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 .
Status of Claims
This action is in reply to the application filed on 08/11/2025.
Claims 1-20 are currently pending and have been examined.
Abstract
Need to object to Abstract for being worded like a claim.
Claim Rejections – 35 § 112(b)
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 1-20 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 1 recites “comparing a description of an issue to a plurality of documents to generate similarity scores for the plurality of documents”. It is unclear how similarity scores are generated based on comparing a description of an issue to a plurality of documents? Are the similarity scores generated based on a formula or an algorithm? Claim 11 recites similar limitations. Claims 1 and 11 are therefore found to be indefinite, because the resulting claims does not clearly set forth the metes and bounds of the patent protection desired. All dependent claims, namely claims 2-10 and 12-20, are rejected for at least the same reason.
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 an abstract idea without significantly more.
Claims 1-20: Step 1
Claims 1-10 are drawn to a computer-implemented method for comparing a description of an issue to documents to generate similarity scores for the documents, which is within the four statutory categories (i.e. process). Claims 11-20 are drawn to a system for comparing a description of an issue to documents to generate similarity scores for the documents, which is within the four statutory categories (i.e. machine).
Claims 1-20: Step 2A Prong One
Claim 1 recites comparing a description of an issue to a plurality of documents to generate similarity scores for the plurality of documents, selecting a set of most-relevant documents from the plurality of documents based on the similarity scores, prompting a large language model (LLM) to generate a solution to the issue, and performing a corrective action based on the solution to correct the issue. Claim 11 recites similar limitations.
These limitations, as drafted, given the broadest reasonable interpretation, but for the recitation of generic computer components, encompass managing personal behavior by manually following rules or instructions, which is a subgrouping of Certain Methods of Organizing Human Activity. But for the recitation of generic computer components, these limitations encompass a user comparing a description of an issue to a plurality of documents to generate similarity scores for the plurality of documents, selecting a set of most-relevant documents from the plurality of documents based on the similarity scores, prompting a large language model (LLM) to generate a solution to the issue, and performing a corrective action based on the solution to correct the issue. These steps could be carried out manually by a user following rules or instructions, which is a subgrouping of Certain Methods of Organizing Human Activity. Claim 11 recites similar limitations.
Claims 2-10 and 12-20 incorporate the abstract idea identified above and recite additional limitations that expand on the abstract idea, but for the recitation of generic computer components. For example, but for the recitation of generic computer components, Claims 2, 9, 12 and 19 further define comparing the description of the issue to the plurality of documents. Claims 3 and 13 further define selecting the set of most relevant documents. Claims 4 and 14 further define the set of most-relevant documents. Claims 5-6 and 15-16 further define the issue description. Claims 7 and 17 further define the plurality of documents. Claims 8 and 18 further define the solution. Claims 10 and 20 further define the large language model. Therefore, these claims are similarly drawn to Certain Methods of Organizing Human Activity.
Claims 1-20: Step 2A Prong Two
This judicial exception is not integrated into a practical application because the remaining elements amount to no more than general purpose computer components programmed to perform the abstract ideas along with insignificant, extra-solution data gathering activity, and adding limitations similar to adding the words “apply it” to the abstract idea. Claim 1 recites the additional elements of a computer recited in the preamble of computer-implemented method to perform the abstract idea. Claim 11 recites a system comprising a processor and memory with computer program to perform the abstract idea.
Claims 1-20, directly or indirectly, recite the following generic computer components: “processor” and “computer program” which are similar to adding the words “apply it” to the abstract idea. The written description discloses that the recited computer components encompass generic components including “The processor 610 may be embodied as any type of processor capable of performing the functions described herein. The processor 610 may be embodied as a single processor, multiple processors, a Central Processing Unit(s) (CPU(s)), a Graphics Processing Unit(s) (GPU(s)), a single or multi-core processor(s), a digital signal processor(s), a microcontroller(s), or other processor(s) or processing/controlling circuit(s)“ (see at least Paragraph [0041]) and “The inventive system may also be considered to be embodied in a computer-readable storage medium, configured with a computer program, where the storage medium so configured causes a computer to operate in a specific and predefined manner to perform the functions described herein” (see at least Paragraph [0056]) . Although the additional element “large language model” limits the identified judicial exceptions, this type of limitation merely confines the use of the abstract idea to a particular technological environment, and thus fails to add an inventive concept to the claims. See MPEP 2106.05 (h). As set forth in the 2019 Eligibility Guidance, 84 Fed. Reg. at 55 “merely include[ing] instructions to implement an abstract idea on a computer” is an example of when an abstract idea has not been integrated into a practical application.
Claims 1-20: Step 2B
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because as discussed above with respect to integration into a practical application, the additional elements (for example, large language model) are recited at a high level of generality, and the written description indicates that these elements are generic computer components. Using generic computer components to perform abstract ideas does not provide a necessary inventive concept. See Alice, 573 U.S. at 223 (“mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention.”). As explained above, the generic computer components and machine learning are at best the equivalent of merely adding the words “apply it” to the judicial exception.
