DETAILED ACTION
In the response filed October 2, 2025, the Applicant amended claims 1, 9, and 17; and canceled claims 8 and 16. Claims 1-7, 9-15, and 17-20 are pending in the current application.
Notice of 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 .
Response to Arguments
In the non-final office action mailed 02 July 2025, claim 17 was presumed to be interpreted under 35 U.S.C. 112(f) for the limitation “a large language model.” Upon reconsideration, the cited limitation of the claim is determined to not invoke the interpretation under 35 U.S.C. 112(f) due to the term “model” not being a nonce term. BRI of the term “model” is considered to be an algorithm and is considered to be software. Furthermore, the amendment to claim 17, “large language model circuitry” does not invoke 112(f) due to the term “circuitry” being structure. Accordingly, the currently amended limitation “large language model circuitry” also does not invoke interpretation under 35 U.S.C. 112(f).
The drawings were objected to for informalities. Examiner thanks the Applicant for revising and amending the disclosure and hereby withdraws the objection from the previous Office action.
Applicant’s arguments for claims 1-7, 9-15, and 17-20 with respect to the 35 U.S.C. 101 rejection have been considered but are unpersuasive. Applicant argues that the claims are not directed to a judicial exception. Examiner respectfully disagrees. Here, under broadest reasonable interpretation, the steps still describe or set-forth generating and providing a customized message to customers, which amounts to commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations). These limitations therefore fall within the “certain methods of organizing human activity” subject matter grouping of abstract ideas.
Applicant argues that the claims are not directed to a judicial exception as they integrate the exception into a practical application. Examiner respectfully disagrees. The steps and limitations as claimed is executed by “a non-transitory machine-readable storage medium,” and “programmable circuitry,” (claim 1); “a system comprising: programmable circuitry; a memory,” (claim 9); and “large language model circuitry,” “the parameterized prompt template formatted using a structured query language;” (claims 1, 9, and 17), is equivalent to adding the words “apply it” on a generic computer and/or mere instructions to implement the abstract idea on a generic computer. These limitations do not impose any meaningful limits on practicing the abstract idea, and therefore do/does not integrate the abstract idea into a practical application. See § MPEP 2106.05(f).
Viewing the additional limitations in combination also shows that they fail to ensure the claims amount to significantly more than the abstract idea. When considered as an ordered combination, the additional components of the claims add nothing that is not already present when considered separately, and thus simply append the abstract idea with words equivalent to “apply it” on a generic computer and/or mere instructions to implement the abstract idea on a generic computer. Applicant’s arguments remain unpersuasive. The 35 U.S.C. 101 rejection is hereby maintained.
Applicant’s arguments for claims 1-7, 9-15, and 17-20 with respect to the 35 U.S.C. 102/103 rejections have been considered but are moot as they do not apply to the combination of references being used in the current rejection.
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 1-7, 9-15, and 17-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step 1: Claims 1-7 are drawn to a process, claims 9-15 are drawn to a device, and claims 17-20 are drawn to a product of manufacture, each of which is within the four statutory categories (e.g., a process, a machine). (Step 1: YES).
Step 2A – Prong One: In prong one of step 2A, the claims are analyzed to evaluate whether they recite a judicial exception.
Claim 1 (representative of claims 9 and 17) recites/describes the following steps:
“select a parameterized prompt template based on an intended purpose of a customized customer message and a type of communication of the customized customer message”
“generate a prompt based on the parameterized prompt template by causing execution of the parameterized prompt template;”
“provide the prompt to …cause generation of the customized customer message;” and
“cause transmission of the customized customer message.”
These steps, under broadest reasonable interpretation, describe or set-forth generating and providing a customized message to customers, which amounts to commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations). These limitations therefore fall within the “certain methods of organizing human activity” subject matter grouping of abstract ideas.
As such, the Examiner concludes that claim 1 recites an abstract idea (Step 2A – Prong One: YES).
