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 .
Response to Amendment
This communication is responsive to the applicant’s amendment dated 07/08/2026. The applicant(s) amended claims 21, 24, 31, and 34.
Response to Arguments
Applicant's arguments with respect to claims 21 and 31 have been considered but are moot in view of the new ground(s) of rejection because the arguments pertain to the newly amended limitations.
Regarding the Double Patenting Rejection, the Examiner maintains the rejection because the “digital information” in combination with the other claim limitations is not enough to be considered patentably distinct from the US Patent. Both sets of claims are directed to using a large language model that has exclusive access to a database in order to provide answers to a user input.
Claim Rejections - 35 USC § 103
Claim(s) 21-24, 26, 30-34, 36, and 40 are rejected under 35 U.S.C. 103 as being unpatentable over Barber et al. (US 20250335483 A1) in view of Mui et al. (US 20240412000 A1).
Regarding claims 21 and 31, Barber teaches:
“at least one memory storing instructions” (par. 0044; ‘The processing device 32, such as a central processing unit (CPU), executes instructions stored in memory 34 to carry out computational tasks and to manage the operation of the computer system 30.’);
“at least one processor configured to execute instructions to perform operations for providing answer data using external language models” (par. 0042; ‘Next, the server 16 is configured to provide the relevant documentation context (obtained from the vector store 20), along with the original user query to an LLM 22.’ The LLM 22 is external.; par. 0044; CPU;), the operations comprising:
“receiving, through a program [[on a first device, the program]] having access to a first limited private dataset but not a second limited private dataset [[that is distinct from the first limited private dataset]], an input from the first user device” (par. 0048; ‘Furthermore, the computing system 50 includes a query searching program 64 configured to perform search functions based on a query received from a corresponding user devices (e.g., user device 14). Also, the computing system 50 includes a section-based chunking program 66 configured to retrieve relevant information (e.g., using RAG methods) from a vector database (e.g., vector store 20) when a search query involves specific reference to private information that is not normally publicly available.’);
“transmitting, to an external language model, the input and digital information derived using the first limited private dataset, wherein the external language model has access to the second limited private dataset but not the first limited private dataset” (par. 0082; ‘In response to receiving a user query directed to subject information retrievable from documentation stored in a private database, the process 100 includes the step of using a section-based chunking procedure to obtain, from the private database, a relevant section of the documentation as context, as indicated in block 102. The process 100 further includes a step of feeding the user query and the relevant section as context to a Large Language Model (LLM), as indicated in block 104.’);
“receiving, from the external language model, answer data after transmitting the input and the digital information” (par. 0042; ‘It should be noted that by using a section-based retrieval or chunking process, the appropriate section of the private information can lead the LLM 22 to create an answer that is relevant with respect to the query and that includes no hallucinations.’);
“generating response data based on the answer data received from the external language model” (par. 0042; ‘It should be noted that by using a section-based retrieval or chunking process, the appropriate section of the private information can lead the LLM 22 to create an answer that is relevant with respect to the query and that includes no hallucinations.’) and
“outputting the response data at the first user device” (par. 0042; ‘The server 16 can then forward the answer to the user device 14.’).
However, Barber does not expressly teach a second limited private dataset that is distinct from the first limited private dataset, as in:
“receiving, through a program [[on a first device, the program]] having access to a first limited private dataset but not a second limited private dataset [[that is distinct from the first limited private dataset]], an input from the first user device.”
Mui teaches:
“receiving, through a program on a first device, the program having access to a first limited private dataset but not a second limited private dataset that is distinct from the first limited private dataset, an input from the first user device” (par. 0048; ‘In some examples, the system may transmit an input to an LLM (e.g., a publicly-accessible LLM, a locally-hosted LLM, a private LLM, or other LLM). The system may transmit the input to the LLM, among other reasons, to obtain natural language output to present the response to the user input.’ ‘In some examples, this LLM may be a publicly accessible LLM, a public LLM that has access restrictions (e.g., based on a token, key, password, or other tenant access control measure), or a private LLM (e.g., a self-hosted LLM, an LLM that is hosted in a private cloud platform, or a private LLM that is hosted on public servers).’) The private LLM reads on a second limited private dataset that is distinct from the first limited private dataset.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Barber’s LLM 22 by incorporating Mui’s private LLM such that the LLM has access to a second limited private dataset that is distinct from the first limited private dataset. The combination provides improved interpretation of natural language input and assignments of processing tools to perform tasks included in the natural language input. (Mui: par. 0035)
Regarding claims 22 (dep. on claim 21) and 32 (dep. on claim 31), the combination of Barber in view of Mui further teaches:
“wherein the external language model is configured to output answer data interpretable by the program” (Barber: par. 0042; ‘It should be noted that by using a section-based retrieval or chunking process, the appropriate section of the private information can lead the LLM 22 to create an answer that is relevant with respect to the query and that includes no hallucinations.’).
Regarding claims 23 (dep. on claim 21) and 33 (dep. on claim 31), the combination of Barber in view of Mui further teaches:
“wherein a graphical user interface facilitates an interaction between a first user and the program” (Barber: par. 0069; ‘A user may enter a query on a Graphical User Interface (GUI) or other input component of the user device 14.’).
Regarding claims 24 (dep. on claim 21) and 34 (dep. on claim 31), the combination of Barber in view of Mui further teaches:
“wherein the first limited private dataset is accessible by the first user device” (Barber: par. 0048; ‘Furthermore, the computing system 50 includes a query searching program 64 configured to perform search functions based on a query received from a corresponding user devices (e.g., user device 14). Also, the computing system 50 includes a section-based chunking program 66 configured to retrieve relevant information (e.g., using RAG methods) from a vector database (e.g., vector store 20) when a search query involves specific reference to private information that is not normally publicly available.’; par. 0079; ‘The Inference procedure, for example, may be performed each time the user enters a query about the private documentation stored in the vector store 20.’).
