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 . This action is made non-final.
This Office action is in response to the claims filed May 24, 2024.
Claim Objections
Claims 3, and 4 are objected to because of the following informalities: the repeated words of 'each' respective', 'corresponding' and the plural action objects, metrics, text objects, actions and thresholds seem awkward, making the language cumbersome. Appropriate correction is required.
Claim 6 is objected to because of the following informalities: financial lability seems to be meant as "financial liability". Appropriate correction is required.
Claim 20 is objected to because of the following informalities: “configured to receive as input …, and generates an output…” the word ‘generates’ may be better changed to ‘generate’ for grammatical consistency. 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 9-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 9 recites the limitation "one or more synthetic transactions that have not been executed by the one or more entities" in page 3. There is insufficient antecedent basis for this limitation in the claim.
Claims 10-17 depend on claim 9 and are therefore rejected for the same reason.
Claim 15 further recites “the entity object” which is indefinite for failing to particularly point out and distinctly claim the subject matter regarded as the invention. Claim 12, from which claim 15 depends, does not previously recite or otherwise provide antecedent basis for an entity object. Although an entity object is recited in claim 13, claim15 does not depend form claim 13. Therefore, it is unclear what entity object is used to generate the authenticity metric recited in claim 15.
Claim 18 recites the limitation "one or more synthetic transactions that have not been executed by the one or more entities" in page 4. There is insufficient antecedent basis for this limitation in the claim.
Claims 19 and 20 depend on claim 18 and are therefore rejected for the same reason.
Claims 19 and 20 further recite “the action object”, which is indefinite for failing to particularly point out and distinctly claim the subject matter regard as the invention. Claims 19, and 20 each recite that an output generated by the AI model “corresponds to the action object.” However, claim 18, from which claims 19, and 20 depend, does not previously recite or otherwise provide antecedent basis for an action object. Therefore, it is unclear what constitutes “the action object” and what relationship the generated text or multimedia output has to the other subject matter recited in claim 18.
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claim 11 is rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends. Claim 11 recites "the one or more synthetic transactions corresponds to one or more transactions that have not been executed by one or more entities." It is unclear what distinction exists between the recited "synthetic transactions" and the "transactions" to which the synthetic transactions allegedly corresponds. Claim 9 already characterizes the synthetic transactions as transactions that have not been executed. It is unclear whether claim 11 requires a separate set of unexecuted transactions or merely restates the characteristics of the synthetic transactions recited in claim 9. Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
Claim Rejections - 35 USC § 101
To determine if a claim is directed to patent ineligible subject matter, the Court has guided the Office to apply the Alice/Mayo test, which requires:
Step 1: Determining if the claim falls within a statutory category.
Step 2A: Determining if the claim is directed to a patent ineligible judicial exception consisting of a law of nature, a natural phenomenon, or abstract idea; and Step 2A is a two prong inquiry. MPEP 2106.04(II)(A). Under the first prong, examiners evaluate whether a law of nature, natural phenomenon, or abstract idea is set forth or described in the claim. Abstract ideas include mathematical concepts, certain methods of organizing human activity, and mental processes. MPEP 2104.04(a)(2). The second prong is an inquiry into whether the claim integrates a judicial exception into a practical application. MPEP 2106.04(d).
Step 2B: If the claim is directed to a judicial exception, determining if the claim recites limitations or elements that amount to significantly more than the judicial exception. (See MPEP 2106).
Claims 1-20 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Claims 1-8 are directed to a system comprising one or more processors, and memory (a machine), Claims 9-17 are directed to a system comprising one or more processors and memory (a machine) and Claims 18-20 is directed to a method (a process). Therefore, Claims 1-20 are directed to a process, machine or manufacture or composition of matter.
Regarding claim 1
Step 2A Prong 1
Claim 1 recites the following mental processes, that in each case under the broadest reasonable interpretation, covers performance of the limitation in the mind (including observation, evaluation, judgement, opinion) or with the aid of pencil and paper but for recitation of generic computer components (e.g., “system”, “devices”, “processors”, and “artificial intelligence (AI) model”) [see MPEP 2106.04(a)(2)(III)].
“identify, based on a query, an entity and an object corresponding to the entity” (e.g., a human can review and identify an entity and an object which from form a query)
“obtain, …, an entity object that identifies one or more aspects extrinsic to the entity and linked with the entity” (e.g., a human can review or gather information concerning an entity and identify eternal aspects associated with that entity)
“obtain, …, a condition object that identifies one or more aspects extrinsic to the object and the entity” (e.g., a human can review or gather information concerning the entity and object and identify external conditions associated with them)
“generate, …, an action object that identifies an action metric” (e.g., a human can evaluate the information concerning the entity and the identified conditions and determine an action and an associated metric)
“cause, in response to the query and based on the action metric, execution of a transaction including the object and the entity” (e.g., a human can evaluate the action metric, decided whether to execute the transaction, and instruct that the transaction be performed)
Accordingly, at Step 2A, prong one, the claim recites an abstract idea.
Step 2A Prong 2
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of “agent”, and “environment” which are recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using generic computer components (See MPEP 2106.05(f)). The Examiner notes that this is used throughout the claim limitations, and is rejected thusly for each claim which recites the same language.
Regarding the “receiving information associated with interactions of an agent with an environment, the interactions including a plurality of states associated with the environment and a plurality of actions associated with each state from the plurality of states, the interactions being according to a policy defined based on a plurality of hyperparameters” this additional element is recited at a high level of generality and amounts to extra-solution activity of receiving data, i.e. pre-solution activity of inputting data for use in the claimed process (see MPEP 2106.05(g)). The examiner notes that “, the interactions including a plurality of states associated with the environment and a plurality of actions associated with each state from the plurality of states, the interactions being according to a policy defined based on a plurality of hyperparameters” is merely defining the data that is being received for the process.
Regarding the “receiving an indication of a target state to be achieved by the agent in the environment” this additional element is recited at a high level of generality and amounts to extra-solution activity of receiving the desired target of the training process, i.e. pre-solution activity of inputting data for use in the claimed process (see MPEP 2106.05(g)).
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional element of a “agent”, and “environment” which are recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Regarding the “receiving information associated with interactions of an agent with an environment, the interactions including a plurality of states associated with the environment and a plurality of actions associated with each state from the plurality of states, the interactions being according to a policy defined based on a plurality of hyperparameters”, and “receiving an indication of a target state to be achieved by the agent in the environment” limitations, these additional elements are recited at a high-level of generality and amounts to extra-solution activity of obtaining data to input for a model, i.e., pre-solution activity of data gathering. The courts have found limitations directed to obtaining information electronically, recited at a high-level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
Accordingly, at Step 2B, the additional element individually or in combination does not amount to significantly more than the judicial exception.