Receiving and transmitting data over a network (i.e. receiving and communicating data or signals) has been recognized as well-understood, routine, and conventional activity of a general-purpose computer (see MPEP 2106.05(d) and buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014)).
Gathering and analyzing information using conventional techniques and displaying the result has also been found to be insufficient to show an improvement to technology, (see MPEP 2106.05(a) and TLI Communications, 823 F.3d at 612-13, 118 USPQ2d at 1747-48).
Insignificant, extra solution, data gathering activity has been found to not amount to significantly more than an abstract idea (see MPEP 2106.05(g) and Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016)). Therefore, the high-level recitation of an output of results also fails to include additional elements that are sufficient to amount to significantly more than the judicial exception.
Therefore, whether considered alone or in combination, the additional elements do not amount to significantly more than the abstract idea.
Claim Rejections - 35 USC § 102
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 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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
(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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-2, 5-8, 10-12, 15-18 and 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Core, What is Rag?.
Claim 1:
Core discloses the following limitations as shown below:
comparing a description of an issue to a plurality of documents to generate similarity scores for the plurality of documents (see at least Pg 3, analyzes user questions (reads on “description of an issue”) to extract relevant keywords, and based on this, retrieves relevant information from external databases or knowledge bases. Techniques such as vector similarity are used to select the most relevant documents or information);
selecting a set of most-relevant documents from the plurality of documents based on the similarity scores (see at least Pg 2, search and integrate information in real time to generate more accurate and up-to-date answers; Pg 3, techniques such as vector similarity are used to select the most relevant documents or information);
prompting a large language model (LLM) to generate a solution to the issue (see at least Pg 3-4, the retrieved information is added to the LLM’s input. Based on the augmented input, the LLM generates the final response. At this stage, the LLM combines the retrieved information with its self-trained knowledge to generate more accurate and contextually relevant responses (reads on “solution to the issue”); and
performing a corrective action based on the solution to correct the issue (see at least Pg 7-8, considering inputting a patient’s symptoms and records and suggesting recommended tests and treatment options).
Claim 11 recites substantially similar system claim to those of method claim 1 and, as such, is rejected for similar reasons as given above.
Claim 2:
Core discloses the limitations as shown in the rejection above. Core further discloses the following limitations:
wherein comparing the description of the issue to the plurality of documents includes comparing vector representations of the description and the plurality of documents using a similarity metric to generate the similarity scores (see at least, Pg 3, analyzes user questions (reads on “description of an issue”) to extract relevant keywords, and based on this, retrieves relevant information from external databases or knowledge bases. Techniques such as vector similarity are used to select the most relevant documents or information).
Claim 12 recites substantially similar system claim to those of method claim 2 and, as such, is rejected for similar reasons as given above.
Claim 5:
Core discloses the limitations as shown in the rejection above. Core further discloses the following limitations:
wherein the issue description identifies a bug in a software project and wherein the corrective action includes patching a file in the software project to fix the bug (see at least Pg 5, RAG can easily integrate expertise in specific fields, making it convenient to apply across various domains).
Claim 15 recites substantially similar system claim to those of method claim 5 and, as such, is rejected for similar reasons as given above.
Claim 6:
Core discloses the limitations as shown in the rejection above. Core further discloses the following limitations:
wherein the issue description identifies a health condition of a patient and wherein the corrective action includes automatically administering a treatment to the patient to treat the health condition (see at least Pg 7, In the medical field, RAG can be utilized as a decision support system. By entering patient symptoms and medical records, the system searches the latest medical papers, clinical guidelines, and drug information databases. Based on this, we suggest possible diagnoses, recommended tests, and treatment options to help doctors establish more accurate diagnoses and optimal treatment plans).
Claim 16 recites substantially similar system claim to those of method claim 6 and, as such, is rejected for similar reasons as given above.
Claim 7:
Core discloses the limitations as shown in the rejection above. Core further discloses the following limitations:
wherein the plurality of documents include medical records of the patient (see at least Pg 5, RAG can easily integrate expertise in specific fields, making it convenient to apply across various domains. For example, in the medical field, the latest clinical research findings can be immediately reflected; Pg 7, In the medical field, RAG can be utilized as a decision support system. By entering patient symptoms and medical records, the system searches the latest medical papers, clinical guidelines, and drug information databases).
Claim 17 recites substantially similar system claim to those of method claim 7 and, as such, is rejected for similar reasons as given above.
Claim 8:
Core discloses the limitations as shown in the rejection above. Core further discloses the following limitations:
wherein the solution is used for medical decision making (see at least Pg 5, RAG can easily integrate expertise in specific fields, making it convenient to apply across various domains. For example, in the medical field, the latest clinical research findings can be immediately reflected, while in the legal field, recent case law can be reflected immediately; Pg 7, In the medical field, RAG ca be utilized as a decision support system. By entering patient symptoms and medical records, the system searches the latest medical papers, clinical guidelines, and drug information databases)(where the limitation following “is used for” is considered intended use, and therefore given little patentable weight).
