DETAILED ACTION
This Office Action is in response to the Application 18/808,807 filed on 08/19/2024.
In the instant application, claim 1 is the only independent claim; Claims 1-14 have been examined and are pending. This action is made non-final.
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 .
Drawings
The drawings submitted on 12/14/2012 are acceptable.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 11/13/2024 was filed before the mailing date of the first office action on the merits. The submissions are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
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.
Claim 3 is 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 pre-AIA the applicant regards as the invention.
Regarding 3, this claim recites the limitation "wherein step (b) includes displaying a visual direction for the subject" in line 2 of the claim. There is insufficient antecedent basis for this limitation in the claim. Appropriate action is required.
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 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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
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 at the time any inventions covered therein were effectively filed 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 at the time a later invention was effectively filed 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 and 7-13 are rejected under 35 U.S.C. 103 as being unpatentable over Dressler, II (“Dressler,” US 2024/0403567), Provisional application 63/506/298, filed on June 5, 2023 in view of OHRN (“Ohrn,” US 2024/0403568), filed on June 2, 2023.
Regarding claim 1, Dressler teaches a method, the method comprising the steps of:
(a) establishing a telecommunication connection with a remote device (Dressler: ¶0033 and Fig. 1; a user interacts with the chatbot service 142 at the application platform 124 to initiate a communication session with the LLM chat bot 152 and/or third party system 150);
[b) generating a prompt to a user of the remote device];
c) receiving data from the user [in response to the generated prompt] (Dressler: ¶0033 and Fig. 1; a user inputs or otherwise provides a conversational user input to the chatbot service 142);
(d) supplementing the data from the user with information from a user database (Dressler: ¶0033 and Fig. 1; a contextual personalization component of the chatbot service 142 utilizes the received conversational user input along with one or more identifiers associated with the user to access the database 106 to retrieve or otherwise obtain one or more models or digital representations associated with the user to identify additional contextual data from the database 106 that is related to the received conversational user input to be provided to the LLM chatbot 152 and/or third party system 150. The contextual personalization component of the chatbot service 142 augments the received conversational user input with the additional contextual data to provide an input prompt that is grounded in a personalized or customized manner. In this regard, the chatbot service 142 automatically generates a personalized or customized augmented conversation input prompt that includes, incorporates or otherwise reflects the additional relevant contextual data identified by the contextual personalization component that is specific to the particular individual user providing the initial conversation user input along with the content of the initial conversational user input), [the information from the user database including one or more selected from the group consisting of: age, geographical location, medical conditions, audio-processing conditions, visual-processing conditions, cognitive decline, and personal interests];
(e) providing the supplemented data to a large language model (LLM) (Dressler: ¶0034; the LLM chatbot 152 automatically parses or analyzes the contextual data as part of the augmented conversational user input prompt in concert with generating a conversational response to the semantic and/or syntactic content of the initial conversational user input using the pretrained GPTs, LLMs, or other algorithms or configurations associated with the LLM chatbot 152 and/or third party system 150. As the result, the autogenerated conversational response to the received conversational user input is customized or personalized to reflect the individual user providing the initial conversational user input based on that user’s individual personalization model or other contextual data provided by the contextual personalization service at the database system 102 based on that individual’s data maintained in the database 106);
(f) determining a desired response to the provided data based at least in part on the large language model (LLM) (Dressler: ¶0034; the autogenerated conversational response to the received conversational user input is customized or personalized to reflect the individual user providing the initial conversation user input based on that user’s individual personalization model or other contextual data provided by the contextual personalization service at the database system 102 based on that individual user’s data maintained in the database 106); and
(g) transmitting the desired response to the user (Dressler: ¶0035 and 0048; chatbot service receives the customized autogenerated conversational response from the LLM chatbot 152 and transmits to the user).
Dressler does not appear to teach: b) generating a prompt to a user of the remote device; c) receiving data from the user in response to the generated prompt; and the information from the user database including one or more selected from the group consisting of: age, geographical location, medical conditions, audio-processing conditions, visual-processing conditions, cognitive decline, and personal interests.