Regarding claim 2
Step 2A Prong 1
Claim 2 recites the following mental processes, that in each case under the broadest reasonable interpretation, covers performance of the limitation in the mind (including observation, evaluation, judgement, opinion) or with the aid of pencil and paper but for recitation of generic computer components (e.g., “system”, “devices”, “processors”, and “artificial intelligence (AI) model”) [see MPEP 2106.04(a)(2)(III)].
“obtain, based on the query, an entity parameter corresponding to the one or more aspects extrinsic to the entity and linked with the entity” (e.g., a human can review the query and obtain or select information concerning external aspects associated with the entity)
“generate, …, the entity object” (e.g., a human can use the entity parameter to formulate or organize information representing the entity)
“wherein the entity parameter indicates an audience of output of the AI model, the audience based at least partially on the one or more aspects extrinsic to the entity and linked with the entity” (e.g., a human can identify or select an intended audience based on external information associated with the entity)
Accordingly, at Step 2A, prong one, the claim recites an abstract idea.
Step 2A Prong 2
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of “via the AI model”, which is recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using generic computer components (See MPEP 2106.05(f)).
Regarding the “the AI model receiving as input the entity parameter” this additional element is recited at a high level of generality and amounts to extra-solution activity of receiving the desired target of the training process, i.e. pre-solution activity of inputting data for use in the claimed process (see MPEP 2106.05(g)).
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional element of “via the AI model” which is recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Regarding the “the AI model receiving as input the entity parameter” limitation, this additional element is recited at a high-level of generality and amounts to extra-solution activity of obtaining data to input for a model, i.e., pre-solution activity of data gathering. The courts have found limitations directed to obtaining information electronically, recited at a high-level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
Accordingly, at Step 2B, the additional element individually or in combination does not amount to significantly more than the judicial exception.
Regarding claim 3
Step 2A Prong 1
Claim 3 recites the following mental processes, that in each case under the broadest reasonable interpretation, covers performance of the limitation in the mind (including observation, evaluation, judgement, opinion) or with the aid of pencil and paper but for recitation of generic computer components (e.g., “system”, “devices”, “processors”, and “artificial intelligence (AI) model”) [see MPEP 2106.04(a)(2)(III)].
“obtain, based on the query, a condition parameter corresponding to the one or more aspects extrinsic to the object and the entity” (e.g., a human can review the query and identify or select external information concerning the object and the entity)
“generate, …, the condition object” (e.g., a human can organize the identified condition information into a representation of the conditions associated with the object and the entity)
“generate, …, a plurality of action objects including the action object, each of the plurality of action objects identifying corresponding action metrics including the action metric” (e.g., a human can consider multiple possible actions and determine a corresponding metric for each action)
“wherein the plurality of action objects each correspond to respective text objects generated by the AI model, each of the text objects including respective descriptions of respective aspects of respective actions including the transaction in view of respective action metrics for each of the text objects” (e.g., a human can associate each possible action with a textual description and describe the action based on its corresponding metric)
Accordingly, at Step 2A, prong one, the claim recites an abstract idea.
Step 2A Prong 2
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of “via the AI model”, which is recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using generic computer components (See MPEP 2106.05(f)).
Regarding the “the AI model receiving as input the condition parameter” this additional element is recited at a high level of generality and amounts to extra-solution activity of receiving the desired target of the training process, i.e. pre-solution activity of inputting data for use in the claimed process (see MPEP 2106.05(g)).
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional element of “via the AI model” which is recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Regarding the “the AI model receiving as input the condition parameter” limitation, this additional element is recited at a high-level of generality and amounts to extra-solution activity of obtaining data to input for a model, i.e., pre-solution activity of data gathering. The courts have found limitations directed to obtaining information electronically, recited at a high-level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
Accordingly, at Step 2B, the additional element individually or in combination does not amount to significantly more than the judicial exception.
Regarding claim 4
Step 2A Prong 1
Claim 4 recites the following mental processes, that in each case under the broadest reasonable interpretation, covers performance of the limitation in the mind (including observation, evaluation, judgement, opinion) or with the aid of pencil and paper but for recitation of generic computer components (e.g., “system”, “devices”, “processors”, and “artificial intelligence (AI) model”) [see MPEP 2106.04(a)(2)(III)].
“wherein the corresponding action metrics are each linked with one or more corresponding thresholds that respectively indicate one or more respective conditions for execution of the transaction” (e.g., a human can associate each action metric with a threshold and determine the conditions under which the transaction should be executed)
Accordingly, at Step 2A, prong one, the claim recites an abstract idea.
Step 2A Prong 2
In accordance with Step 2A, Prong 2, the claim does not include any additional elements and the judicial exception is not integrated into a practical application.
Step 2B
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Regarding claim 5
Step 2A Prong 1
Claim 5 recites the following mental processes, that in each case under the broadest reasonable interpretation, covers performance of the limitation in the mind (including observation, evaluation, judgement, opinion) or with the aid of pencil and paper but for recitation of generic computer components (e.g., “system”, “devices”, “processors”, and “artificial intelligence (AI) model”) [see MPEP 2106.04(a)(2)(III)].
“wherein the entity corresponds to one or more of a private corporation, a public corporation, an unbanked entity or person, or a banked entity or person” (e.g., a human can obtain or compile information representing a corporation or person and identify whether the corporation or person is banked or unbanked)
Accordingly, at Step 2A, prong one, the claim recites an abstract idea.
Step 2A Prong 2
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of “wherein the AI model is configured to obtain the entity object corresponding to one or more of the private corporation, the public corporation, the unbanked entity or person, or the banked entity or person” this additional element is recited at a high level of generality and amounts to extra-solution activity of receiving the desired target of the training process, i.e. pre-solution activity of inputting data for use in the claimed process (see MPEP 2106.05(g)).
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional element of
“wherein the AI model is configured to obtain the entity object corresponding to one or more of the private corporation, the public corporation, the unbanked entity or person, or the banked entity or person” limitation, this additional element is recited at a high-level of generality and amounts to extra-solution activity of obtaining data to input for a model, i.e., pre-solution activity of data gathering. The courts have found limitations directed to obtaining information electronically, recited at a high-level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
Accordingly, at Step 2B, the additional element individually or in combination does not amount to significantly more than the judicial exception.
Regarding claim 6
Step 2A Prong 1
Claim 6 does not recite an abstract idea, but is directed to the abstract idea identified in its parents claim(s).
Accordingly, at Step 2A, prong one, the claim recites an abstract idea.
Step 2A Prong 2
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of “wherein the object is a financial object, and wherein the financial object corresponds to a financial asset, a financial lability, or a financial model " which is recited at a high-level of generality such that they amount to no more than generally linking the use of abstract idea to a particular technological environment or field of use using a generic computer component (See MPEP 2106.05(h)). In particular it is merely describing how the data is labeled for use in the claimed process.