Regarding claims 26 (dep. on claim 21) and 36 (dep. on claim 31), the combination of Barber in view of Mui further teaches:
“the input is associated with a content type comprising at least one of an academic subject, health, technology, or course registration” (Barber: par. 0069; ‘In this example, the user enters the query “How do I make banana bread?” The server 16 and/or retriever 18 may recognize this query as a request for a recipe and may create a system message for the LLM 22 reading, “You are a helpful AI cook that summarizes recipes for users based on their queries. You will be given a recipe as context.’ Inquiring about a recipe pertains to health.); and
“the second limited private dataset, accessible by the external language model but not the program, includes data associated with the content type” (par. 0069; ‘It should be noted that, based on the retrieval strategy implemented in this example, the LLM 22 may come up with a number of different responses.’ See also par. 0074).
Regarding claims 30 (dep. on claim 21) and 40 (dep. on claim 31), Barber teach an external language model as well as wireless communications (par. 0043; ‘The computer system 30 includes a processing device 32, memory 34, Input/Output (I/O) devices 36, a network interface 38, a data storage device 40, and a wireless communications device 41 (e.g., radio system, cellular communications system, Wi-Fi communications system, Bluetooth system, etc.).’) but does not expressly teach not having access to the internet, as in:
“wherein the external language model does not have access to the internet.”
Mui teaches using a network protocol different from the internet (par. 0024; ‘The network may implement transfer control protocol and internet protocol (TCP/IP), such as the Internet, or may implement other network protocols.’).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Barber’s external language model and wireless communications by implement another network protocol different from the internet as taught by Mui such that the external language model communicates while not having access to the internet/offline. The combination improves the usability of LLMs in a wide range of use cases that require a high level of confidence in the response that an LLM provides. (Mui: par. 0022)
Claim(s) 25, 27-29, 35, and 37-39 are rejected under 35 U.S.C. 103 as being unpatentable over Barber in view of Mui, further in view of Lee et al. (US 20250140245 A1).
Regarding claims 25 (dep. on claim 21) and 35 (dep. on claim 31), Barber and Mui do not expressly teach:
“the input comprises a verbal query;” and
“the operations further comprise translating the verbal query into a text representation using speech recognition.”
Lee teaches:
“the input comprises a verbal query” (par. 0100; ‘In some examples, the user may use speech input to the client software 336, which may employ automatic speech recognition to generate a textual representation of the speech, which may then be provided as a prompt to the personalized LLM.’) and
“the operations further comprise translating the verbal query into a text representation using speech recognition” (par. 0100; automatic speech recognition).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Barber’s (in view of Mui) query processing by incorporating Lee’s client software in order to process speech input queries. The combination would allow a user to provide a textual representation of speech as a prompt to a personalized large language model. (Lee: par. 0100)
Regarding claims 27 (dep. on claim 21) and 37 (dep. on claim 31), Barber and Mui teach an external language model.
However, Barber and Mui do not expressly teach:
“wherein the external language model is accessible by a second user device.”
Lee teaches:
“wherein the external language model is accessible by a second user device” (par. 0081; ‘Such a reduced LLM 342 may then be provided to one or more client devices 330 to be used locally.’).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Barber’s (in view of Mui) external language model by incorporating Lee’s method of providing a large language model to multiple client devices such that the external language model is accessible by a second user device. The combination allows a user to create a personalized large language model. (Lee: par. 0082)
Regarding claims 28 (dep. on claim 27) and 38 (dep. on claim 37), the combination of Barber in view of Mui and Lee further teaches:
“the first user device has a first set of privileges and the second user device has a second set of privileges” (Lee: par. 0069; ‘For example, the user could keep their personal LLM on a personal laptop or smartphone, or could keep it installed on their own private server in at a cloud provider. They could then use various access controls to ensure that they have control over who is able to use that personal LLM.’); and
“the second set of privileges corresponds to a security level of the external language model” (Lee: par. 0069; ‘For example, the user could keep their personal LLM on a personal laptop or smartphone, or could keep it installed on their own private server in at a cloud provider. They could then use various access controls to ensure that they have control over who is able to use that personal LLM.’).
Regarding claims 29 (dep. on claim 28) and 39 (dep. on claim 38), the combination of Barber in view of Mui and Lee further teaches:
“wherein the external language model is configured to receive an input from the second user device” (Lee: par. 0081; ‘Such a reduced LLM 342 may then be provided to one or more client devices 330 to be used locally.’).
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 21, 23, 27, 30, 31, 33, 37, and 40 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 3, 12, 14, 15, 17, and 18 of US 12265788 B1. Although the claims at issue are not identical, they are not patentably distinct from each other because removing inherent and/or unnecessary limitations/step and rearranging the claims would be within the level of one of ordinary skill in the art. It is well settled that the omission of an element, e.g. identifying an external large language model from among a plurality of external large language models by using at least one keyword in the input to determine that the second limited private dataset associated with the external large language model contains answer data associated with the input, etc. (see claim 1 of US Patent application) and its function is an obvious expedient if the remaining elements perform the same function as before. In re Karlson, 136 USPQ 184 (CCPA 1963). Also note Ex parte Rainu, 168 USPQ 375 (Bd. App. 1969). Omission of a reference element or step whose function is not needed would be obvious to one of ordinary skill in the art.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARK VILLENA whose telephone number is (571)270-3191. The examiner can normally be reached 10 am - 6pm EST Monday through Friday.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Richemond Dorvil can be reached at (571) 272-7602. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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MARK . VILLENA
Examiner
Art Unit 2658
/MARK VILLENA/Examiner, Art Unit 2658
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