However Ohrn teaches a method of providing context-aware authoring assistance. Ohrn further teaches: b) generating a prompt to a user of the remote device (Ohrn: ¶0047; Fig 4A depicts an example graphical user interface screen 400A of an application that provides an assistant for authoring context-aware content. As depicted, the assistant may begin the conversation by displaying a UI element 410 that asks how it can help the user); (c) receiving data from the user in response to the generated prompt (Ohrn: ¶0047 and Fig. 4A; the user can utilize a UI element 412 to enter a user query. In the example depicted in screen 400A, the user submits a request to the assistant to draft an email from the user to Jennifer Smith about going over this month’s budget); and the information from the user database including one or more selected from the group consisting of: age, geographical location, medical conditions, audio-processing conditions, visual-processing conditions, cognitive decline, and personal interests (Ohrn: ¶0023; the authoring assistance system 110 receives or intercepts a user request from the application 120 and/or local application 164 and performs preprocessing on the user request to generate a prompt that is personalized for the requesting user and/or context of the request. To achieve this, the authoring assistance system 110 may utilize one or more trained ML models to retrieve or infer user history and/or behavioral data and/or data about the context. In some implementations, at least some user behavioral data, characteristics, and/or patterns are precomputed using trained ML models. For example, some user characteristics such as writing styles and preferences are inferred offline and stored in a data store such as a user profile data store. ¶0024; the authoring assistance system 110 utilizes a prompt generation engine to generate a prompt that is likely to result in a personalized responses from the language model 130).
Accordingly, it would have been obvious to one of ordinary skill in the art , before the effective filing date of the claimed invention, having the teachings of Ohrn and Dressler in front of them to include the method of providing context-awareness assistance as disclosed by Ohrn with the customized autogenerated conversational response as taught by Dressler to provide an improved systems and methods for generating a response to the user query that is customized to both the user and the context (Ohrn: ¶0002-0003).
Regarding claim 2, Dressler and Ohrn teach the method of claim 1,
Dressler and Ohrn also teach: the method further comprising: (h) training the LLM based at least in part on the received data from the user (Dressler: ¶0034; the LLM chatbot 152 automatically parses or analyzes the contextual data provided as part of the augmented conversational user input prompt in concert with generating a conversational response to the semantic and/or syntactic content of the initial conversational user input using pretrained GPTs, LLMs, or other algorithms or configurations associated with the LLM chatbot 152 and/or third party system 150).
Regarding claim 5, Dressler and Ohrn teach the method of claim 1,
Dressler and Ohrn also teach: wherein the telecommunication connection includes one or more of a video channel and an audio channel (Dressler: ¶0027; depending on the implementation, the conversational input may be received by the user selecting or otherwise activating a GUI element presented within the chat window, or the user may input, (e.g., via typing, swiping, touch, voice, or any other suitable method), a conversational string of words in a free-form or unconstrained manner, which is captured by a user input device of the client device 108 and provided over the network 110 to application platform 124 and/or the chatbot service 142 via the client application 109).
Regarding claim 7, Dressler and Ohrn teach the method of claim 1,
Dressler and Ohrn also teach: wherein steps (b) and (g) include using a chatbot (Dressler: ¶0043; the chatbot at the LLM chatbot 152 and/or third party system 150 automatically generates a personalized conversational response that is responsive to the conversational user input but accounts for or otherwise reflects the use’s supplemental textual content).
Regarding claim 8, Dressler and Ohrn teach the method of claim 1,
Dressler and Ohrn also teach: wherein the method is implemented using a device selected from the group consisting of: a smartphone, a tablet computer, a laptop computer, and a general purpose computing device (Dressler: ¶0020; the application server 104 generally represents the one or more server computing devices).
Regarding claim 9, Dressler and Ohrn teach the method of claim 8,
Dressler and Ohrn also teach: wherein the remote device is selected from the group consisting of: another smartphone, another tablet computer, another laptop computer, and another general purpose computing device (Dressler: ¶0022; the client device 108 can be realized as any sort of personal computer, mobile telephone, tablet or other network-enabled electronic device).
Regarding claim 10, Dressler and Ohrn teach the method of claim 1,
Dressler and Ohrn also teach: wherein the method is implemented using a tablet computer (Dressler: ¶0022; the client device 108 can be realized as any sort of personal computer, mobile telephone, tablet or other network-enabled electronic device).