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional element of a “wherein the object is a financial object, and wherein the financial object corresponds to a financial asset, a financial lability, or a financial model” which is recited at a high-level of generality such that they amount to no more than generally linking the use of abstract idea to a particular technological environment or field of use using a generic computer component (See MPEP 2106.05(h)). In particular it is merely describing how the data is labeled for use in the claimed process.
Accordingly, at Step 2B, the additional element individually or in combination does not amount to significantly more than the judicial exception.
Regarding claim 7
Step 2A Prong 1
Claim 7 recites the following mental processes, that in each case under the broadest reasonable interpretation, covers performance of the limitation in the mind (including observation, evaluation, judgement, opinion) or with the aid of pencil and paper but for recitation of generic computer components (e.g., “system”, “devices”, “processors”, and “artificial intelligence (AI) model”) [see MPEP 2106.04(a)(2)(III)].
“wherein the entity object corresponds to a text object … and includes a description of the entity, wherein the description is based on the entity and the one or more aspects extrinsic to the entity and linked with the entity” (e.g., a human can review information concerning an entity and prepare a textual description of the entity based on that information)
Accordingly, at Step 2A, prong one, the claim recites an abstract idea.
Step 2A Prong 2
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of “generated by the AI model”, which is recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using generic computer components (See MPEP 2106.05(f)).
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional element of “generated by the AI model” which is recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Accordingly, at Step 2B, the additional element individually or in combination does not amount to significantly more than the judicial exception.
Regarding claim 8
Step 2A Prong 1
Claim 8 recites the following mental processes, that in each case under the broadest reasonable interpretation, covers performance of the limitation in the mind (including observation, evaluation, judgement, opinion) or with the aid of pencil and paper but for recitation of generic computer components (e.g., “system”, “devices”, “processors”, and “artificial intelligence (AI) model”) [see MPEP 2106.04(a)(2)(III)].
“wherein the condition object corresponds to a text object … and includes a description of the one or more aspects extrinsic to the object and the entity” (e.g., a human can review information concerning an object and entity and prepare a textual description of that information)
“wherein the action object corresponds to a text object … and includes a description of one or more aspects of an action including the transaction in view of the action metric” (e.g., a human can evaluate an action metric and prepare a textual description of ana associated action or transaction based on that metric)
Accordingly, at Step 2A, prong one, the claim recites an abstract idea.
Step 2A Prong 2
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of “generated by the AI model”, which is recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using generic computer components (See MPEP 2106.05(f)).
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional element of “generated by the AI model” which is recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Accordingly, at Step 2B, the additional element individually or in combination does not amount to significantly more than the judicial exception.
Regarding claim 9
Step 2A Prong 1
Claim 9 recites the following mental processes, that in each case under the broadest reasonable interpretation, covers performance of the limitation in the mind (including observation, evaluation, judgement, opinion) or with the aid of pencil and paper but for recitation of generic computer components (e.g., “system”, “devices”, “processors”, and “artificial intelligence (AI) model”) [see MPEP 2106.04(a)(2)(III)].
“identify, based on a query, first data having an authenticity property and including one or more first transaction records, the first transaction records identifying one or more actual transactions” (e.g., a human can review a query and transaction records, identify records representing actual transactions, and determine or recognize an authenticity characteristic associated with the records)
“generate, …, second data having the authenticity property and including one or more second transaction records, the second transaction records corresponding to one or more synthetic transactions that have not been executed by the one or more entities” (e.g., a human can formulate hypothetical transactions that have not actually occurred and create records describing those transactions)
Accordingly, at Step 2A, prong one, the claim recites an abstract idea.
Step 2A Prong 2
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of “via an artificial intelligence (AI) model” which are recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using generic computer components (See MPEP 2106.05(f)). The Examiner notes that this is used throughout the claim limitations, and is rejected thusly for each claim which recites the same language.
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional element of a “via an artificial intelligence (AI) model” which are recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Accordingly, at Step 2B, the additional element individually or in combination does not amount to significantly more than the judicial exception.
Regarding claim 10
Step 2A Prong 1
Claim 10 recites the following mental processes, that in each case under the broadest reasonable interpretation, covers performance of the limitation in the mind (including observation, evaluation, judgement, opinion) or with the aid of pencil and paper but for recitation of generic computer components (e.g., “system”, “devices”, “processors”, and “artificial intelligence (AI) model”) [see MPEP 2106.04(a)(2)(III)].
“wherein the one or more actual transactions correspond to one or more transactions that have been executed by one or more entities” (e.g., a human review transaction information and determine whether a transaction was actually executed by an entity)
Accordingly, at Step 2A, prong one, the claim recites an abstract idea.
Step 2A Prong 2
In accordance with Step 2A, Prong 2, the claim does not include any additional elements and the judicial exception is not integrated into a practical application.
Step 2B
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Regarding claim 11
Step 2A Prong 1
Claim 11 recites the following mental processes, that in each case under the broadest reasonable interpretation, covers performance of the limitation in the mind (including observation, evaluation, judgement, opinion) or with the aid of pencil and paper but for recitation of generic computer components (e.g., “system”, “devices”, “processors”, and “artificial intelligence (AI) model”) [see MPEP 2106.04(a)(2)(III)].
“wherein the one or more synthetic transactions correspond to one or more transactions that have not been executed by one or more entities” (e.g., a human can formulate or review hypothetical transaction information and determine that the transactions were not actually executed by an entity)
Accordingly, at Step 2A, prong one, the claim recites an abstract idea.
Step 2A Prong 2
In accordance with Step 2A, Prong 2, the claim does not include any additional elements and the judicial exception is not integrated into a practical application.
Step 2B
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Regarding claim 12
Step 2A Prong 1
Claim 12 recites the following mental processes, that in each case under the broadest reasonable interpretation, covers performance of the limitation in the mind (including observation, evaluation, judgement, opinion) or with the aid of pencil and paper but for recitation of generic computer components (e.g., “system”, “devices”, “processors”, and “artificial intelligence (AI) model”) [see MPEP 2106.04(a)(2)(III)].
“in response to a determination that an authenticity metric satisfies a fraud threshold corresponding to an entity among the one or more entities” (e.g., a human can evaluate the authenticity metric, compare it with a fraud threshold, and determine whether the threshold is satisfied)
Accordingly, at Step 2A, prong one, the claim recites an abstract idea.
Step 2A Prong 2
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of “cause… execution of a transaction including the entity and an object corresponding to the entity” which are recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using generic computer components (See MPEP 2106.05(f)). The Examiner notes that this is used throughout the claim limitations, and is rejected thusly for each claim which recites the same language.
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional element of a “cause… execution of a transaction including the entity and an object corresponding to the entity” which are recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Accordingly, at Step 2B, the additional element individually or in combination does not amount to significantly more than the judicial exception.