Each of the depending claims 2-7, 10-15, and 18-20 likewise recite/describe these steps (by incorporation - and therefore also recite limitations that fall within this subject matter grouping of abstract ideas), and these claims are therefore determined to recite an abstract idea under the same analysis. Any elements recited in a dependent claim that are not specifically identified/addressed by the Examiner under step 2A (prong two) or step 2B of this analysis shall be understood to be an additional part of the abstract idea recited by that particular claim.
Step 2A – Prong Two:
The claims recite the additional elements/limitations of: “a non-transitory machine-readable storage medium,” and “programmable circuitry,” (claim 1); “a system comprising: programmable circuitry; a memory,” (claim 9); and “large language model circuitry,” “the parameterized prompt template formatted using a structured query language;” (claims 1, 9, and 17).
The requirement to execute the claimed steps/functions using “a non-transitory machine-readable storage medium,” and “programmable circuitry,” (claim 1); “a system comprising: programmable circuitry; a memory,” (claim 9); and “large language model circuitry,” “the parameterized prompt template formatted using a structured query language;” (claims 1, 9, and 17), is equivalent to adding the words “apply it” on a generic computer and/or mere instructions to implement the abstract idea on a generic computer. These limitations do not impose any meaningful limits on practicing the abstract idea, and therefore do/does not integrate the abstract idea into a practical application. See § MPEP 2106.05(f).
Remaining dependent claims 2-7, 10-15, and 18-20 either recite the same additional elements as noted above or fail to recite any additional elements (in which case, note prong one analysis as set forth above – those claims are further part of the abstract idea as identified by the Examiner for each respective dependent claim).
The Examiner has therefore determined that the additional elements, or combination of additional elements, do not integrate the abstract idea into a practical application. Accordingly, the claims are directed to an abstract idea (Step 2A – Prong two: NO).
Step 2B:
As discussed above in “Step 2A – Prong 2,” the requirement to execute the claimed steps/functions using “a non-transitory machine-readable storage medium,” and “programmable circuitry,” (claim 1); “a system comprising: programmable circuitry; a memory,” (claim 9); and “large language model circuitry,” “the parameterized prompt template formatted using a structured query language;” (claims 1, 9, and 17), is equivalent to adding the words “apply it” on a generic computer and/or mere instructions to implement the abstract idea on a generic computer. These limitations therefore do not qualify as “significantly more.” See MPEP § 2106.05(f).
Viewing the additional limitations in combination also shows that they fail to ensure the claims amount to significantly more than the abstract idea. When considered as an ordered combination, the additional components of the claims add nothing that is not already present when considered separately, and thus simply append the abstract idea with words equivalent to “apply it” on a generic computer and/or mere instructions to implement the abstract idea on a generic computer.
Remaining dependent claims 2-7, 10-15, and 18-20 either recite the same additional elements as noted above or fail to recite any additional elements (in which case, note prong one analysis as set forth above – those claims are further part of the abstract idea as identified by the Examiner for each respective dependent claim).
The Examiner has therefore determined that no additional element, or combination of additional claims elements is/are sufficient to ensure the claims amount to significantly more than the abstract idea identified above (Step 2B: NO).
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 for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-4, 7, 9-12, 15, and 17-20, are rejected under 35 U.S.C. 103 as being unpatentable over Luzhnica et al. (US 11,516,158 B1), hereinafter Luzhnica, in view of Burton (US 12,210,839 B1).
