DETAILED ACTION
Notice of Pre-AIA or AIA Status
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 present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 07/25/2024 was filed before the mailing date of a first action. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Objections
Claims 4, 11, and 18 are objected to because of the following informalities.
Claims 4, 11, and 18 recite "the respective rating of each stored prompt" lacks antecedent basis and has been interpreted as "[[the]] --a-- respective rating of each stored prompt".
Appropriate correction is required.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter.
Claim 1 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
The claim recites a method for modifying prompts, comprising: generating, via large language model, a first group of prompts based on receiving a first user prompt from a first user; receiving, from the first user, a first input selecting a first selected prompt of the first group of prompts; generating, via a first generative model, a first output based on the first user selecting the first selected prompt; and receiving, from a second user, a first rating associated with the first output.
The limitation of generating a first group of prompts based on receiving a first user prompt from a first user, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, nothing in the claim element precludes the step from practically being performed in the mind. For example, "generating" in the context of this claim encompasses a user evaluation of a group of prompts based on a user observing a user prompt.
The limitation of receiving, from the first user, a first input selecting a first selected prompt of the first group of prompts, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. For example, "receiving" in the context of this claim encompasses a user observation, evaluation, or judgement of user input selecting an observed or evaluated prompt of an evaluated group of prompts.
The limitation of generating a first output based on the first user selecting the first selected prompt, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. For example, "generating" in the context of this claim encompasses a user evaluation or judgement of output based on an evaluation or judgement selecting the prompt.
The limitation of receiving, from a second user, a first rating associated with the first output, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. For example, "receiving" in the context of this claim encompasses a user observation of another user making a rating judgement associated with the evaluated output.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the "Mental Processes" grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites a large language model and a first generative model. The large language model and first generative model are recited at a high level of generality and recited so generically that they represent no more than mere instructions to apply the judicial exception on a computer [MPEP 2106.05(f)]. These limitations can also be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of machine learning [MPEP 2106.05(h)].
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of a large language model and a first generative model amount to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept.
Considering the additional elements individually and in combination and the claim as a whole, the additional elements do not provide significantly more than the abstract idea. The claim is not patent eligible.
The dependent claims also recite limitations of identifying a subset of prompts from a set of prompts based on receiving a second user prompt from a third user, each stored prompt of the subset of stored prompts associated with a rating; generating a second group of prompts based on the subset of prompts and the second user prompt; receiving, from the third user, a second input selecting a second selected prompt of the second group of prompts; generating a second output based receiving the second input selecting the second selected prompt; and receiving, from a fourth user, a second rating associated with the second output (claims 2, 9, 16); identifying the subset of prompts (claims 3, 10, 17); the respective rating of each stored prompt in the set of stored prompts (claims 4, 11, 18); wherein the subset of prompts is identified based on a quantity of prompts in the set of prompts being greater than a stored prompt threshold (claims 5, 12, 19); wherein the first user is the same user as the third user and/or the second user is the same user as the fourth user (claims 6, 13, 20); generate the first group of prompts; and the first group of prompts is generated in response to a second prompt (claims 7, 14) that are processes that, under its broadest reasonable interpretation, cover performance of the limitation in the mind but for the recitation of generic computer components encompassing user observations or evaluations of a subset of prompts from an observed set of prompts based on a user observation of another prompt of another user, a user evaluation or judgement of another group of prompts based on the evaluated subset of prompts and observed user prompt, a user observation or evaluation of another user selecting another prompt, a user evaluation or judgement of other output based on the evaluated selection input, a user observation or judgement of another rating from another user, a user observation or evaluation identifying the subset of prompts based on observing or evaluating an observed quantity of prompts is greater than another observed quantity, and a user evaluation or judgement of a group of prompts based on an observed prompt and thus fall within the "Mental Processes" grouping of abstract ideas.
This judicial exception is not integrated into a practical application. The dependent claims recite additional limitations including generating via a second generative model (claims 2, 9, 16); an embedding of the second user prompt (claims 3, 10, 17); wherein the large language model is trained, and a second prompt received at the large language model (claims 7, 14) that are recited at a high level of generality and recited so generically that they represent no more than mere instructions to apply the judicial exception on a computer [MPEP 2106.05(f)] and generally link the use of the judicial exception to the technological environment of machine learning [MPEP 2106.05(h)] and do not impose any meaningful limits on practicing the abstract idea. The dependent claims also recite additional limitations of a subset of stored prompts from a set of stored prompts (claims 2, 9, 16) that represent insignificant extra-solution activity including nominal or tangential additions to the claim, amounting to mere data collection [MPEP 2106.05(g)]. Accordingly, the additional elements do not integrate the abstract idea into a practical application because they do not impose meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea.
The dependent claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional elements of storing data are recited at a high level of generality which are well-understood, routine, or conventional activities [MPEP 2106.05(d))(II), "presenting offers and gathering statistics", "electronic recordkeeping", and "storing and retrieving information in memory"] and remain insignificant extra-solution activity even upon reconsideration [MPEP 2106.05(g)]. Mere instructions to apply an exception using generic computer components, linking the use of an exception to a technological field of use, and insignificant extra-solution activity cannot provide an inventive concept. The claims are not patent eligible.
Claim 8 recites method steps substantially similar to those recited in claim 1 and recite an abstract idea. While the claim recites additional elements of an apparatus, processors, memories, and executing stored processor-executable code, the elements are recited at a high level of generality and recited so generically that they represent no more than mere instructions to apply the judicial exception on a computer [MPEP 2106.05(f)] and do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of an apparatus, processors, memories, and executing stored processor-executable code amount to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. Considering the additional elements individually and in combination and the claim as a whole, the additional elements do not provide significantly more than the abstract idea. The claim is not patent eligible.
