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 .
Specification
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed.
The following title is suggested: --Terminal, Control Method of Terminal, and Non-Transitory Computer-readable Storage Medium for Providing Explanatory Text Related to a Method of Using an Application based upon Language Model Prompting--.
Claim Objections
Claims 4 and 9 are objected to because of the following informalities:
In claim 4, "execute the set of instructions to calculates" should be corrected to read --execute the set of instructions to calculate--.
Claim 9 depends upon claim 4 and inherits the minor informality of claim 4 by virtue of its dependency.
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 1-14 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.
In Claim 1, Lines 7-8, "the operation history of an application selected by a user" lacks antecedent basis and it is unclear what prior limitation is being referenced. For claim interpretation in the interest of compact prosecution, "the operation history of an application selected by a user" will be construed as --an operation history of an application selected by a user--. A similar antecedent basis issue applies to "the application for which the user requests an explanation of a method of using" found in lines 9-10 where this limitation will be construed as --an application for which the user requests an explanation of a method of using-- in the interest of compact prosecution for claim interpretation purposes. Independent Claims 13-14 contain similar antecedent basis issues and have been likewise rejected under 35 U.S.C. 112(b) for being indefinite.
In Claim 5, "the operation history of an application different from the selected application" lacks antecedent basis and it is unclear what prior limitation is being referenced. For claim interpretation in the interest of compact prosecution, "the operation history of an application different from the selected application" will be construed as --an operation history of an application different from the selected application--.
The remaining dependent claims further limit and inherit the indefinite subject matter of independent claim 1 (and 5 in the case of claim 10), and thus, have also been rejected under 35 U.S.C. 112(b) by virtue of their dependency.
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 1-14 are rejected under 35 U.S.C. 101 for being directed towards a patent ineligible abstract idea under the broadest reasonable interpretation (BRI).
Independent Claims 1, 13, and 14 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims regard a process that, as drafted under its broadest reasonable interpretation, covers performance of the limitations as a mental process, but for the recitation of generic computer components. Note also that though the claimed process/functionality mentions a generic language model (LM), the involvement of the LM is passive as is described in the following mental process analysis under the BRI.
In regards to the process the independent claims, the claimed functionality could be practiced as a mental process in the following manner:
acquire an operation history of each of a plurality of applications installed in own apparatus (a human could manually obtain an operation history by reviewing/reading documentation or a log);
generate a prompt to be input into a language model using the operation history of an application selected by a user from among the plurality of applications as the application for which the user requests an explanation of a method of using (a human could obtain this information and compile such information into the form of a request including the operation history and a particular operation; note here that the LM is generic and not being used for any type of processing where the LM is instead the intended target for the prompt); and
present to the user an explanatory text related to a method of using the selected application, the explanatory text being acquired from the language model using the generated prompt (a human could read and mentally process text acquired from a language model by reading and then handing suggested training help documentation to another person manually).
This judicial exception is not integrated into a practical application. Outside of the identified abstract idea, the claimed invention only recites computer components (e.g., processor, programs, machine-readable storage media) that amount to no more than mere instructions to implement an otherwise abstract idea using generic computer components and a passive mention of a generic LM that only serves intended target of a prompt that could be generated by a human and output that could be read/reviewed mentally by a human under the BRI that does not involve any processing by an LM let alone a particularly trained LM or model invented/improved by Applicant.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The above identified additional generic computer components are no more than mere instructions to apply the exception using generic computer components that are well-known, routine, and conventional as is evidenced by Bancorp Services v. Sun Life (Fed. Cir. 2012) and Alice Corp. v. CLS Bank (2014). Also, while it is noted that the identified LM is part of the mental process under the BRI due to the passivity of the model in the claims, the specification does provide evidence that the model is well-known via the citation of interchangeable, publicly available LMs provided in the specification (e.g., RoBERTa and T5) (Paragraph 0085).