Regarding claim 11, the claim is directed to a device comprising a graphical user display and a processor (Dressler: ¶0022; the client device 108 can be realized as any sort of personal computer, mobile telephone, tablet or other network-enabled electronic device. The client device 108 includes a display device such as a monitor, screen, or another conventional electronic display), executing the method as claimed in claim 1; Claim 11 is similar scope to claim 1 and is therefore rejected under similar rationale.
Regarding claim 12, Dressler and Ohrn teach the device of claim 11,
Dressler and Ohrn also teach: the device further comprising one or more selected from the group consisting of: a communication interface, a microphone, a memory device, and a storage device (Dressler: ¶0022; the client device 108 can be realized as any sort of personal computer, mobile telephone, tablet or other network-enabled electronic device coupled to the network 110 that executes or otherwise supports a web browser or other client application 109 that allows a user to access one or more GUI displays provided by the virtual web application 140. In exemplary implementations, the client device 108 includes a display device and a microphone).
Regarding claim 13, Dressler and Ohrn teach the device of claim 11,
Dressler and Ohrn also teach: wherein the graphical user display is configured to display a graphical user interface, the graphical user interface being configured to minimize the input from the user (Dressler: ¶0027; depending on the implementation, the conversational input may be received by the user selecting or otherwise activating a GUI element presented within the chat window, or the user may input, (e.g., via typing, swiping, touch, voice, or any other suitable method) a conversational string of words in a free-form or unconstrained manner. Note: the use of voice input would minimize the input from the user).
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Dressler and Ohrn as applied to claim 1 above and further in view Martin et al. (“Martin,” US 2023/0420090), filed on Oct. 26, 2021.
Regarding claim 3, Dressler and Ohrn teach the method of claim 1,
Dressler and Ohrn do not appear to teach: wherein step (b) includes displaying a visual direction for the subject.
However Martin teaches a method for providing access to content; wherein step (b) includes displaying a visual direction for the subject (Martin: ¶0155-0156 and Fig. 10; the interactive interface 3100 includes an insight portion 3102 that is configured to display insights to the user that are customized based on the user’s previous interactions to the system 100. The insights can include conversations or messages, for example “Good Afternoon BryanCM2! Here’s where I’ll share tips and information, just for you! Tap “Tell Me More” anytime to learn more”).
Accordingly, it would have been obvious to one of ordinary skill in the art , before the effective filing date of the claimed invention, having the teachings of Martin, Dressler and Ohrn in front of them to include the interactive interface as disclosed by Martin with the customized autogenerated conversational response as taught by Dressler to provide engaging and informative interactions with the user that allows the user to feel in control of his or her diabetes management and gain diabetes education (Martin: ¶0063).
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Dressler and Ohrn as applied to claim 1 above and further in view Ekron (“Ekron,” US 2022/0366131), published on Nov. 17, 2022.
Regarding claim 4, Dressler and Ohrn teach the method of claim 1,
Dressler and Ohrn do not appear to teach: the method further comprising: (i) modifying a graphical user interface based on one or more of an audio capability of the user, a visual capability of the user, and an audio-visual capability of the user.
However Ekron teaches a method for altering display parameters for users with visual impairment; wherein (i) modifying a graphical user interface based on one or more of an audio capability of the user, a visual capability of the user, and an audio-visual capability of the user (Ekron: ¶0287 and Fig. 5; the accessibility GUI may provide a diverse range of web accessibility profiles to suit a wide range of disabled users, each web accessibility profile associated with a set of predefined changes to assist in adapting website to suit the needs of different categories users. The accessibility GUI may present a hearing-impaired profile to address hearing difficulties, and additional profiles to address additional disabilities. In some embodiments, the accessibility GUI may present web accessibility profiles for at least three of : of vision impairment, epilepsy, color blindness, mobility impairment, hearing difficulties, seizures, photosensitivity, cognitive impairment, or dyslexia).
Accordingly, it would have been obvious to one of ordinary skill in the art , before the effective filing date of the claimed invention, having the teachings of Ekron, Dressler and Ohrn in front of them to incorporate the method for altering display parameters for user with specific impairment as disclosed by Ekron with the customized autogenerated conversational response as taught by Dressler to provide an improved computing interface that allow for the selection of a specific web accessibility profile that addresses a particular disability of a user (Ekron: ¶0004).
Claims 6 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Dressler and Ohrn as applied to claim 1 above and further in view Rakshit (“Rakshit,” US 2021/0273892), published on Sept. 2, 2021.
