generator 107 selects a response from the ranked list of candidate responses based on a likelihood of being a correct response to the query, which is different when a new query is received, thus selecting a different response from a plurality of responses.).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Li in view of Gray for the same reasons disclosed above in the rejection of claim 15.
Regarding claim 19, Li in view of Gray teaches further comprising: receiving a second input query (Li [0062] “Following start operation 602, the method 600 begins with receive operation 604, which receives a query. In aspects, the receive operation 604 receives the query from a bot (e.g., the bot 108 as shown in FIG. 1), which received the query from a user using the client device (e.g., the client device 102 as shown in FIG. 1) in a dialog with the bot.” Li provides receiving queries as part of a dialog with a user, which includes more than one user query, thus receiving a second input query.); determining one or more characteristics of the second input query (Li [0063] “An extract operation 606 extracts one or more entities from the query. In aspects, the extract operation 606 may include one or more natural language processors, including a natural language understanding system, a knowledge management system, and a natural language generating system. In aspects, the extract operation 606 extracts the one or more entities from the query for determining contexts and semantics of a dialog associated with a particular task” Li provides extracting entities from a query for determining contexts and semantics, thus determining characteristics of the input query.); and constructing, based on the preferred metrics and the one or more characteristics of the second input query, one or more response modules for generating a response to the second input query (Li [0034] “The response generator 170 determines and/or generates a response to the received query. In aspects, the response generator 107 selects a response from the ranked list of candidate responses. In aspects, candidate responses may be ranked according to a likelihood of being a correct response to the query. The ranking may be based on a combination of rules and/or conditions associated with a specific task and dialog history data across tasks.” Li provides generating a ranked list of responses based on a likelihood of being a correct response to the query and a combination of rules and/or conditions associated with a specific task and dialog history data across tasks, thus constructing responses based on preferred metrics and query characteristics.).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Li in view of Gray for the same reasons disclosed above in the rejection of claim 15.
Regarding claim 20, Li in view of Gray teaches wherein a response of the one or more generated responses comprises any one or more of a natural language request for a second input query, a description of a person, a description of a product, a description of a location, and a description of an event (Li [0038] “The database 216 includes entities that may be used to replace entity placeholders in de-lexicalized responses (e.g., templates) in generating a response to a query. For example, the database 216 may include names of restaurants with various properties (e.g., location, food type, and the like) associated with respective restaurants.” Li provides generating responses that include at least a description of a location.).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Li in view of Gray for the same reasons disclosed above in the rejection of claim 1.
Regarding claim 21, it is the system embodiment of claim 1 with similar limitations to claim 1 and is rejected using the same reasoning found above in the rejection of claim 1. Further, Li teaches a system for generating a response to an input query, comprising: one or more processors (Li [0071] “In a basic configuration, the computing device 700 may include at least one processing unit 702 and a system memory 704.” Li provides a processor.); a memory (Li [0071] “In a basic configuration, the computing device 700 may include at least one processing unit 702 and a system memory 704.” Li provides a memory.); and one or more programs (Li [0071] “The system memory 704 may include an operating system 705 and one or more program tools 706 suitable for performing the various aspects disclosed herein such. The operating system 705, for example, may be suitable for controlling the operation of the computing device 700.” Li provides programs.), wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors (Li [0071]“In a basic configuration, the computing device 700 may include at least one processing unit 702 and a system memory 704. Depending on the configuration and type of computing device, the system memory 704 may comprise, but is not limited to, volatile storage (e.g., random access memory), non-volatile storage (e.g., read-only memory), flash memory, or any combination of such memories. The system memory 704 may include an operating system 705 and one or more program tools 706 suitable for performing the various aspects disclosed herein such.” Li provides programs stored in memory and executed by a processor.).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Li in view of Gray for the same reasons disclosed above in the rejection of claim 1.
Regarding claim 22, it is the non-transitory computer readable storage medium embodiment of claim 1 with similar limitations to claim 1 and is rejected using the same reasoning found above in the rejection of claim 1. Further, Li teaches a non-transitory computer readable storage medium storing one or more programs (Li [0071] “Depending on the configuration and type of computing device, the system memory 704 may comprise, but is not limited to, volatile storage (e.g., random access memory), non-volatile storage (e.g., read-only memory), flash memory, or any combination of such memories.” Li provides a non-transitory computer readable storage medium storing programs.), the one or more programs comprising instructions, which when executed by one or more processors of an electronic device, cause the electronic device to (Li [0071] “In a basic configuration, the computing device 700 may include at least one processing unit 702 and a system memory 704. Depending on the configuration and type of computing device, the system memory 704 may comprise, but is not limited to, volatile storage (e.g., random access memory), non-volatile storage (e.g., read-only memory), flash memory, or any combination of such memories. The system memory 704 may include an operating system 705 and one or more program tools 706 suitable for performing the various aspects disclosed herein such.” Li provides a processor for executing program instructions.)