Claim 15 recites method steps substantially similar to those recited in claim 1 and recite an abstract idea. While the claim recites additional elements of a medium having recorded program code executed, the elements are recited at a high level of generality and recited so generically that they represent no more than mere instructions to apply the judicial exception on a computer [MPEP 2106.05(f)] and do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of a medium having recorded program code executed amount to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. Considering the additional elements individually and in combination and the claim as a whole, the additional elements do not provide significantly more than the abstract idea. The claim is not patent eligible.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Shrivastava et al. (US 20260195930 A1).
As to claim 1, Shrivastava discloses a method for modifying prompts, comprising:
generating, via large language model, a first group of prompts based on receiving a first user prompt from a first user [para 0102, 0107-0108, generate suggested prompt elements (read: first group of prompts) based on initial prompt (read: first user prompt) from client user with machine learning language model];
receiving, from the first user, a first input selecting a first selected prompt of the first group of prompts [para 0122, obtain second user input (read: first input) selecting suggested prompt element of suggested prompt elements];
generating, via a first generative model, a first output based on the first user selecting the first selected prompt [para 0125, generates output responsive to providing obtained second user input selecting suggested prompt element to generation model]; and
receiving, from a second user, a first rating associated with the first output [para 0063-0064, 0098-0099, obtain feedback (read: first rating) scored by human on different client device of generated output].
As to claim 2, Shrivastava discloses the method of claim 1, further comprising:
identifying a subset of stored prompts from a set of stored prompts based on receiving a second user prompt from a third user, each stored prompt of the subset of stored prompts associated with a rating [para 0102, 0107-0108, 0112, obtain suggested prompt elements (read: subset of stored prompts) from suggested prompt elements stored in cache (read: set of stored prompts) from obtained initial prompt (read: second user prompt) from client user device (read: third user)];
generating a second group of prompts based on the subset of stored prompts and the second user prompt [para 0107-0108, 0112, generate suggested prompt elements (read: second group of prompts) in addition to obtaining stored suggested prompt elements from obtained initial prompt];
receiving, from the third user, a second input selecting a second selected prompt of the second group of prompts [para 0112, 0122, obtain second user input from client user selecting suggested prompt element];
generating, via a second generative model, a second output based receiving the second input selecting the second selected prompt [para 0124-0125, generate output responsive to providing obtained second user input to generation model]; and
receiving, from a fourth user, a second rating associated with the second output [para 0063-0064, 0098-0099, obtain feedback (read: first rating) scored by human on different client device of generated output].
As to claim 3, Shrivastava discloses the method of claim 2, wherein the subset of stored prompts are identified based on an embedding of the second user prompt [para 0110-0112, 0161, 0165, select suggested prompt elements based on embedding the prompt input and determining distance (read: embedding) between initial prompt and prompt elements]
As to claim 4, Shrivastava discloses the method of claim 2, wherein the subset of stored prompts identified based on the respective rating of each stored prompt in the set of stored prompts [para 0059-0060, 0115-0116, determine obtained suggested prompt elements based on score (read: rating) for each respective prompt element]
As to claim 5, Shrivastava discloses the method of claim 2, wherein the subset of stored prompts is identified based on a quantity of stored prompts in the set of stored prompts being greater than a stored prompt threshold [para 0079, 0081, select top N (read: stored prompt threshold) of suggested prompt elements from number (read: quantity) of stored prompt elements]
As to claim 6, Shrivastava discloses the method of claim 2, wherein the first user is the same user as the third user and/or the second user is the same user as the fourth user [para 0102, obtain initial user prompt input used to generate and additionally obtain suggested prompt elements from client device user]
As to claim 7, Shrivastava discloses the method of claim 1, wherein:
the large language model is trained to generate the first group of prompts [para 0088, 0129, train machine learning language model generating output]; and
the first group of prompts is generated in response to a second prompt received at the large language model [para 0102, 0107-0108, generate suggested prompt elements based on transmitting obtained initial user prompt and context (read: second prompt) to generation model including machine learning language model].
As to claim 8, Shrivastava discloses an apparatus for modifying prompts, comprising: one or more processors; and one or more memories coupled with the one or more processors and storing processor-executable code that, when executed by the one or more processors, is configured to cause the apparatus [para 0135, system includes processor and memory storing instructions executed by processor] to: perform limitations substantially similar to those recited in claim 1 and is rejected under similar rationale.
As to claims 9-14, Shrivastava discloses the apparatus of claim 8 comprising limitations substantially similar to those recited in claims 2-7, respectively, and are rejected under similar rationale.
As to claim 15, Shrivastava discloses a non-transitory computer-readable medium having program code recorded thereon for modifying prompts, the program code executed by one or more processors [para 0135, system includes memory storing instructions executed by processor] and comprising: perform limitations substantially similar to those recited in claim 1 and is rejected under similar rationale.
As to claims 16-20, Shrivastava discloses the apparatus of claim 8 comprising limitations substantially similar to those recited in claims 2-6, respectively, and are rejected under similar rationale.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Fitzmaurice et al. (US 20250131167 A1) generally disclose large language model systems generating modified prompts.
Iu et al. (US 20240273286 A1) generally discloses multiple users providing ratings associated with iterative outputs via generative models based on generated large language model prompts.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LINDA HUYNH whose telephone number is (571)272-5240. The examiner can normally be reached M-F between 9am-5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Adam Queler can be reached at (571) 272-4140. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/LINDA HUYNH/Primary Examiner, Art Unit 2172
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