Accordingly, at least independent Claims 1, 13, and 14 are not patent eligible under 35 U.S.C. 101.
The remaining dependent claims fail to add patent eligible subject matter to their respective parent claims:
Claims 2-10 narrow the type of information included in the generated prompt that can be generated by a person via a calculation and manually combined with the other information using pen and paper or remembered.
Claim 11 regards communication over a network as a communication medium for extra solutional data gathering. Note that communication over a network is well-known, routine, and conventional as per Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information) and buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network).
Claim 12 regards generic computer components as addressed in the independent claims.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-2, 4-7, and 9-14 are rejected under 35 U.S.C. 103 as being unpatentable over Bhowmick, et al. (U.S. PG Publication: 2019/0324778 A1) in view of Luus, et al. (U.S. PG Publication: 2024/0428275 A1).
With respect to Claim 1, Bohwmick discloses:
A terminal, comprising:
at least one memory storing a set of instructions (computer-readable media such as a memory storing instructions, Paragraphs 0024, 0028, and 0073); and
at least one processor configured to execute the set of instructions (one or more processors to execute the set of instructions, Paragraphs 0024, 0028, and 0073) to:
acquire an operation history of each of a plurality of applications installed in own apparatus (collection of in-app history, Paragraph 0054; plurality of applications, Paragraph 0028; depiction of application installed on user device, Fig. 1, Element 110);
generate a prompt to be input into a (generating a prompt/request for help from a user for a selected application that includes the in-app history, Paragraphs 0054-0055; wherein the contextual help system utilizes a machine learning (i.e., neural network) model, Paragraphs 0032 and 0040); and
present to the user an explanatory text related to a method of using the selected application, the explanatory text being acquired from the (help documentation is identified based upon the prompted in-app history and presented to the user in a text document format, Paragraphs 0014, 0022, 0050, and 0055; Fig. 3, Element 312).
While Bohwmick teaches the overall application help process based upon in-app operation history, the model used by Bohwmick is a neural network rather than the generic language model recited in the instant claim that is not explicitly taught by Bohwmick. Luus, however, discloses large language models (LLMs) are used to generate instructional guidance/walkthrough for the completion of a software application tasks (Paragraph 0023, 0029, 0031, and 0044-0045).
Bohwmick and Luus are analogous art because they are from a similar field of endeavor in software application guidance using machine learning models. Thus, it would have been obvious to one of ordinary skill before the effective filing date to substitute the LLMs taught by Luus for the neural networks taught by Bohwmick in providing in-app guidance to provide a predictable result of generating more relevant, coherent, and personalized content for a user (Luus, Paragraphs 0029 and 0031).
With respect to Claim 2, Bohwmick further discloses:
The terminal according to claim 1, wherein the at least one processor is further configured to execute the set of instructions to generate the prompt using a most recent operation content of the selected application (the in-app history provided as part of the prompt/request to the model is based on time recency of user event operations, Paragraph 0054).
With respect to Claim 4, Luus further discloses:
The terminal according to claim 1, wherein the at least one processor is further configured to execute the set of instructions to calculates a usage frequency of the selected application based on the operation history of the selected application, and generate the prompt using the calculated usage frequency (request provided to AI model/LLM includes calculated "application frequency of use," Paragraphs 0018, 0029, 0038, and 0043, for use in generating more relevant, coherent, and personalized content for a user).
With respect to Claim 5, Bohwmick further discloses:
The terminal according to claim 1, wherein the at least one processor is further configured to execute the set of instructions to generate the prompt using the operation history of the selected application and the operation history of an application different from the selected application (the model receives in-app events from the user and in-app events from a different application (e.g., a different user’s application), Paragraphs 0028, 0045, and 0055).
With respect to Claim 6, Luus further discloses:
The terminal according to claim 1, wherein the at least one processor is further configured to execute the set of instructions to generate the prompt using attribute information of the user (prompting including user profile attributes such as metrics- usage frequency of the application, subscription level, use of functions, purpose, etc., Paragraphs 0022, 0038, and 0045, for use in generating more relevant, coherent, and personalized content for a user).