Regarding claim 13
Step 2A Prong 1
Claim 13 recites the following mental processes, that in each case under the broadest reasonable interpretation, covers performance of the limitation in the mind (including observation, evaluation, judgement, opinion) or with the aid of pencil and paper but for recitation of generic computer components (e.g., “system”, “devices”, “processors”, and “artificial intelligence (AI) model”) [see MPEP 2106.04(a)(2)(III)].
“identify, based on a query, the entity and the object” (e.g., a human can review a query and identify the entity and object referenced by the query)
“obtain, …, an entity object that identifies one or more aspects extrinsic to the entity and linked with the entity” (e.g., a human can gather or review information concerning an entity and identify external aspects associated with that entity)
Accordingly, at Step 2A, prong one, the claim recites an abstract idea.
Step 2A Prong 2
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of “via the AI model” which are recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using generic computer components (See MPEP 2106.05(f)). The Examiner notes that this is used throughout the claim limitations, and is rejected thusly for each claim which recites the same language.
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional element of a “via the AI model” which are recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Accordingly, at Step 2B, the additional element individually or in combination does not amount to significantly more than the judicial exception.
Regarding claim 14
Step 2A Prong 1
Claim 14 does not recite an abstract idea, but is directed to the abstract idea identified in its parents claim(s).
Accordingly, at Step 2A, prong one, the claim recites an abstract idea.
Step 2A Prong 2
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of “cause a user interface to present the entity object " which is recited at a high-level of generality such that it amounts to extra-solution activity of presenting data, i.e. post-solution activity of data outputting for use in the claimed process (see MPEP 2106.05(g)).
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional element of a “cause a user interface to present the entity object " limitation, the additional element is recited at a high-level of generality and amounts to extra-solution activity of post-solution activity of outputting data for display. The courts have found limitations directed to obtaining information electronically, recited at a high-level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
Accordingly, at Step 2B, the additional element individually or in combination does not amount to significantly more than the judicial exception.
Regarding claim 15
Step 2A Prong 1
Claim 15 recites the following mental processes, that in each case under the broadest reasonable interpretation, covers performance of the limitation in the mind (including observation, evaluation, judgement, opinion) or with the aid of pencil and paper but for recitation of generic computer components (e.g., “system”, “devices”, “processors”, and “artificial intelligence (AI) model”) [see MPEP 2106.04(a)(2)(III)].
“generate the authenticity metric based on the entity object and one or more of the synthetic transactions ” (e.g., a human can review the information represented by the entity object and the synthetic transactions and determine or assign a measure of authenticity based on that information)
Accordingly, at Step 2A, prong one, the claim recites an abstract idea.
Step 2A Prong 2
In accordance with Step 2A, Prong 2, the claim does not include any additional elements and the judicial exception is not integrated into a practical application.
Step 2B
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Regarding claim 16
Step 2A Prong 1
Claim 16 recites the following mental processes, that in each case under the broadest reasonable interpretation, covers performance of the limitation in the mind (including observation, evaluation, judgement, opinion) or with the aid of pencil and paper but for recitation of generic computer components (e.g., “system”, “devices”, “processors”, and “artificial intelligence (AI) model”) [see MPEP 2106.04(a)(2)(III)].
“generate, …, an action object that identifies an action metric, the AI model receiving as input the one or more synthetic transactions and the entity object” (e.g., a human can review the synthetic transaction information and entity information, determine an appropriate action, and assign or identify a corresponding metric for that action)
Accordingly, at Step 2A, prong one, the claim recites an abstract idea.
Step 2A Prong 2
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of “via the AI model” which are recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using generic computer components (See MPEP 2106.05(f)). The Examiner notes that this is used throughout the claim limitations, and is rejected thusly for each claim which recites the same language.
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional element of a “via the AI model” which are recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Accordingly, at Step 2B, the additional element individually or in combination does not amount to significantly more than the judicial exception.
Regarding claim 17
Step 2A Prong 1
Claim 17 does not recite an abstract idea, but is directed to the abstract idea identified in its parents claim(s).
Accordingly, at Step 2A, prong one, the claim recites an abstract idea.
Step 2A Prong 2
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of “obtain, via a user interface, a selection of the action object t " which is recited at a high-level of generality such that it amounts to extra-solution activity of presenting data, i.e. post-solution activity of data gathering for use in the claimed process (see MPEP 2106.05(g)).
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional element of a “obtain, via a user interface, a selection of the action object " limitation, the additional element is recited at a high-level of generality and amounts to extra-solution activity of post-solution activity of gathering data for display. The courts have found limitations directed to obtaining information electronically, recited at a high-level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
Accordingly, at Step 2B, the additional element individually or in combination does not amount to significantly more than the judicial exception.
Regarding claim 18, which substantially recites the same limitations as claim 9 and is rejected for the same reasons as described above.
Regarding claim 19
Step 2A Prong 1
Claim 19 recites the following mental processes, that in each case under the broadest reasonable interpretation, covers performance of the limitation in the mind (including observation, evaluation, judgement, opinion) or with the aid of pencil and paper but for recitation of generic computer components (e.g., “system”, “devices”, “processors”, and “artificial intelligence (AI) model”) [see MPEP 2106.04(a)(2)(III)].
“receive as input a prompt including first text and to generate an output including a second text that corresponds to the action object” (e.g., a human can review a textual prompt and compose responsive text describing or representing the determined action)
Accordingly, at Step 2A, prong one, the claim recites an abstract idea.
Step 2A Prong 2
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of “wherein the AI model corresponds to a multi-modal model (MMM)” which are recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using generic computer components (See MPEP 2106.05(f)). The Examiner notes that this is used throughout the claim limitations, and is rejected thusly for each claim which recites the same language.
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional element of a “wherein the AI model corresponds to a multi-modal model (MMM)” which are recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Accordingly, at Step 2B, the additional element individually or in combination does not amount to significantly more than the judicial exception.
Regarding claim 19
Step 2A Prong 1
Claim 19 recites the following mental processes, that in each case under the broadest reasonable interpretation, covers performance of the limitation in the mind (including observation, evaluation, judgement, opinion) or with the aid of pencil and paper but for recitation of generic computer components (e.g., “system”, “devices”, “processors”, and “artificial intelligence (AI) model”) [see MPEP 2106.04(a)(2)(III)].
“prompt including first text and … a second text that corresponds to the action object” (e.g., a human can review a textual prompt and compose responsive text describing or representing the determined action)
Accordingly, at Step 2A, prong one, the claim recites an abstract idea.
Step 2A Prong 2
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of “wherein the AI model corresponds to a large language model (LLM) configured to receive as input a prompt… and to generate an output” which are recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using generic computer components (See MPEP 2106.05(f)). The Examiner notes that this is used throughout the claim limitations, and is rejected thusly for each claim which recites the same language.
