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 .
This action is responsive to the Amendment filed on 7/8/2026.
Claims 1-7 and 9-20 are pending in the case. Claim(s) 8 has/have been cancelled.
Response to Arguments
Applicant's arguments and amendments with regards to the 35 U.S.C. § 101 rejection of claim(s) 1-20 have been fully considered and are are persuasive. The 35 U.S.C. § 101 rejection of claim(s) 1-20 is respectfully withdrawn.
Applicant’s arguments and amendments with regards to the 35 U.S.C. § 112(b) rejection of claim(s) 12-19 have been fully considered and are persuasive. Therefore, the 35 U.S.C. § 112(b) rejection of claim(s) 12-19 is respectfully withdrawn.
Applicant's arguments and amendments with regards to the 35 U.S.C. § 102 and 103 rejection of claim(s) 1-7 and 9-20 have been considered, but are not persuasive. Applicant argues that the amended claims are allowable due to the following:
Regarding claim(s) 1, applicant argues “Specifically, Spiegel at paragraphs [0107] and [0108] states, respectively:
...the LLM 338 is continuously retrained using information about advertising content 358 stored in the advertising and campaigns database 346. For example, the LLM 338 is trained on the latest products being offered by advertisers on the interaction system 100 and offers product information on those products in response to requests by a user for the newest model of particular product categories…. the LLM 338 is continuously retrained or finetuned based on user interactions with the advertising content 358. For example, the interaction system 100 collects advertising content engagement metrics and stores the metrics in the advertisement analytics database 344. The metrics are then used to provide reinforcement to the LLM 338 when the LLM 338 provides a sequence of responses that lead to a successful user intent determination and consequently properly targeted advertising content 358 that the user interacted with.
However, and as discussed during the interview, Spiegel does not disclose or suggest re-training "based upon one or more differences between (i) the stylistic scheme and an updated stylistic scheme determined from a subsequent user query or (ii) the contextual scheme and an updated contextual scheme determined from the subsequent user query," as recited in claim 1. Spiegel's re-training is driven by external advertising signals, specifically, advertising content from an advertising database and advertising engagement metrics from user interactions with advertising content. See id. This is not the same as the above-recited elements of claim 1, which re-train the ML chatbot based upon detected differences between stylistic and contextual schemes determined from internal user queries. The remainder of Spiegel is also silent as to re-training based upon differences between stylistic or contextual schemes and is further silent as to retaining one or more stylistic or contextual characteristics of the user through the re-training process”.
Examiner respectfully disagrees.
Spiegel [94, 107, 108, 185, 186, 196, 211, 254] discloses model may be retrained based in differences between determined response and updated response, differences could be in style information, and
Spiegel Abstract [30] discloses continuous retraining improves modeling accuracy, ad content is used in chatbot replies.
Therefore, while Spiegel discloses using ad content, the re-training in Spiegel is based on chatbot interaction, user queries and chatbot responses, and therefore
Spiegel sufficiently teaches re-training, by the one or more processors, the ML chatbot based upon one or more differences between (i) the stylistic scheme and an updated stylistic scheme determined from a subsequent user query …
Regarding claim(s) 2-7 and 9-20 applicant argues that the claims are allowable for reasons similar to those references with regards to claim 1.
For reasons similar to those discussed above with regards to claim 1 examiner asserts that the previously cited art sufficiently teaches the amended claims 2-7 and 9-20.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-7 and 9-20 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claims 1, 12 and 20, each recite “wherein the updated stylistic scheme retains one or more stylistic characteristics of the user determined from the user query, and the updated contextual scheme retains one or more contextual characteristics of the user determined from the user query”.
The original specification teaches adapting one or more stylistic characteristics of the user determined from the user query or adapting one or more contextual characteristics of the user determined from the user query,
rather than retaining one or more stylistic characteristics of the user determined from the user query or retaining one or more contextual characteristics of the user determined from the user query,
and therefore does not teach “wherein the updated stylistic scheme retains one or more stylistic characteristics of the user determined from the user query, and the updated contextual scheme retains one or more contextual characteristics of the user determined from the user query”.
Therefore the above noted limitations of claims 1, 12 and 20 do not have support in the original specification.
Claims 2-11, 13-19 merely recite additional functions performed by the inventions of claims 1 and 12 Accordingly, claims 2-11, 13-19 are also rejected under 35 U.S.C. 112(a).
Applicant is requested to make appropriate amendments to the claims or clearly point of the specific portions of paragraphs in the specification that support the claim limitations.
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 1-7, 9-20 are rejected under 35 U.S.C. 103 as being unpatentable over Baeuml (US 20230074406 A1), in view of Spiegel (US 20240249318 A1).