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Li in view of Gray for the same reasons disclosed above in the rejection of claim 1.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Li et al. (U.S. Patent Publication No. 2023/0153348) (“Li”) in view of Gray et al. (U.S. Patent No. 11,769,017) (“Gray”) in further view of Chung et al. (U.S. Patent Publication No. 2024/0256965) (“Chung”).
Regarding claim 5, Li in view of Gray teaches the method of claim 1, as discussed above in the rejection of claim 1, but fails to teach wherein the plurality of machine learning models in each respective response module comprises each of a foundational language model, one or more adapter models, one or more retrieval models, and a prompting optimization model.
However, Chung teaches wherein the plurality of machine learning models in each respective response module comprises each of a foundational language model (Chung [0202] “Model development platform 12 can provide one or more model libraries 13 containing building blocks for new models. Model libraries 13 can include one or more pre-trained foundational models 13-1, which can provide a backbone of processing power across various tasks.” Chung provides a plurality of machine learning models including foundational models.), one or more adapter models (Chung [0199] “Data-to-sequence models 11-1, 11-2, and 11-3 can be adapted to each respective input modality 10-1, 10-2, and 10-3.” Chung provides sequence to sequence models that can be adapted to each respective input modality, corresponding to adapter models.), one or more retrieval models (Chung [0233] “For instance, runtime data source(s) 37 can include a knowledge graph 37-1 that facilitates structured information retrieval for information associated with input request(s) 33 (e.g., a search engine service).” Chung provides a knowledge graph 37-1 that facilitates structured information retrieval for information associated with input request(s), corresponding to a retrieval model.), and a prompting optimization model (Chung [0214] “Prompt libraries 17-4 can include one or more prompt engineering tools. Prompt engineering tools can provide workflows for retrieving or learning optimized prompt values.”; [0215] “Prompt libraries 17-4 can include pipelines for prompt generation. For example, inputs can be generated using development model 16 itself or other machine-learned models. In this manner, for instance, a first model can process information about a task and output a input for a second model to process in order to perform a step of the task.” Chung provides prompt optimization including using development model 16 itself or other machine-learned models, corresponding to a prompt optimization model.).
Li, Gray and Chung are all considered to be analogous to the claimed invention because they are in the same field of artificial intelligence and more specifically applied to generating natural language responses to a user input query. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Li in view of Gray with the above teachings of Chung. Doing so would enable models to handle tasks that traditionally required human cognitive abilities (Chung [0032] “This improvement reflects a technical advancement in the field of natural language processing and artificial intelligence, as it enables models to handle tasks that traditionally required human cognitive abilities.”).
Claims 6-7 are rejected under 35 U.S.C. 103 as being unpatentable over Li et al. (U.S. Patent Publication No. 2023/0153348) (“Li”) in view of Gray et al. (U.S. Patent No. 11,769,017) (“Gray”) in further view of Chung et al. (U.S. Patent Publication No. 2024/0256965) (“Chung”) in further view of Sminchisescu et al. (U.S. Patent Publication No. 2023/0116884) (“Sminchisescu”).
Regarding claim 6, Li in view of Gray in further view of Chung teaches the method of claim 5 as discussed above in the rejection of claim 5, but fails to teach wherein an adapter model of the one or more adapter models and a retrieval model of the one or more retrieval models are provided upstream of the foundational model to modify an input to the foundational model.
However, Sminchisescu teaches wherein an adapter model of the one or more adapter models and a retrieval model of the one or more retrieval models are provided upstream of the foundational model to modify an input to the foundational model (Sminchisescu [0047] “The capture model 122 can receive the input image data 102 and capture data 104 to provide inputs (e.g., inputs 11-19) to encoder model layer 126-1. The inputs 11-19 can include serialized image data 102 (e.g., serialized image features 103), combined (e.g., concatenated) with capture data 104 and one or more positional encodings, as transformed according to the capture model 122.”; [0065] “The machine-learned models described in this specification may be used in a variety of tasks, applications, and/or use cases, including a pipeline including a plurality of machine-learned model(s), including one or more machine-learned model(s) upstream and/or downstream of the reconstruction model.” Sminchisescu provides multiple machine learning model upstream of a reconstruction model, corresponding to an adapter and retrieval model, wherein input data may be combined with capture data 104 and one or more positional encodings before being input to the reconstruction model, which is being interpreted as the foundational model, wherein the combined input data corresponds to the modified input.).