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional element of a “wherein the AI model corresponds to a large language model (LLM)” which are recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Accordingly, at Step 2B, the additional element individually or in combination does not amount to significantly more than the judicial exception.
Regarding claim 20
Step 2A Prong 1
Claim 20 recites the following mental processes, that in each case under the broadest reasonable interpretation, covers performance of the limitation in the mind (including observation, evaluation, judgement, opinion) or with the aid of pencil and paper but for recitation of generic computer components (e.g., “system”, “devices”, “processors”, and “artificial intelligence (AI) model”) [see MPEP 2106.04(a)(2)(III)].
“one or more of first text or first multimedia content, … one or more of second text or second multimedia content that corresponds to the action object” (e.g., a human can review a first text and composing second text describing or representing the corresponding action object)
Accordingly, at Step 2A, prong one, the claim recites an abstract idea.
Step 2A Prong 2
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of “wherein the AI model corresponds to a multi-modal model (MMM) configured to receive as input…, and generates an output” which are recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using generic computer components (See MPEP 2106.05(f)). The Examiner notes that this is used throughout the claim limitations, and is rejected thusly for each claim which recites the same language.
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional element of a “wherein the AI model corresponds to a multi-modal model (MMM)” which are recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Accordingly, at Step 2B, the additional element individually or in combination does not amount to significantly more than the judicial exception.
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.
Claim(s) 1, 5, and 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Subbarayan et al. (US 20180183737 A1, referred to as Subbarayan, in view of Edwards et al. (US 20210303973 A1, referred to as Edwards).
Regarding Claim 1, Subbarayan teaches a system comprising:
one or more memory devices; and
one or more processors coupled to the one or more memory devices, the one or more processors ([0217-0219], and Figure 8: Describes a computing device which implements in a system and comprises a processor, and a memory which are coupled together in a communication infrastructure. To execute instructions stored in memory on computer hardware.)configured to:
identify, based on a query, an entity and an object corresponding to the entity(Fig. 4C, 4D, 6, [0050-0052], and [0136-0140]: Describes receiving and analyzing, using natural language processing, one or more natural language messages entered by a user and identifying form the messages a product that the user seeks to purchase. The user corresponds to an entity, the identified product corresponds to an object associated with the entity, and the one or more natural language messages correspond to a query.);
Subbarayan obtain, via the AI model, a condition object that identifies one or more aspects extrinsic to the object and the entity ([0051-0054], and [0148-0150]: Describes using natural language processing to analyze messages and determine a context of communications session, including the purpose and circumstances of the session, information provided by the merchant, and additional details concerning the proposed transaction. The determined context corresponds to the condition object as it is a data representation of circumstances external to the user and the identified product, but relevant to determining the transaction related action.)
Although Subbarayan obtain, via the AI model, a condition object that identifies one or more aspects extrinsic to the object and the entity. It does not teach obtain, via an artificial intelligence (AI) model, an entity object that identifies one or more aspects extrinsic to the entity and linked with the entity
Edwards teaches obtain, via an artificial intelligence (AI) model, an entity object that identifies one or more aspects extrinsic to the entity and linked with the entity (FIG. 6, [0010], [0020-0027], and [0035]: Describes storing user resource data representing resources associated with a user and processing the user resource data using an AI transaction optimization model. The user resource data may identify the user’s financial assets, account balances, investments, anticipated financial inputs and outputs, and other financial resources. The user resource data corresponds to the entity object because it constitutes a data representation identifying financial resources that are external to, but associated with, the user. The user corresponds to the entity, and the user’s financial resources correspond to the aspects extrinsic to and linked with the entity.)
It would have been obvious to one of ordinary skill in the art at the time of the claimed invention to have combined the conversational transaction system of Subbarayan with the transaction optimization model and action metric of Edward’s. Doing so would have enabled the system to improve the selection of transitions consistent with the user’s financial goals.
Edwards further teaches generate, via the AI model, an action object that identifies an action metric, the AI model receiving as input the entity object and the condition object ([0069-0072], [0121-0124], and [0152-0157]: Describes providing a user’s resources and financial goals to a transaction optimizing neural network, which models and selects possible transactions or financial strategies for moving the user form a present resource state toward the user’s goals. The generated transaction or strategy corresponds to the action object. The network evaluates the transaction or strategy using a cost function, goal priority, path weight, or degree to which the transaction advances the user toward the financial goal, which corresponds to the action metric. The user resource data and user goal data supplied to the neural network correspond respectively to the entity object and condition object.); and
Subbarayan in view of Edwards teaches cause, in response to the query and based on the action metric, execution of a transaction including the object and the entity (Subbarayan [0061-0064] describes analyzing natural language messages form a user to identify a product and a request to purchase the product and, in response to the identified request, initiating and processing a payment transaction on behalf of the user for the identified product. The user corresponds to the claimed entity, and the product corresponds to the object. ; Edwards [0069-0073], and [0128-0132] describes evaluating a proposed financial action based on an action metric, such as the likelihood or degree to which the action advances the user toward a financial goal, the weight associated with a transaction path, or the consistency or advisability of the action relative to the user’s goal. Accordingly, in the combined system, execution of Subbarayan’s transaction would be caused based on the action metric generated by Edward’s transaction optimizing AI model. ).
Regarding Claim 5, Subbarayan in view of Edwards, teaches the system of claim 1.
Subbarayan further teaches wherein the entity corresponds to one or more of a private corporation, a public corporation, an unbanked entity or person, or a banked entity or person, and wherein the AI model is configured to obtain the entity object corresponding to one or more of the private corporation, the public corporation, the unbanked entity or person, or the banked entity or person ([0060-0062]: Describes obtaining information corresponding to an entity. After analyzing the user’s natural language messages, the commerce system accesses the user’s account to identify payment information and obtain a payment credential or payment token associated with the user for processing the transaction.; [0197-0198]: Describes that the entity corresponds to a banked person. A user registering a deposit account or other payment credential, wherein the suer profile stores payment credentials including credit cards, debit cards, deposit accounts, and other bank accounts together with identifying information for the user.).
Regarding Claim 6, Subbarayan in view of Edwards, teaches the system of claim 1.
Edwards further teaches wherein the object is a financial object, and wherein the financial object corresponds to a financial asset, a financial lability, or a financial model ([0027, and [0122-0124]: Describes storing and updating user financial assets data and representing the user’s financial assets as an input state object supplied to a transaction optimizing artificial intelligence model. The model represents transactions as changes in the state of the user’s financial assets.).
Claim(s) 2, 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Subbarayan et al. (US 20180183737 A1, referred to as Subbarayan, in view of Edwards et al. (US 20210303973 A1, referred to as Edwards), in view of Lagi et al. (US 20200065857 A1, referred to as Lagi).