Regarding claim 1, Luzhnica discloses a non-transitory machine-readable storage medium comprising instructions that (Col. 60: Lines 18-22), when executed or instantiated by programmable circuitry (Col. 58: Lines 45-50), facilitate performance of operations, comprising:
select a prompt template (Col. 83: Lines 32-38, Structural prompts (also called template prompts) are NN prompts that direct one or more aspects of message generation other than the content of the message; Col. 84: Lines 36-40 structural prompts can come in either the format mentioned above where users or associated users give instructions in a line after line manner, by user selection, or in a templated manner. For example, a templated structural prompt might have the following type of format, prompt format selected to include the following information) based on an intended purpose of a customized customer message (Col. 83: Line 66 – Col. 84: Line 6, Structural prompts can also use keywords, recognized prompt categories/statement categories and the like (e.g., where a system is trained to recognize "news" as a category of statement, prompt elements, or inputs) and a type of communication of the customized customer message (Col. 83: Lines 38-41, structural prompts can direct the system to generate messages that are adapted to a style of presentation, or to prepare messages of a certain presentation (e.g., an email, an audio file, a video, etc.));
generate a prompt based on the prompt template (Col. 84: Lines 35-39, structural prompt generated in a templated manner);
provide the prompt to large language model circuitry to cause generation of the customized customer message (Col. 84: Lines 47-59, message generated from the neural network or (natural language model – Col. 69: Lines 13-15) using a structural prompt); and
cause transmission of the customized customer message (Col.108: Lines 35-42, In aspects, most, generally all, or essentially all output is a message that is generally ready for transmission to an intended recipient. In aspects, methods/systems provide an option to selectively transmit messages to recipients).
Luzhnica does not explicitly disclose a parameterized prompt template, the parameterized prompt template formatted using a structured query language; and generate a prompt based on the parameterized prompt template by causing execution of the prompt template.
Burton teaches a parameterized prompt template (Col. 72, Lines 50-53, the system may cause a semantic stored procedure to be synthesized by the use of iterative or chained prompting with prompt-generating template prompts, or “metaprompts”), the parameterized prompt template formatted using a structured query language (Col. 72, Lines 42-49, the semantic stored procedures may be held in a database or library of these procedures within or without the boundaries of the system, and produced by a curator. Or, by using a query language subexpression corresponding to a stored semantic procedure parameterized to be constructed in a deferred manner); and generate a prompt based on the parameterized prompt template by causing execution of the prompt template (Col. 72, Lines 56-57, the system may apply metaprompts to construct the terminal prompt).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the prompt system of Luzhnica to include the parametrized template abilities of Burton since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. It would have been recognized that applying the technique of Burton to the teachings of Luzhnica would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such prompt features into similar system. As in Burton, it is within the capabilities of one of ordinary skill in the art to include the parameterized template features to Luzhnica’s prompt system with the predicted result of generating a customized customer message as needed in Luzhnica.
Regarding claim 2, Luzhnica discloses wherein the generated prompt includes customer data (Col. 87: Lines 46-50, the situational prompts, instructional prompts, initial training set, or any combination thereof comprises information about one or more organizations associated with one or more audience members; Col. 88: Lines 36-51).
Regarding claim 3, Luzhnica discloses wherein the customer data is representative of a plurality of customers (Col. 87: Lines 46-50, the situational prompts, instructional prompts, initial training set, or any combination thereof comprises information about one or more organizations associated with one or more audience members).
Regarding claim 4, Luzhnica discloses wherein the operations further comprise generating an embedding based on customer data (Col. 73: Lines 9-14, associated with additional data elements in records (e.g., metadata tags, additional context, and the like). E.g., in aspects, natural language message components of a method, such as prompts, training set data, or both, may subjected to embedding – prompts which include customer data are subjected to embedding), the embedding provided to the large language model as a context for the prompt Col. 73: Lines 9-14, prompts are subjected to embedding/associated with additional context).
Regarding claim 7, Luzhnica discloses wherein the operations comprise analyzing the customized customer message to confirm that the customized customer message is acceptable for transmission, wherein the transmission of the customized customer message is to occur after the confirmation that the customized customer message is acceptable for transmission (Col. 115: Lines 25-29, Draft messages, #128, are delivered, #202, back to the 25 user, #102, via an interface. The user in turn can provide feedback regarding a message (e.g., a like/dislike selection, a rating, etc.), can edit the message, or can elect to transmit message(s) to audience member(s)).