Regarding claim 1, Baeuml teaches a computer-implemented method for generating dynamic responses in a communication system, the computer-implemented method comprising (Baeuml [ Abstract, 5, 136] method implemented as processor executing instructions stored on medium, to provide responses in response to queries):
receiving, at one or more processors, a user query from a user (Baeuml [5, 20, 43] query is received from user);
determining, by the one or more processors executing a machine learning (ML) chatbot, a stylistic scheme and a contextual scheme for a response to the user query, wherein the ML chatbot is trained ... (Baeuml [63, 64] style parameters (scheme) are determined, Baeuml [47, 79, 87] context based parameters (scheme) are determined, Baeuml [1, 5, 89] parameters used for assistant (chatbot) response using model(s), response is for user query, Baeuml [66] chatbot model is trained (implied since it is retrained));
generating, by the one or more processors executing the ML chatbot, the response to the user query that is articulated in accordance with the stylistic scheme and the contextual scheme (Baeuml [14, 15, 63, 64, 73] responses are generated and then output is generated based on responses, output is based on determined parameters);
causing, by the one or more processors, the response to be conveyed to the user (Baeuml [73] generated output is rendered (conveyed) to user).
…generating…, by the one or more processors … updated stylistic scheme …that…retains one or more stylistic characteristics of the user determined from the user query, and … updated contextual scheme …that…retains one or more contextual characteristics of the user determined from the user query (Baeuml [11, 16, 19, 101, 105, 120, 122] model determines changes in conversation context and/or style and updates context and style (personality) parameters based on change, updates may combine multiple context and style (including previous and current));and
generating, by the one or more processors executing the re-trained ML chatbot, a subsequent response that is articulated in accordance with the updated stylistic scheme or the updated contextual scheme (Baeuml [358, 105, 120-122] responses to additional query are based on updated context and style parameters and can be using re-trained chatbot).
Baeuml does not specifically teach wherein the ML chatbot is trained with a plurality of training user queries as inputs to generate a plurality of training responses as outputs; re-training, by the one or more processors, the ML chatbot based upon one or more differences between (i) the stylistic scheme and an updated stylistic scheme determined from a subsequent user query or (ii) the contextual scheme and an updated contextual scheme determined from the subsequent user query.
However Spiegel teaches wherein the ML chatbot is trained with a plurality of training user queries as inputs to generate a plurality of training responses as outputs (Spiegel [200, 203, 210, 215-218, 222] model is trained using conversations (including user queries) and provides answers, Spiegel [199, 92, 94] model provides answers based on conversation style and context);
re-training, by the one or more processors, the ML chatbot based upon one or more differences between (i) the stylistic scheme and an updated stylistic scheme determined from a subsequent user query … (Spiegel [94, 107, 108, 185, 186, 196, 211, 254] model may be retrained based in differences between determined response and updated response, differences could be in style information, Spiegel Abstract [30] continuous retraining improves modeling accuracy, ad content is used in chatbot replies).
It would have been obvious to one of an ordinary skill in the art before the effective filing date of the claimed invention, to have incorporated the concept taught by Spiegel of wherein the ML chatbot is trained with a plurality of training user queries as inputs to generate a plurality of training responses as outputs; re-training, by the one or more processors, the ML chatbot based upon one or more differences between (i) the stylistic scheme and an updated stylistic scheme determined from a subsequent user query …, into the invention suggested by Baeuml; since both inventions are directed towards assistants providing answers based on conversation style and context, and incorporating the teaching of Spiegel into the invention suggested by Baeuml would provide the added advantage of leveraging user input by using existing conversation history to train the model and improve modeling accuracy , and the combination would perform with a reasonable expectation of success (Spiegel [200, 203, 210, 215-218, 222, 199, 92, 94).
Regarding claim 2, Baeuml and Spiegel teach the invention as claimed in claim 1 above. Baeuml further teaches wherein the user query and the response include at least one of: (i) a verbal communication or (ii) a textual communication... (Baeuml [20, 51] user query and response may be verbal or text).
Regarding claim 3, Baeuml and Spiegel teach the invention as claimed in claim 2 above. Baeuml further teaches wherein, responsive to receiving a first verbal communication ...comprising the user query, the computer-implemented method further comprises (Baeuml [5, 20, 43] query is received from user, Baeuml [20, 51] user query and response may be verbal or text, steps performed to provide response to user):
converting, by the one or more processors, the user query to a first text string (Baeuml [43, 76] speech to text conversion may be performed for user query);
determining, by the one or more processors executing the ML chatbot, the stylistic scheme and the contextual scheme for the response to the user query based upon the first text string (Baeuml [1, 5, 63, 64, 47, 79, 87] style and context based parameters (scheme) for assistant (chatbot) response using model(s), response is for user query, Baeuml [ 89, 100] analysis may be for text representation of user query);
generating, by the one or more processors executing the ML chatbot, the response to the user query as a second text string (Baeuml [89, 122] query response may be formulated as text);
converting, by the one or more processors, the second text string to a second verbal communication (Baeuml [51, 122] text response may be converted to synthesized speech); and
causing, by the one or more processors, the second verbal communication ... to be conveyed to the user (Baeuml [51, 122] synthesizes speech may be audibly rendered to user).