Regarding Claim 2, Subbarayan in view of Edwards teaches the system of claim 1, wherein the one or more processors are further configured to:
Subbarayan obtain, based on the query, an entity parameter corresponding to the one or more aspects extrinsic to the entity and linked with the entity ([0060-0062]: Describes analyzing messages in which a user requests product recommendations based on the user’s interests or preferences and, in response, accessing a user account or stored user preferences to identify one or more interests or preferences associated with the user. The identified interest or preference corresponds to the entity parameter because it represents a particular value or characteristic associated with the user and corresponding to the user related information represented by the entity object)
Although Subbarayan teaches the entity object and AI model generation. It does not teach that the AI model receives as input the entity parameter.
Lagi teaches generate, via the AI model, the entity object, the AI model receiving as input the entity parameter ([0046-0047], and [0117-0118]: Describes retrieving entity data relating to an individual or an organization associated with the individual and generates directed content using a machine learned generative model trained to generate text based on the entity data and a message objective.)
It would have been obvious to one of ordinary skill in the art at the time of the claimed invention to have combined the system of Subbarayan in view of Edwards with the entity linked recipient information of Lagi. Doing so would have enabled the system to generate output tailored to an intended recipient based on information associated with that recipient, to increase relevance and personalization of the generated output.
Lagi further teaches wherein the entity parameter indicates an audience of output of the AI model, the audience based at least partially on the one or more aspects extrinsic to the entity and linked with the entity ([0037], [0045], and [0117-0118: Describes how it obtains a recipient profile indicating attributes of an intended recipient and determines a recipient list based on the recipient profile and information represented in a knowledge graph. The recipient list is further determined bae don entity data, event data, and relationship data relating to an individual or an organization associated with the individual, and personalized content is generated for the identified recipients.).
Regarding Claim 7, Subbarayan in view of Edwards, teaches the system of claim 1.
Although , Subbarayan in view of Edwards teaches the system of claim 1 they do not teach wherein the entity object corresponds to a text object generated by the AI model and includes a description of the entity, wherein the description is based on the entity and the one or more aspects extrinsic to the entity and linked with the entity.
Lagi teaches wherein the entity object corresponds to a text object generated by the AI model and includes a description of the entity, wherein the description is based on the entity and the one or more aspects extrinsic to the entity and linked with the entity ([0046]: Describes retrieving entity data relating to an individual or an organization associated with the individual and generating directed content comprising at least a phrase or sentence containing information corresponding to the retrieved entity data. It generates a personalized message based on the directed content using a machine learning generative model trained to generate text from entity data.; [0037]: Describes personalizing the generated message based on entity data, relationship data, and event data associated with the individual or organization. The generated textual description in based on the entity itself and on relationship or event information extrinsic to and linked with the entity.).
It would have been obvious to one of ordinary skill in the art at the time of the claimed invention to have combined the system of Subbarayan in view of Edwards with the personalized textual content of Lagi. Doing so would have enabled the system to improve the relevance and usefulness of the AI generated output.
Claim(s) 3, and 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Subbarayan et al. (US 20180183737 A1, referred to as Subbarayan, in view of Edwards et al. (US 20210303973 A1, referred to as Edwards), in view of Bade et al. (US 20220051665 A1, referred to as Bade), in view of Daly et al. (US 20200219004 A1, referred to as Daly).
Regarding Claim 3, Subbarayan in view of Edwards teaches the system of claim 1, wherein the one or more processors are further configured to:
Subbarayan further teaches obtain, based on the query, a condition parameter corresponding to the one or more aspects extrinsic to the object and the entity ([0051-0054], and [0063]: Describes analyzing the user’s natural language messages to determine the context and circumstances of a potential transaction and, based on the identified product and purchase request, communicating with the merchant system to obtain a price for the product and purchase request, communicating with the merchant system to obtain a price for the product and assigning the price as the payment amount for the transaction. The obtained price or payment amount corresponds to the claimed condition parameter because it is a particular transaction related value associated with circumstances external to both the user and the product.);
Although Subbarayan in view of Edwards teaches the system of claim 1, wherein the one or more processors are further configured to: obtain, based on the query, a condition parameter corresponding to the one or more aspects extrinsic to the object and the entity. They do not teach to generate, via the AI model, the condition object, the AI model receiving as input the condition parameter
Bade teaches generate, via the AI model, the condition object, the AI model receiving as input the condition parameter ([0027-0036], and [0047-0048]: Describes using natural language processing models and parsers to extract contextual parameters form a user query, including temporal phrases, locative phrases, verb tense, negation, and other verb arguments. It provides the extracted parameters to a verb object generator, which generates a structured verb object containing the extracted contextual information for subsequent intent processing. The extracted temporal, locative, or other contextual value corresponds to the condition parameter, while the generated verb object containing that contextual value corresponds to the condition object.)
It would have been obvious to one of ordinary skill in the art at the time of the claimed invention to have combined the conversational transaction system of Subbarayan in view of Edwards with the natural language query parsing and structured object generation techniques of Bade. Doing so would have enabled the system to improve its ability to interpret the query and evaluate the requested transaction in view of the surrounding context.
Edwards teaches generate, via the AI model, a plurality of action objects including the action object, each of the plurality of action objects identifying corresponding action metrics including the action metric ([[0072-0075]: Describes generating, via a transaction optimizing AI model, a plurality of action objects including the action object, wherein the action objects corresponds to respective possible financial transactions, choices, or workflow decisions represented within the transaction optimizing network, and wherein each action object identifies a corresponding action metric, such as likelihood or network weight indicating the effect of the respective financial choice on a path toward the user’s financial goal.)
Although Subbarayan in view of Edwards in view of Bade teaches, generate, via the AI model, a plurality of action objects including the action object, each of the plurality of action objects identifying corresponding action metrics including the action metric. They do not teach wherein the plurality of action objects each correspond to respective text objects generated by the AI model, each of the text objects including respective descriptions of respective aspects of respective actions including the transaction in view of respective action metrics for each of the text objects.
Daly teaches wherein the plurality of action objects each correspond to respective text objects generated by the AI model, each of the text objects including respective descriptions of respective aspects of respective actions including the transaction in view of respective action metrics for each of the text objects ( [0065-0067], and [0070-0072]: Describes a plurality of recommender engines that generate recommended actions based on respective factors and scores affecting a predicted outcome, and a table associating each recommended action with a respective explanation describing the action in view of the corresponding score or predicted impact. It recommends adding an experienced team member to improve a role dimension score and lowering a product price to increase the likelihood that a sales transaction will be successfully concluded.; Edwards is relied upon for the plurality of transaction oriented actions and corresponding action metrics, where Daly supplies the respective metric based explanatory text linked to the respective actions.).