Regarding claim 9, Luzhnica discloses a system comprising: programmable circuitry (Col. 58: Lines 45-50); a memory that stores executable instructions that (Col. 60: Lines 18-22), when executed or instantiated by the programmable circuitry, facilitate performance of operations including:
select a prompt template (Col. 83: Lines 32-38, Structural prompts (also called template prompts) are NN prompts that direct one or more aspects of message generation other than the content of the message; Col. 84: Lines 36-40 structural prompts can come in either the format mentioned above where users or associated users give instructions in a line after line manner, by user selection, or in a templated manner. For example, a templated structural prompt might have the following type of format, prompt format selected to include the following information) based on an intended purpose of a customized customer message (Col. 83: Line 66 – Col. 84: Line 6, Structural prompts can also use keywords, recognized prompt categories/statement categories and the like (e.g., where a system is trained to recognize "news" as a category of statement, prompt elements, or inputs) and a type of communication of the customized customer message (Col. 83: Lines 38-41, structural prompts can direct the system to generate messages that are adapted to a style of presentation, or to prepare messages of a certain presentation (e.g., an email, an audio file, a video, etc.));
generate a prompt based on the prompt template (Col. 84: Lines 35-39, structural prompt generated in a templated manner);
provide the prompt to a large language model to cause generation of the customized customer message (Col. 84: Lines 47-59, message generated from the neural network or (natural language model – Col. 69: Lines 13-15) using a structural prompt); and
cause transmission of the customized customer message (Col.108: Lines 35-42, In aspects, most, generally all, or essentially all output is a message that is generally ready for transmission to an intended recipient. In aspects, methods/systems provide an option to selectively transmit messages to recipients).
Luzhnica does not explicitly disclose a parameterized prompt template, the parameterized prompt template formatted using a structured query language; and generate a prompt based on the parameterized prompt template by causing execution of the prompt template.
Burton teaches a parameterized prompt template (Col. 72, Lines 50-53, the system may cause a semantic stored procedure to be synthesized by the use of iterative or chained prompting with prompt-generating template prompts, or “metaprompts”), the parameterized prompt template formatted using a structured query language (Col. 72, Lines 42-49, the semantic stored procedures may be held in a database or library of these procedures within or without the boundaries of the system, and produced by a curator. Or, by using a query language subexpression corresponding to a stored semantic procedure parameterized to be constructed in a deferred manner); and generate a prompt based on the parameterized prompt template by causing execution of the prompt template (Col. 72, Lines 56-57, the system may apply metaprompts to construct the terminal prompt).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the prompt system of Luzhnica to include the parametrized template abilities of Burton since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. It would have been recognized that applying the technique of Burton to the teachings of Luzhnica would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such prompt features into similar system. As in Burton, it is within the capabilities of one of ordinary skill in the art to include the parameterized template features to Luzhnica’s prompt system with the predicted result of generating a customized customer message as needed in Luzhnica.
Regarding claim 10, Luzhnica discloses wherein the generated prompt includes customer data (Col. 87: Lines 46-50, the situational prompts, instructional prompts, initial training set, or any combination thereof comprises information about one or more organizations associated with one or more audience members; Col. 88: Lines 36-51).
Regarding claim 11, Luzhnica discloses wherein the customer data is representative of a plurality of customers (Col. 87: Lines 46-50, the situational prompts, instructional prompts, initial training set, or any combination thereof comprises information about one or more organizations associated with one or more audience members).
Regarding claim 12, Luzhnica discloses wherein the operations further comprise generating an embedding based on customer data (Col. 73: Lines 9-14, associated with additional data elements in records (e.g., metadata tags, additional context, and the like). E.g., in aspects, natural language message components of a method, such as prompts, training set data, or both, may subjected to embedding – prompts which include customer data are subjected to embedding), the embedding provided to the large language model as a context for the prompt Col. 73: Lines 9-14, prompts are subjected to embedding/associated with additional context).