Regarding claim 6, Dressler and Ohrn teach the method of claim 1,
Dressler and Ohrn also teach: wherein the prompt is automatically provided in response to a [detected] concern (Ohrn: ¶0047; Fig 4A depicts an example graphical user interface screen 400A of an application that provides an assistant for authoring context-aware content. As depicted, the assistant may begin the conversation by displaying a UI element 410 that asks how it can help the user).
Dressler and Ohrn do not appear to teach: a concern is a detected concern.
However Rakshit teaches a chatbot enhanced augmented reality device guidance. Rakshit further teaches: a concern is a detected concern (Rakshit: ¶0050; chatbot 112 can utilized sensors attached to computing device 110 and/or devices paired to computing device 110 or chatbot 112 to collect the user’s biometric data. ¶0051; chatbot may use the user’s biometric data to prompt the user).
Accordingly, it would have been obvious to one of ordinary skill in the art , before the effective filing date of the claimed invention, having the teachings of Rakshit, Dressler and Ohrn in front of them to incorporate the use of collected user’s biometric data to interact with the user as disclosed by Rakshit with the customized autogenerated conversational response as taught by Dressler to help a user perform an activity more efficiently by dynamically instructing the user to adjust the user’s actions and/or body position while providing instructions responsive to a query (Rakshit: ¶0009).
Regarding claim 14, Dressler and Ohrn teach the method of claim 1
Dressler and Ohrn also teach: a system used in connection with the method of claim 1 (Dressler: ¶0018 and Fig. 1; computing system 100), the system comprising: a device including: a graphical user display (Dressler: ¶0022; the client device 108 includes a display device); [a camera configured to capture the video stream]; and a processor, the processor configured to implement the method of claim 1 (Dressler: ¶0022; the client device 108 can be realized as any sort of personal computer, mobile telephone, tablet or other network-enabled electronic device. The client device 108 includes a display device such as a monitor, screen, or another conventional electronic display); and another device, the another device being selected from the group consisting of: a smartphone, a tablet computer, a laptop computer, and a general purpose computing device (Dressler: ¶0020 and Fig. 1; the application server 104 generally represents the one or more server computing devices).
Dressler and Ohrn do not appear to teach: the system comprising: a camera configured to capture the video stream.
However Rakshit teaches a chatbot enhanced augmented reality device guidance. Rakshit further teaches: the system (Rakshit: see Fig. 1; a distributed data processing environment 100 includes computing device 110 with user interface 106 and server computer 120) comprising: a camera configured to capture the video stream (Rakshit: ¶0020 and Fig. 1; camera component 108 is executed on computing device 110. In some embodiments, camera component 108 can be located and/or executed anywhere within distributed data processing environment 100. Camera component 108 is capable of recording, transmitting, and storing live or recorded videos and capable of taking, transmitting, and storing photographs. ¶0037; the captured video can be transferred to chatbot 112 on a real-time basis from camera component 108).
Accordingly, it would have been obvious to one of ordinary skill in the art , before the effective filing date of the claimed invention, having the teachings of Rakshit, Dressler and Ohrn in front of them to incorporate the use of augmented reality device to interact with AI based chatbot as disclosed by Rakshit with the customized autogenerated conversational response as taught by Dressler to help a user perform an activity more efficiently by dynamically instructing the user to adjust the user’s actions and/or body position while providing instructions responsive to a query (Rakshit: ¶0009).
Conclusion
The prior art made of record on form PTO-892 and not relied upon is considered pertinent to applicant's disclosure. Applicant is required under 37 C.F.R. § 1.111(c) to consider these references fully when responding to this action.
It is noted that any citation to specific, pages, columns, lines, or figures in the prior art references and any interpretation of the references should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. In re Heck, 699 F.2d 1331, 1332-33,216 USPQ 1038, 1039 (Fed. Cir. 1983) (quoting In re Lemelson, 397 F.2d 1006,1009, 158 USPQ 275,277 (CCPA 1968)).
Inquiry
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Tam T. Tran whose telephone number is (571) 270-5029. The examiner can normally be reached M-F: 7:30 AM - 5:00 PM.
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, William L. Bashore can be reached on 571-272-4088. 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.
/TAM T TRAN/Primary Examiner, Art Unit 2174
Prosecution Insights