It would have been obvious to one of ordinary skill in the art at the time of the claimed invention to have combined the system of Subbarayan in view of Edwards in view of Bade, with the explanatory recommendation techniques of Daly. Doing so would have enabled the system to improve its ability to interpret the query and evaluate the requested transaction in view of the surrounding context.
Regarding Claim 4, Subbarayan in view of Edwards, in view of Bade, in view of Daly teaches the system of claim 3.
Subbarayan in view of Edwards further teaches wherein the corresponding action metrics are each linked with one or more corresponding thresholds that respectively indicate one or more respective conditions for execution of the transaction (Edwards [0072-0073] is used for the generating a plurality of action objects having corresponding action metrics associated with respective possible financial actions and further teaches that transaction may be executed when sufficient circumstantial conditions are satisfied.; Subbarayan [0199-0202]: Describes determining a risk level or realness score associated with a user or payment transaction, compares the score with a predetermined threshold, and selectively allows or blocks bk the payment transaction based on whether the threshold condition is satisfied.).
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Subbarayan et al. (US 20180183737 A1, referred to as Subbarayan, in view of Edwards et al. (US 20210303973 A1, referred to as Edwards), in view of Lagi et al. (US 20200065857 A1, referred to as Lagi), in view of Daly et al. (US 20200219004 A1, referred to as Daly).
Regarding Claim 8, Subbarayan in view of Edwards, teaches the system of claim 1.
Although , Subbarayan in view of Edwards teaches the system of claim 1 they do not teach wherein the condition object corresponds to a text object generated by the AI model and includes a description of the one or more aspects extrinsic to the object and the entity.
Lagi teaches wherein the condition object corresponds to a text object generated by the AI model and includes a description of the one or more aspects extrinsic to the object and the entity ([0047, and [0192]: Describes using a machine learning generative model to generate directed content comprising a phrase or sentence based no event data r relationship data concerning an individual or an organization associated with the individual. Such even and relationship information constitutes contextual aspects external to, but associated with, the relevant object and entity.)
It would have been obvious to one of ordinary skill in the art at the time of the claimed invention to have combined the system of Subbarayan in view of Edwards with the content and relationship content of Lagi. Doing so would have enabled the system to improve the relevance and usefulness of the AI generated output.
Although , Subbarayan in view of Edwards, in view of Lagi teaches wherein the condition object corresponds to a text object generated by the AI model and includes a description of the one or more aspects extrinsic to the object and the entity they do not teach wherein the action object corresponds to a text object generated by the AI model and includes a description of one or more aspects of an action including the transaction in view of the action metric.
Daly teaches wherein the action object corresponds to a text object generated by the AI model and includes a description of one or more aspects of an action including the transaction in view of the action metric ([0065-0068, and [0072]: Describes a machine learning system calculating a success rate or confidence score for a transactional sales opportunity and generating recommended actions, such as adding a team member or reducing a product price, based on factors affecting that score. It provides a textual explanation corresponding to the recommended action and describing the action in view of the score or factor to be improved. ).
It would have been obvious to one of ordinary skill in the art at the time of the claimed invention to have combined the system of Subbarayan in view of Edwards, in view of Lagi with the recommended transactions of Daly. Doing so would have enabled the system to improve the interpretability and usefulness of the action objects by enabling a user to understand the relationships between a recommended action, the underlying transaction, and the metric supporting the recommendation.
Claim(s) 9-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Subbarayan et al. (US 20180183737 A1, referred to as Subbarayan, in view of Edwards et al. (US 20210303973 A1, referred to as Edwards), in view of Walter et al. (US 20200012902 A1, referred to as Walters).
Regarding Claim 9, Subbarayan in view of Edwards, in view of Bade, in view of Daly a system comprising:
Subbarayan teaches at least one processing circuit comprising at least one memory coupled to at least one
processor, the at least one processing circuit ([0217-0219], and Figure 8: Describes a computing device which implements in a system and comprises a processor, and a memory which are coupled together in a communication infrastructure. To execute instructions stored in memory on computer hardware.)configured to:
identify, based on a query, first data having an authenticity property and including one or more first transaction records, the first transaction records identifying one or more actual transactions ([0041], and [0199-0203]: Describes analyzing natural language messages from a user to identify purchase information and facilitate a payment transaction, generating a transaction identifier associated with the payment request and payment information, and storing the transaction identifier and payment information in a transaction database. It associates users and transactions with fraud risk or “realness” information based on stored activity and purchase history information, thereby teaching an authenticity related property associated with the identified transaction data.)
Although Subbarayan teaches identify, based on a query, first data having an authenticity property and including one or more first transaction records, the first transaction records identifying one or more actual transactions. It does not teach generate, via an artificial intelligence (AI) model, second data having the authenticity property and including one or more second transaction records, the second transaction records corresponding to one or more synthetic transactions that have not been executed by the one or more entities.
Walters teaches generate, via an artificial intelligence (AI) model, second data having the authenticity property and including one or more second transaction records, the second transaction records corresponding to one or more synthetic transactions that have not been executed by the one or more entities ([0022], [0061], and [0064]: Describes datasets comprising actual data reflecting real world events and further teaches that such datasets may comprise transaction or financial data. It trains machine learning models, including generative adversarial , recurrent neural network, and long short term memory models, to generate synthetic data based on an input dataset comprising actual data.; [0002], [0048], [0050], [0076], and [0079]: Describes generating the synthetic data to appear realistic and training the models based on similarity metrics comparing statistical properties, distributions, correlations, and other characteristic of the synthetic data with those of the actual data. The generated synthetic transaction data possess an authentic related property derived from the actual transaction data while representing fake, rather than actually executed, transactions.).
It would have been obvious to one of ordinary skill in the art at the time of the claimed invention to have combined the system of Subbarayan in view of Edwards, with the realistic synthetic transaction generation of Walters. Doing so would have enabled the system to reduce the need to expose or repeatedly use actual customer transaction data.
Regarding Claim 10, Subbarayan in view of Edwards, in view of Walters teaches the system of claim 9.
Subbarayan further teaches wherein the one or more actual transactions correspond to one or more transactions that have been executed by one or more entities ([0197-0203]: Describes users initiating and completing payment transactions involving identified senders, recipients, merchants and payment accounts, and further discloses generating and storing transaction identifiers and payment information corresponding to those executed transactions. Accordingly, the stored transaction records identify actual transactions carried out by the respective entities.).
Regarding Claim 11, Subbarayan in view of Edwards, in view of Walters teaches the system of claim 9.
Walters further teaches wherein the one or more synthetic transactions correspond to one or more transactions that have not been executed by one or more entities ([0002], and [0022]: Distinguishes actual data reflecting real world conditions or events from synthetic data comprising fake data and teaches that the generated datasets may comprise transaction data or financial data. Accordingly, the generated synthetic transaction records represent fake transactions rather than transactions actually executed by the entities.).