Regarding claim 15, Luzhnica discloses wherein the operations comprise analyzing the customized customer message to confirm that the customized customer message is acceptable for transmission, wherein the transmission of the customized customer message is to occur after the confirmation that the customized customer message is acceptable for transmission (Col. 115: Lines 25-29, Draft messages, #128, are delivered, #202, back to the 25 user, #102, via an interface. The user in turn can provide feedback regarding a message (e.g., a like/dislike selection, a rating, etc.), can edit the message, or can elect to transmit message(s) to audience member(s)).
Regarding claim 17, Luzhnica discloses a method for generating a customized customer message, the method comprising:
selecting a prompt template (Col. 83: Lines 32-38, Structural prompts (also called template prompts) are NN prompts that direct one or more aspects of message generation other than the content of the message; Col. 84: Lines 36-40 structural prompts can come in either the format mentioned above where users or associated users give instructions in a line after line manner, by user selection, or in a templated manner. For example, a templated structural prompt might have the following type of format, prompt format selected to include the following information) based on an intended purpose of the customized customer message (Col. 83: Line 66 – Col. 84: Line 6, Structural prompts can also use keywords, recognized prompt categories/statement categories and the like (e.g., where a system is trained to recognize "news" as a category of statement, prompt elements, or inputs) and a type of communication of the customized customer message (Col. 83: Lines 38-41, structural prompts can direct the system to generate messages that are adapted to a style of presentation, or to prepare messages of a certain presentation (e.g., an email, an audio file, a video, etc.));
generating a prompt based on the prompt template (Col. 84: Lines 35-39, structural prompt generated in a templated manner);
providing the prompt to a large language model to cause generation of the customized customer message (Col. 84: Lines 47-59, message generated from the neural network or (natural language model – Col. 69: Lines 13-15) using a structural prompt); and
causing transmission of the customized customer message (Col.108: Lines 35-42, In aspects, most, generally all, or essentially all output is a message that is generally ready for transmission to an intended recipient. In aspects, methods/systems provide an option to selectively transmit messages to recipients).
Luzhnica does not explicitly disclose a parameterized prompt template, the parameterized prompt template formatted using a structured query language; and generate a prompt based on the parameterized prompt template by causing execution of the prompt template.
Burton teaches a parameterized prompt template (Col. 72, Lines 50-53, the system may cause a semantic stored procedure to be synthesized by the use of iterative or chained prompting with prompt-generating template prompts, or “metaprompts”), the parameterized prompt template formatted using a structured query language (Col. 72, Lines 42-49, the semantic stored procedures may be held in a database or library of these procedures within or without the boundaries of the system, and produced by a curator. Or, by using a query language subexpression corresponding to a stored semantic procedure parameterized to be constructed in a deferred manner); and generate a prompt based on the parameterized prompt template by causing execution of the prompt template (Col. 72, Lines 56-57, the system may apply metaprompts to construct the terminal prompt).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the prompt system of Luzhnica to include the parametrized template abilities of Burton since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. It would have been recognized that applying the technique of Burton to the teachings of Luzhnica would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such prompt features into similar system. As in Burton, it is within the capabilities of one of ordinary skill in the art to include the parameterized template features to Luzhnica’s prompt system with the predicted result of generating a customized customer message as needed in Luzhnica.
Regarding claim 18, Luzhnica discloses wherein the generated prompt includes customer data (Col. 87: Lines 46-50, the situational prompts, instructional prompts, initial training set, or any combination thereof comprises information about one or more organizations associated with one or more audience members; Col. 88: Lines 36-51).
Regarding claim 19, Luzhnica discloses wherein the customer data is representative of a plurality of customers (Col. 87: Lines 46-50, the situational prompts, instructional prompts, initial training set, or any combination thereof comprises information about one or more organizations associated with one or more audience members).