Li, Gray, Chung, and Sminchisescu are all considered to be analogous to the claimed invention because they are in the same field of artificial intelligence and generative artificial intelligence. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Li in view of Gray in further view of Chung with the above teachings of Sminchisescu. Doing so can provide for improved three-dimensional reconstructions of bodies in space using two-dimensional input images, reducing the computational cost and component complexity of reconstructing three-dimensional scenes (Sminchisescu [0039] “For example, systems and methods according to example aspects of the present disclosure can provide for improved three-dimensional reconstructions of bodies in space using two-dimensional input images, reducing the computational cost and component complexity of reconstructing three-dimensional scenes.”).
Regarding claim 7, Li in view of Gray in further view of Chung teaches the method of claim 5 as discussed above in the rejection of claim 5, but fails to teach wherein an adapter model of the one or more adapter models and a retrieval model of the one or more retrieval models are provided downstream of the foundational model to modify an output from the foundational model.
However, Sminchisescu teaches wherein an adapter model of the one or more adapter models and a retrieval model of the one or more retrieval models are provided downstream of the foundational model to modify an output from the foundational model (Sminchisescu [0065] “The machine-learned models described in this specification may be used in a variety of tasks, applications, and/or use cases, including a pipeline including a plurality of machine-learned model(s), including one or more machine-learned model(s) upstream and/or downstream of the reconstruction model.”; [0067] “As another example, the machine-learned model(s) can process the latent encoding data to generate a reconstruction output. As another example, the machine-learned model(s) can process the latent encoding data to generate a search output.” Sminchisescu provides multiple machine learning model downstream of a reconstruction model, corresponding to an adapter and retrieval model, wherein the machine-learned models can process the reconstruction model output (the latent encoding data) to generate a search output, wherein the reconstruction model is being interpreted as the foundational model, and wherein the search output corresponds to the modified output.)
Li, Gray, Chung, and Sminchisescu are all considered to be analogous to the claimed invention because they are in the same field of artificial intelligence and generative artificial intelligence. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Li in view of Gray in further view of Chung with the above teachings of Sminchisescu. Doing so can provide for improved three-dimensional reconstructions of bodies in space using two-dimensional input images, reducing the computational cost and component complexity of reconstructing three-dimensional scenes (Sminchisescu [0039] “For example, systems and methods according to example aspects of the present disclosure can provide for improved three-dimensional reconstructions of bodies in space using two-dimensional input images, reducing the computational cost and component complexity of reconstructing three-dimensional scenes.”).
Claims 8-10 are rejected under 35 U.S.C. 103 as being unpatentable over Li et al. (U.S. Patent Publication No. 2023/0153348) (“Li”) in view of Gray et al. (U.S. Patent No. 11,769,017) (“Gray”) in further view of Chung et al. (U.S. Patent Publication No. 2024/0256965) (“Chung”) in further view of Erdenee et al. (U.S. Patent Publication No. 2023/0154453) (“Erdenee”).
Regarding claim 8, Li in view of Gray in further view of Chung teaches the method of claim 5 as discussed above in the rejection of claim 5, but fails to teach wherein the prompting optimization model is configured to modify the first input query using static prompting and dynamic prompting to generate a response generation prompt for the foundational language model.
However, Erdenee teaches wherein the prompting optimization model is configured to modify the first input query using static prompting (Erdenee [0038] “Prompt engineering may be applied to optimize the information obtained from conversation models.”; [0055] “Specifically, when prompts generated using the static method are used, high response consistency and response appropriateness may be achieved.” Erdenee provides prompt optimization including static prompting methods.) and dynamic prompting (Erdenee [0055] “Meanwhile, when prompts generated using the dynamic method are used, a highest performance may be achieved in the style-reflecting metric.” Erdenee provides dynamic prompting methods.) to generate a response generation prompt for the foundational language model (Erdenee [0055] “Specifically, when prompts generated using the static method are used, high response consistency and response appropriateness may be achieved. Meanwhile, when prompts generated using the dynamic method are used, a highest performance may be achieved in the style-reflecting metric.”; [0063] “In accordance with various embodiments, generative models 442 may generate responses based on dialogue-type prompts generated through retrieval models 441.” Erdenee provides generating prompts for generative models 442, corresponding to a generating response generation prompt for a foundational language model.).