Regarding Claim 12, Subbarayan in view of Edwards, in view of Walters teaches the system of claim 9, wherein the at least one processing circuit is configured to:
cause, in response to a determination that an authenticity metric satisfies a fraud threshold corresponding to an entity among the one or more entities, execution of a transaction including the entity and an object corresponding to the entity (Walters further teaches determining an authenticity metric for generated synthetic data. [0048], [0050], [0076], [0079], and [0102]: Describes evaluating the generated synthetic data using similarity or performance metrics that compare statistical properties, distributions, correlations, and other characteristics of the synthetic data with corresponding actual data. This corresponds toa metric representing the authenticity or realistic similarity of generated data.; Subbarayan further teaches causing execution of a transaction in response to determining that a fraud related metric satisfies a threshold corresponding to an entity. [0197], and [0199-0203]: Describes evaluating a payment transaction based on fraud or risk information associated with a participating user and permits or processes the transaction when the determined risk satisfies the applicable threshold, the transaction involving the user and a recipient, merchant, account, or other transaction object.).
Regarding Claim 13, which corresponds to the same limitations as claim 1 and is rejected for the same reason as described in claim 1.
Regarding Claim 14, Subbarayan in view of Edwards, in view of Walters teaches the system of claim 12,
Edwards further teaches, wherein the at least one processing circuit is further configured to:
cause a user interface to present the entity object ([0162-0165]: Describes disclosing a processor including a user interface generator module configured to generate a user interface, wherein the user interface outputs user recommendation data to the user. An AI model determines how an element of the user interface is presented to the user and that the user interface presents suggestions corresponding to financial plans, transactions, or recommendations associated with the user.).
Regarding Claim 15, Subbarayan in view of Edwards, in view of Walters teaches the system of claim 12, wherein the at least one processing circuit is further configured to:
Walters further teaches generate the authenticity metric based on the entity object and one or more of the synthetic transactions ([0048], [0050], [0076], [0079], and [0102]: Describes evaluating generated synthetic data using similarity or performance metrics based on comparisons between the synthetic data and corresponding actual data, including comparisons of statistical properties, distributions, correlations, covariance, and other characteristics of the datasets.; Subbarayan [0197-0203] teaches that the actual transaction data included information associated with an identified entity and its corresponding account,. payment, recipient, or transaction object. Accordingly, in the combined system, Walters teaches authenticity metric ius generated by comparing the synthetic transaction records with actual transaction information represented by the entity object.).
Regarding Claim 16, Subbarayan in view of Edwards, in view of Walters teaches the system of claim 13, wherein the at least one processing circuit is configured to:
generate, via the AI model, an action object that identifies an action metric, the AI model receiving as input the one or more synthetic transactions and the entity object (Edwards [0072-0073] further teaches generating, via an artificial intelligence model, an action object that identifies an action metric. It uses a transaction optimizing artificial intelligence model to evaluate a particular financial choice or action simulating the choice and measuring whether the choice increases or decreases progress toward the user’s financial goals.; Edwards [0130], [0133], [0157], and [0163-0165]: Describes generating recommendations, workflow steps, or decisions corresponding to actions evaluated by the model. Corresponding to generating an action related output that identifies a metric representing the effect or advisability of the action.; Walters teaches proving one or more synthetic transactions as input to an artificial intelligence model, while Subbarayan teaches transaction information associated with an identified entity and corresponding entity object. Accordingly, Subbarayan in view of Edwards, in view of Walters teaches the artificial intelligence model receives the synthetic transactions and the entity object as inputs and generates the action object identifying the action metric.).
Regarding Claim 17, Subbarayan in view of Edwards, in view of Walters teaches the system of claim 16, wherein the at least one processing circuit is configured to:
Edwards further teaches obtain, via a user interface, a selection of the action object ([0080], [0081], [0133], and [0163]: Describes presenting an option or recommendation to a user through a user interface and receiving user input through an input device, such as a touchscreen, mouse or button, in response to the presented interface element.).
Regarding claim 18, which recites substantially the same limitations as claim 9 and further recites a method (Subbarayan [0006-0007]: Describes using the method steps in the system to execute software on the system.) to execute the system steps of claim 9, respectively, and is therefore rejected for the same reason as described above.
Claim(s) 19, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Subbarayan et al. (US 20180183737 A1, referred to as Subbarayan, in view of Edwards et al. (US 20210303973 A1, referred to as Edwards), in view of Tsimpoukelli, Maria, et al. ( "Multimodal few-shot learning with frozen language models.", referred to as Tsimpoukelli ).
Regarding Claim 19, Subbarayan in view of Edwards, in view of Walters teaches the method of claim 18.
Although Subbarayan in view of Edwards, in view of Walters teaches the method of claim 18 and the action object. They do not teach a large language model (LLM) configured to receive as input a prompt including first text and to generate an output including a second text.
Tsimpoukelli teaches wherein the AI model corresponds to a large language model (LLM) configured to receive as input a prompt including first text and to generate an output including a second text that corresponds to the action object (Sections 1, 3.1, and 3.3 : Describes a pretrained, large autoregressive langue model implemented using a transformer architecture and having approximately seven billion parameters. The language model is conditioned upon arbitrary textual prompt or prefix and autoregressively generates a subsequent textual output sequence. The prompts may include task induction text, questions, examples, or other textual context and that the model generates responsive text including answers, captions, and other open ended linguistic outputs.; Edwards teaches generating an action object or action related output corresponding to a recommended action, financial decision, workflow, or recommendation evaluated by an artificial intelligence model.).
It would have been obvious to one of ordinary skill in the art at the time of the claimed invention to have combined the system of Subbarayan in view of Edwards, in view of Walters with the langue model structure of Tsimpoukelli . Doing so would have enabled the system to provide natural language output corresponding to the identified object while allowing wording and form of the generated output to adapt to the information contained in the prompt.
Regarding Claim 20, which substantially recites the same language as claim 19 and further recites a multi-modal model (MMM)( Tsimpoukelli Sections 1, 3.2, and 3.3: Describes extending a pretrained large language model into a multimodal model by providing visual information together with textual prompts, wherein the model receives prompts including interleaved text and image representations in arbitrary sequences. The multimodal model generates responsive outputs including textual answers, captions, and other open ended language corresponding to the provided prompt. The disclosed multimodal model is capable of performing visual question answering, image captioning, and other vision-langue tasks using both textual and visual inputs.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See attached PTO-892 for additional art including.
US 20230177072 A1: AI system to generate recommendations
US 20240070484 A1: AI financial processing
US 20230289882 A1: text generation
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/D.T.R./Examiner, Art Unit 2128
/OMAR F FERNANDEZ RIVAS/Supervisory Patent Examiner, Art Unit 2128
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