Regarding claim 20, Luzhnica discloses wherein the operations further comprise generating an embedding based on customer data (Col. 73: Lines 9-14, associated with additional data elements in records (e.g., metadata tags, additional context, and the like). E.g., in aspects, natural language message components of a method, such as prompts, training set data, or both, may subjected to embedding – prompts which include customer data are subjected to embedding), the embedding provided to the large language model as a context for the prompt Col. 73: Lines 9-14, prompts are subjected to embedding/associated with additional context).
Claims 5, 6, 13, and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Luzhnica (US 11,516,158 B1) in view of Burton (US 12,210,839 B1) and Zheng (US 2024/0329926 A1).
Regarding claim 5, Luzhnica discloses computing the embedding based on customer data (Col. 73: Lines 9-14, associated with additional data elements in records (e.g., metadata tags, additional context, and the like). E.g., in aspects, natural language message components of a method, such as prompts, training set data, or both, may subjected to embedding – prompts which include customer data are subjected to embedding), the embedding provided to the large language model as a context for the prompt Col. 73: Lines 9-14, prompts are subjected to embedding/associated with additional context). Luzhnica does not explicitly disclose wherein the operations further comprise: accessing a plurality of fields of customer data; removing fields having null or empty data from the plurality of columns; sorting the remaining fields; separating the sorted fields into a first group of fields and a second group of fields; and computing the embedding based on the first group of fields and randomly selected fields from the second group of fields.
Zheng teaches accessing a plurality of fields of customer data (Par. [0031], arrangement data of multi-column data);
removing fields having null or empty data from the plurality of columns (Par. [0051], null value directly ignored, null values removed);
sorting the remaining fields (Par, [0079, final sorting – removing null values to obtain sorted row identification sequence);
separating the sorted fields into a first group of fields and a second group of fields (Par. [0045], columns grouped in column and IdRelation “CIR” groups CIR1, CIR2).
It would have been obvious to one of ordinary skill in the art before the effective filing data to include in the customized message system of Luzhnica and Burton to include the customer data managing abilities of Zheng to teach “wherein the operations further comprise: accessing a plurality of fields of customer data; removing fields having null or empty data from the plurality of columns; sorting the remaining fields; separating the sorted fields into a first group of fields and a second group of fields; and computing the embedding based on the first group of fields and randomly selected fields from the second group of fields,” as a need exists to optimize multi-column data to improve data processing efficiency and increase user experience (Zheng, Par. [0018]).
It would have been obvious to one of ordinary still in the art before the effective filing date to include in the customized messaging system of Luzhnica and Burton the ability to optimize data as taught by Zheng since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 6, Luzhnica discloses aggregating the first embedding and the second embedding to create an aggregated embedding, the aggregated embedding used as the context for the prompt (Col. 73: Lines 9-14, Records relating to natural language messages can, at various stages of storage, use, etc., be put into (translated into) different form not corresponding to natural language and analyzed, stored, relayed, etc., in such modified forms (e.g., in a machine-readable code, programming language, vector, or other encoding) or can be associated with additional data elements in records (e.g., metadata tags, additional context, and the like)). Luzhnica does not explicitly disclose generating a second embedding based on the first group of fields and second randomly selected fields from the second group of fields. Zheng teaches based on the first group of fields and second randomly selected fields from the second group of fields (Par. [0045], columns grouped in column and IdRelation “CIR” groups CIR1, CIR2; Par. [0036]. [0044], randomly selected fields from the second group of fields).
It would have been obvious to one of ordinary skill in the art before the effective filing data to include in the customized message system of Luzhnica and Burton to include the customer data managing abilities of Zheng to teach “wherein the operations further comprise: accessing a plurality of fields of customer data; removing fields having null or empty data from the plurality of columns; sorting the remaining fields; separating the sorted fields into a first group of fields and a second group of fields; and computing the embedding based on the first group of fields and randomly selected fields from the second group of fields,” as a need exists to optimize multi-column data to improve data processing efficiency and increase user experience (Zheng, Par. [0018]).