Regarding claim 4, Baeuml and Spiegel teach the invention as claimed in claim 1 above. Baeuml further teaches predicting, by the one or more processors executing the ML chatbot, a conversation style of the user based upon one or more stylistic characteristics of the user query; and determining, by the one or more processors executing the ML chatbot, the stylistic scheme for the response based upon the conversation style of the user (Baeuml [11, 15, 16] user speaking style may be predicted using prior conversations, parameters (scheme) for response personality may be based on the speaking style).
Regarding claim 5, Baeuml and Spiegel teach the invention as claimed in claim 1 above. Baeuml does not specifically teach predicting, by the one or more processors executing the ML chatbot, a conversational context and a conversational tone of the user based upon one or more contextual characteristics of the user query; and determining, by the one or more processors executing the ML chatbot, the contextual scheme for the response based upon the conversational context and the conversational tone of the user
However Spiegel teaches predicting, by the one or more processors executing the ML chatbot, a conversational context and a conversational tone of the user based upon one or more contextual characteristics of the user query; and determining, by the one or more processors executing the ML chatbot, the contextual scheme for the response based upon the conversational context and the conversational tone of the user (Spiegel [141, 144, 199, 92, 94] user speaking style and context may be predicted using conversation history, speaking style may include tone, response to user generating using personality incorporating the context and style).
Regarding claim 6, Baeuml and Spiegel teach the invention as claimed in claim 1 above. Baeuml further teaches wherein the response includes a set of information predicted to address at least a portion of the user query (Baeuml [11, 17] response may be an answer to a user question).
Regarding claim 7, Baeuml and Spiegel teach the invention as claimed in claim 7 above. Baeuml further teaches causing, by the one or more processors, the subsequent response to be conveyed to the user (Baeuml [105] response to additional query (based on updated context and style parameters) are rendered to user).
Regarding claim 9, Baeuml and Spiegel teach the invention as claimed in claim 1 above. Baeuml further teaches wherein determining the stylistic scheme and the contextual scheme further comprises: generating, by the one or more processors, one or more embeddings associated with the user query; comparing, by the one or more processors, the one or more embeddings to a library of embeddings (Baeuml [10] embeddings are generated from user query and compared with embeddings indexed in memory (library)) ; and
determining, by the one or more processors, the stylistic scheme and the contextual scheme based upon the comparing (Baeuml [63-65, 120] comparison yields information about context and style which is used to determine style and context parameters (scheme)).
Regarding claim 10, Baeuml and Spiegel teach the invention as claimed in claim 9 above. Baeuml further teaches wherein generating the response further comprises: retrieving, by the one or more processors, one or more prior responses from a response database based upon the one or more embeddings; and generating, by the one or more processors executing the ML chatbot, the response based upon the stylistic scheme, the contextual scheme, and the one or more prior responses (Baeuml [5, 16, 50] output response may be based on previous responses, Baeuml [14, 15, 63, 64, 73] output is based on determined parameters for style and context).
Regarding claim 11, Baeuml and Spiegel teach the invention as claimed in claim 1 above. Baeuml does not specifically teach wherein generating the response further comprises: inputting, by the one or more processors, a plurality of documentation corresponding to conversation topics into the ML chatbot; and generating, by the one or more processors executing the ML chatbot, the response based upon the user query and the plurality of documentation
However Spiegel teaches wherein generating the response further comprises: inputting, by the one or more processors, a plurality of documentation corresponding to conversation topics into the ML chatbot (Spiegel [181, 209, 217, 247, 256] information used by model may include text documents, documents may correspond to concepts and attributes (topics)); and
generating, by the one or more processors executing the ML chatbot, the response based upon the user query and the plurality of documentation (Spiegel [203, 217, 218] chatbot response may be based on user query and model (which is based on documentation)).
Claim 12 is directed towards a system executing instructions similar in scope to the instructions performed by the method of claim 1, and is rejected under the same rationale.
Baeuml further teaches system for generating dynamic responses in a communication system, comprising: one or more processors; and a non-transitory computer-readable memory coupled to the one or more processors and the user interface, the memory storing instructions thereon that, when executed by the one or more processors, cause the one or more processors
(Baeuml [Abstract, 5, 108, 136] method implemented as processor executing instructions stored on medium, to provide responses in response to queries, device includes user interface).
Claim(s) 13-16, 17-19 is/are dependent on claim 12 above, is/are directed towards a system executing instructions similar in scope to the instructions performed by the method of claim(s) 2-5, 8-10 respectively, and is/are rejected under the same rationale.
Claim 20 is directed towards a medium storing instructions similar in scope to the instructions performed by the method of claim 1, and is rejected under the same rationale.
Baeuml further teaches a tangible machine-readable medium comprising instructions for generating dynamic responses in a communication system that, when executed, cause a machine to (Baeuml [ Abstract, 5, 136] method implemented as processor executing instructions stored on medium, to provide responses in response to queries).
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 SANCHITA ROY whose telephone number is (571)272-5310. The examiner can normally be reached Monday-Friday 12-8.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Usmaan Saeed can be reached at (571) 272-4046. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
SANCHITA ROY
Primary Examiner
Art Unit 2146
/SANCHITA ROY/Primary Examiner, Art Unit 2146