Claim 18 recites substantially similar system claim to those of method claim 8 and, as such, is rejected for similar reasons as given above.
Claim 10:
Core discloses the limitations as shown in the rejection above. Core further discloses the following limitations:
wherein the large language model is a trained machine learning model that accepts the set of most-relevant documents as context to a prompt to generate the solution (see at least Pg 2, RAG technology was developed to overcome the limitations of traditional Large Language Models (LLMs); Pg 3, the emergence of RAG is significant in that AI can not only reproduce pre-trained information but also search and integrate information in real time to generate more accurate and up-to-date answers; Pg 5, RAG can leverage external databases or knowledge bases to reflect information updated in real time. This enables accurate information about fast-changing fields or the latest events; Pg 3-4, the retrieved information is added to the LLM’s input. Based on the augmented input, the LLM generates the final response. At this stage, the LLM combines the retrieved information with its self-trained knowledge to generate more accurate and contextually relevant responses (reads on “generate the solution”)).
Claim 20 recites substantially similar system claim to those of method claim 10 and, as such, is rejected for similar reasons as given above.
Claim Rejections - 35 USC § 103
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 of this title, if the differences between the claimed invention and the prior art axe 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 3-4 and 13-14 are rejected under 35 U.S.C. 103 as being unpatentable over Core, What is RAG? in view of Choi et al., KR Patent KR 102624653 B1.
Claim 3:
Core discloses the limitations as shown in the rejection above. Core may not specifically disclose the following limitations, but Choi as shown does:
wherein selecting the set of most-relevant documents includes selecting a number of documents in accordance with a limitation of the LLM (see at least Claim 8, considering that If the number of tokens included in the conversation data is greater than or equal to a threshold number, the conversation data is provided to a conversation classifier, conversations related to a user’s psychology classified by the conversation classifier are provided as the conversation data to a prompt processor, and if the number of tokens included in the conversation data is less than the threshold number, all conversations included in the conversation data are provided as conversation data to the prompt processor).
At the time of the filing of the application it would have been obvious to one of ordinary skill in the art to combine the teaching of the retrieval augmented generation of Core with the feature of Choi with the motivation of providing the benefit and convenience that “… allow users to conveniently determine their psychological state at any time without being restricted by location through the user's terminal” (Choi, see at least Background).
Claim 13 recites substantially similar system claim to those of method claim 3 and, as such, is rejected for similar reasons as given above.
Claim 4:
The combination of Core/Choi discloses the limitations as shown in the rejection above. Core may not specifically disclose the following limitations, but Choi as shown does:
wherein the set of most-relevant documents includes a maximum number of documents having highest similarity scores of the plurality of documents without exceeding a token limit of the LLM (see at least Claim 8, considering that If the number of tokens included in the conversation data is greater than or equal to a threshold number, the conversation data is provided to a conversation classifier, conversations related to a user’s psychology classified by the conversation classifier are provided as the conversation data to a prompt processor, and if the number of tokens included in the conversation data is less than the threshold number, all conversations included in the conversation data are provided as conversation data to the prompt processor).
At the time of the filing of the application it would have been obvious to one of ordinary skill in the art to combine the teaching of the retrieval augmented generation of Core with the feature of Choi for at least the same reasons as given for claim 3.
Claim 14 recites substantially similar system claim to those of method claim 4 and, as such, is rejected for similar reasons as given above.
Claims 9 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Core, What is RAG? in view of Qu et al., Tool Learning With Large Language Models.
Claim 9:
Core discloses the limitations as shown in the rejection above. Core may not specifically disclose the following limitations, but Qu as shown does:
wherein comparing the description of the issue to the plurality of documents includes computing a TF-IDF (term frequency, inverse document frequency) for the plurality of documents (see at least Page 10, considering that Term-based methods (i.e. sparse retrieval, such as TD-IDF (Sparck Jones, 1972) and BM25 (Robertson et al., 2009), represent both documents and queries as high-dimensional sparse vectors).
At the time of the filing of the application it would have been obvious to one of ordinary skill in the art to combine the teaching of the retrieval augmented generation of Core with the feature of Qu with the motivation that “… the integration significantly improves their response accuracy to user queries, facilitating more effective and reliable user interactions (Qu, see at least Page 2).
Claim 19 recites substantially similar system claim to those of method claim 9 and, as such, is rejected for similar reasons as given above.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Joy Chng whose telephone number is 571.270.7897. The examiner can normally be reached on Monday-Friday, 9:00am-5:00pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, JASON DUNHAM can be reached on 571.272.8109. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Joy Chng/
Primary Examiner, Art Unit 3686
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