It would have been obvious to one of ordinary still in the art before the effective filing date to include in the customized messaging system of Luzhnica and Burton the ability to optimize data as taught by Zheng since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 13, Luzhnica discloses computing the embedding based on customer data (Col. 73: Lines 9-14, associated with additional data elements in records (e.g., metadata tags, additional context, and the like). E.g., in aspects, natural language message components of a method, such as prompts, training set data, or both, may subjected to embedding – prompts which include customer data are subjected to embedding), the embedding provided to the large language model as a context for the prompt Col. 73: Lines 9-14, prompts are subjected to embedding/associated with additional context). Luzhnica does not explicitly disclose wherein the operations further comprise: accessing a plurality of fields of customer data; removing fields having null or empty data from the plurality of columns; sorting the remaining fields; separating the sorted fields into a first group of fields and a second group of fields; and computing the embedding based on the first group of fields and randomly selected fields from the second group of fields.
Zheng teaches accessing a plurality of fields of customer data (Par. [0031], arrangement data of multi-column data);
removing fields having null or empty data from the plurality of columns (Par. [0051], null value directly ignored, null values removed);
sorting the remaining fields (Par, [0079, final sorting – removing null values to obtain sorted row identification sequence);
separating the sorted fields into a first group of fields and a second group of fields (Par. [0045], columns grouped in column and IdRelation “CIR” groups CIR1, CIR2); randomly selected fields from the second group of fields (Par. [0036]. [0044]).
It would have been obvious to one of ordinary skill in the art before the effective filing data to include in the customized message system of Luzhnica and Burton to include the customer data managing abilities of Zheng to teach “wherein the operations further comprise: accessing a plurality of fields of customer data; removing fields having null or empty data from the plurality of columns; sorting the remaining fields; separating the sorted fields into a first group of fields and a second group of fields; and computing the embedding based on the first group of fields and randomly selected fields from the second group of fields,” as a need exists to optimize multi-column data to improve data processing efficiency and increase user experience (Zheng, Par. [0018]).
It would have been obvious to one of ordinary still in the art before the effective filing date to include in the customized messaging system of Luzhnica and Burton the ability to optimize data as taught by Zheng since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 14, Luzhnica discloses aggregating the first embedding and the second embedding to create an aggregated embedding, the aggregated embedding used as the context for the prompt (Col. 73: Lines 9-14, Records relating to natural language messages can, at various stages of storage, use, etc., be put into (translated into) different form not corresponding to natural language and analyzed, stored, relayed, etc., in such modified forms (e.g., in a machine-readable code, programming language, vector, or other encoding) or can be associated with additional data elements in records (e.g., metadata tags, additional context, and the like)). Luzhnica does not explicitly disclose generating a second embedding based on the first group of fields and second randomly selected fields from the second group of fields. Zheng teaches based on the first group of fields and second randomly selected fields from the second group of fields (Par. [0045], columns grouped in column and IdRelation “CIR” groups CIR1, CIR2; Par. [0036]. [0044], randomly selected fields from the second group of fields).
It would have been obvious to one of ordinary skill in the art before the effective filing data to include in the customized message system of Luzhnica and Burton to include the customer data managing abilities of Zheng to teach “wherein the operations further comprise: accessing a plurality of fields of customer data; removing fields having null or empty data from the plurality of columns; sorting the remaining fields; separating the sorted fields into a first group of fields and a second group of fields; and computing the embedding based on the first group of fields and randomly selected fields from the second group of fields,” as a need exists to optimize multi-column data to improve data processing efficiency and increase user experience (Zheng, Par. [0018]).
It would have been obvious to one of ordinary still in the art before the effective filing date to include in the customized messaging system of Luzhnica and Burton the ability to optimize data as taught by Zheng since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/Patrick Kim/Examiner, Art Unit 3628
/RESHA DESAI/Supervisory Patent Examiner, Art Unit 3628
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