Claims 7 and 9-10 recite subject matter similar to Claim 6, and thus, are rejected under similar rationale.
With respect to Claim 11, Bhowmick and Luus further disclose:
The terminal according to claim 6, wherein the at least one processor is further configured to execute the set of instructions to acquire the explanatory text related to the method of using the selected application by transmitting the generated prompt to a server apparatus in which the language model is implemented (neural network model-based response is received by communicating a request to a server over a network via a user device, Paragraphs 0022, 0025, 0031, and 0033-0034 and see the sending of a request depicted in Fig. 3; note that Luus teaches that the model is in the form of an LLM as applied to claim 1 where it is further disclosed that the LLM can be implemented at a server, Paragraphs 0017 and 0039).
With respect to Claim 12, Bhowmick and Luus further disclose:
The terminal according to claim 6, wherein the at least one processor is further configured to execute the set of instructions to acquire the explanatory text related to the method of using the selected application by inputting the generated prompt into the language model internally implemented (neural network model-based response is generated using a locally integrated help system, Paragraphs 0032-0034 and see the sending of a request depicted in Fig. 3; note that Luus teaches that the model is in the form of an LLM as applied to claim 1 where it is further disclosed that the LLM can be implemented as a single device, Paragraphs 0017 and 0082).
Claim 13 is directed towards a method embodiment of the invention carrying out the process corresponding to the functionality of system claim 1, and thus, is rejected under similar rationale.
Claim 14 is directed towards a method embodiment of the invention in the form of a non-transitory computer-readable storing medium storing a program for carrying out the process corresponding to the functionality of system claim 1, and thus, is rejected under similar rationale. Moreover, Bhowmick teaches system functionality implemented as a program stored on a non-transitory computer-readable storage medium (non-transitory computer-readable media such as a memory storing instructions, Paragraphs 0024, 0028, and 0073).
Claims 3 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Bhowmick, et al. in view of Luus, et al. and further in view of Vadapalli, et al. (U.S. PG Publication: 2022/0300984 A1).
With respect to Claim 3, Bohwmick in view of Luus teaches the application help process based upon in-app operation history using LLM prompting as applied to Claim 1. While Luus further teaches the consideration of application usage metrics as a way of determining a user skill level in prompting a guidance request (Paragraphs 0022 and 0038), Bohwmick in view of Luus does not teach a usage metric in the form of a calculated cumulative usage time. Vadapalli, however, discloses the level of experience for an application is based upon total tracked "time spent...with the application" in order to tailor support instructions (Paragraph 0016, 0021, 0024, and 0030).
Bohwmick, Luus, and Vadapalli are analogous art because they are from a similar field of endeavor in software application guidance using machine learning models. Thus, it would have been obvious to one of ordinary skill before the effective filing date to further consider the experience metric of tracked application usage time taught by Vadapalli as another experience metric for providing the guidance taught by Bohwmick in view of Luus to provide a predictable result of a useful metric that can be used to categorize user experience/skill in generating guidance that matches a user skill (Vadapalli, Paragraph 0030).
Claim 8 recites subject matter similar to Claim 6, and thus, is rejected under similar rationale.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Vu, et al. ("GPTVoiceTasker: LLM-Powered Virtual Assistant for Smartphone," January 2024)- teaches using a user help task along with application state information including UI elements as a prompt to an LLM (see Fig. 2).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAMES S WOZNIAK whose telephone number is (571)272-7632. The examiner can normally be reached 7-3, off alternate Fridays.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Andrew Flanders can be reached at (571)272-7516. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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JAMES S. WOZNIAK
Primary Examiner
Art Unit 2655
/JAMES S WOZNIAK/Primary Examiner, Art Unit 2655
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