Li, Gray, Chung, and Erdenee are all considered to be analogous to the claimed invention because they are in the same field of artificial intelligence and generative artificial intelligence. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Li in view of Gray in further view of Chung with the above teachings of Erdenee. Doing so would enable the generation of responses mimicking conversational styles using utterances and apparatuses (Erdenee [0006] “Using systems and methods of the forms disclosed herein may therefore enable the generation of responses mimicking conversational styles using utterances and apparatuses.”).
Regarding claim 9, Li in view of Gray in further view of Chung in further view of Erdenee teaches wherein an adapter model of the one or more adapter models (Erdenee [0049] “A language model may quickly adapt to the context-response mapping of a given prompt through in-context learning.”; [0068] “In accordance with certain embodiments of the disclosure, generative models may generate responses 530 corresponding to input context through a plurality of decoders 520 using the prompts 510.” Erdenee provides a language model may quickly adapt to the context-response mapping of a given prompt through in-context learning, such as a decoder, corresponding to an adapter model.) is configured to modify the response generation prompt generated by the prompting optimization model before the response generation prompt is received by the foundational model (Erdenee [0068] “In accordance with certain embodiments of the disclosure, generative models may generate responses 530 corresponding to input context through a plurality of decoders 520 using the prompts 510. Referring to FIG. 5… Through this, the prompt 510 can be constructed. Correspondingly, the generative model may then create “Just finished reading a good book. You?” as a response to the input context “Hi what's up?”.” Erdenee provides modifying the prompts using a decoder before being received by the generative models, as shown in figure 5, wherein the generative model corresponds to the foundational model.).
Li, Gray, Chung, and Erdenee are all considered to be analogous to the claimed invention because they are in the same field of artificial intelligence and generative artificial intelligence. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Li in view of Gray in further view of Chung with the above teachings of Erdenee. Doing so would enable the generation of responses mimicking conversational styles using utterances and apparatuses (Erdenee [0006] “Using systems and methods of the forms disclosed herein may therefore enable the generation of responses mimicking conversational styles using utterances and apparatuses.”).
Regarding claim 10, Li in view of Gray in further view of Chung teaches the method of claim 5 as discussed above in the rejection of claim 5, but fails to teach wherein an adapter model of the one or more adapter models is configured to modify an output of the foundational model, wherein the output of the foundational model is based on the response generation prompt received by the foundational model.
However, Erdenee teaches wherein an adapter model of the one or more adapter models (Erdenee [0049] “A language model may quickly adapt to the context-response mapping of a given prompt through in-context learning.”; [0068] “In accordance with certain embodiments of the disclosure, generative models may generate responses 530 corresponding to input context through a plurality of decoders 520 using the prompts 510.” Erdenee provides a language model may quickly adapt to the context-response mapping of a given prompt through in-context learning, such as a decoder, corresponding to an adapter model.) is configured to modify an output of the foundational model, wherein the output of the foundational model is based on the response generation prompt received by the foundational model (Erdenee [0049] “A language model may quickly adapt to the context-response mapping of a given prompt through in-context learning.”; [0068] “In accordance with certain embodiments of the disclosure, generative models may generate responses 530 corresponding to input context through a plurality of decoders 520 using the prompts 510. Referring to FIG. 5… Through this, the prompt 510 can be constructed. Correspondingly, the generative model may then create “Just finished reading a good book. You?” as a response to the input context “Hi what's up?”.” Erdenee provides a decoder corresponding to an adapter model, which modifies the output of generative model (foundational model) based on the received prompts, as shown in Figure 5.).
Li, Gray, Chung, and Erdenee are all considered to be analogous to the claimed invention because they are in the same field of artificial intelligence and generative artificial intelligence. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Li in view of Gray in further view of Chung with the above teachings of Erdenee. Doing so would enable the generation of responses mimicking conversational styles using utterances and apparatuses (Erdenee [0006] “Using systems and methods of the forms disclosed herein may therefore enable the generation of responses mimicking conversational styles using utterances and apparatuses.”).
Conclusion
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/KURT NICHOLAS PRESSLY/Examiner, Art Unit 2125
/KAMRAN AFSHAR/Supervisory Patent Examiner, Art Unit 2125
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