DETAILED ACTION
This is a Non-Final Office Action in response to the Request for Continued Examination filed 04/10/2026.
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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 04/10/2026 has been entered.
Status of Claims
Claims 1-20 are currently pending in the application and have been examined.
Response to Amendment
The amendment filed 04/10/2026 has been entered.
Response to Arguments
Claim Rejections 35 U.S.C. § 101:
Applicant submits on page 7 of the remarks that the amended claims do not recite a judicial exception. Examiner respectfully disagrees and notes Examiner notes that under step 2A of the analysis of claims per the Alice framework, if a claim limitation covers managing personal behavior or relationships or interactions between people, then it falls within the “certain methods of organizing human activity” grouping of abstract ideas.
Applicant submits on page 8 of the remarks that the amended claims recite an improvement in the field of artificial intelligence. Examiner respectfully disagrees and notes the additional elements recited in the claims are cited in a very general sense performing a computer generic function of sending/receiving data and do not impose any meaningful limit on practicing the abstract idea. Additionally, per the Revised October 2019 guidance: in order to determine if an invention improves the functioning of a computer or other technology and integrate the judicial exception into a practical application, while the courts have not provided an explicit test for this consideration, MPEP 2106.04(a) and 2106.05(a) provide guidance, first the specification should be evaluated to determine if the disclosure provides sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement; second, if the specification sets forth an improvement in technology, the claim must be evaluated to ensure that the claim itself reflects the disclosed improvement. When looking at the specification, the disclosure supports that the provided improvement is directed to the abstract idea.
Regarding Applicant’s comparison to Ex parte Desjardins, the Examiner notes that the claims were patent eligible based on a finding that the claims reflect improvement to training a machine model by using less storage capacity, enabling reduced system complexity and effectively learning new tasks in succession whilst protecting knowledge about previous tasks. The present claims merely recite the use of machine learning to train a model without providing any improvement to the model.
Applicant submits that the claims provide an inventive concept. Examiner respectfully disagrees and notes that because the specification describes the additional elements in general terms without describing the particulars, the claim limitations may be broadly but reasonably construed as reciting conventional computer components and techniques, particularly in light of Applicant’s’ specification. The claim does not provide an inventive concept because the claim, in essence, merely recites various computer-based elements along with no more than mere instructions to implement the identified abstract idea using the computer-based elements.
Claim Rejections 35 U.S.C. § 103:
Applicant’s arguments have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-patentable subject matter. The claims are directed to an abstract idea without significantly more.
With respect to claims 1-20, the independent claims (claims 1, 14 and 19) are directed, in part, to systems and methods for personalized coaching. Step 1 – First pursuant to step 1 in the eligibility analysis, claims 1-13 are directed to a method comprising a series of steps which falls under the statutory category of a process and claims 14-20 are directed to a system which falls under the statutory category of a machine. However, these claim elements are considered to be abstract ideas because they are directed to a method of organizing human activity which includes managing personal behavior and teaching.
As per Step 2A - Prong 1 of the subject matter eligibility analysis, the claims are directed, in part, to using an application programming interface (API) gateway, determining permissions to one or more data sources; using a data extraction engine, extracting information from the one or more data sources to obtain extracted information related to a user; using a goal determination module, analyzing the extracted information to determine user preferences, user biases, and goals information for the user; training a virtual assistant module to account for the user preferences, user biases, and goals information when generating personalized coaching information, wherein the virtual assistant module is configured to generate personalized coaching information using an artificial intelligence protocol; using the trained virtual assistant module, generating personalized coaching information based on the user preferences, user biases, and goals information; transmitting the personalized coaching information to a user device; receiving user feedback from the user device related to the personalized coaching information; and further training the virtual assistant module to adapt generation of the personalized coaching information based on the user feedback. If a claim limitation, under its broadest reasonable interpretation covers managing personal behavior or teaching, then it falls within the “certain methods of organizing human activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
As per Step 2A - Prong 2 of the subject matter eligibility analysis, this judicial exception is not integrated into a practical application. In particular, the independent claims recite additional elements application programming interface, data sources, data extraction engine, virtual assistant module, user device. The dependent claims recite the use of natural language processing, machine learning, database and server. These additional elements are recited at a high-level of generality (i.e., as a generic device performing a generic computer function of receiving and storing data) such that these elements amount no more than mere instructions to apply the exception using a generic computer component. Examiner looks to Applicant’s specification in at least figures 1 and 6 and related text and [0054-0059] to understand that the invention may be implemented in a generic environment that “Devices 602, 620 can be or include any suitable device with wired or wireless communication features and that can connect to network 622. For example, one or more of devices 602, 620 can be or include a wearable device, a tablet computer, a wired phone, a mobile phone, a personal (e.g., laptop or desktop) computer, a streaming device, such as a game console or other media streaming device, or the like. One or more of devices 602, 620 can include an application or client 630 to perform various functions set forth herein and/or to cause to be displayed text and/or other information as described herein. By way of example, an application or client 630 can include a user interface that displays virtual assistant information as described herein and/or that allows a user to provide user and/or feedback and/or user profile information as described herein. Network 622 can include or be, for example, an internet protocol (IP) network. Exemplary types of networks suitable for network 622 can be or include a local area network, a wide-area network, a metropolitan area network, one or more wireless networks, or a portion of the Internet. Various components of network 622 can be coupled to one or more other components using an Ethernet connection, other wired connections, and/or wireless interfaces. Network 622 can be coupled to other networks and/or to other devices typically coupled to networks. By way of particular example, network 622 includes a communication network and network 622 can be coupled to additional networks that can be coupled to one or more devices, such as devices 602 and 620. Exemplary additional networks can include a network similar to network 622, a public switched telephone network (PSTN), or the like. Servers or data sources 604-612 can be or include any suitable server(s). Servers
604-612 can perform various functions as described herein. For example, server 604 can be a communication (e.g., a private branch exchange (PBX) server), server 606 can be a text server, server 608 can be an email server, server 610 can be a document or file server, and server 612 can be a social media server. Although separately illustrated, various servers 604-614 can be combined in a single system or machine. Further, it will be appreciated that other servers and/or data sources can be coupled to or form part of electronic communication system 600. Electronic communication system 600 includes various engines, database(s),
and/or modules as described herein. As used herein, the terms engine and module may be used interchangeably. In some cases, a module can include one or more engines and/or be coupled to one or more engines. The terms "module" or "engine" can refer to computer program instructions, encoded on computer storage medium for execution by, or to control the operation of, data processing apparatus. Alternatively, or additionally, the program instructions can be encoded on an artificially generated propagated signal, e.g., a machine-generated electrical, optical, or electromagnetic signal, which is generated to encode information for transmission to suitable receiver apparatus for execution by a data processing apparatus. A computer storage medium can be, or be included in, a computer-readable storage device, a computer-readable storage substrate, a random or serial access memory array or device, or a combination of one or more of the substrates and devices. Moreover, while a computer storage medium is not a propagated signal, a computer storage medium can be a source or destination of computer program instructions encoded in an artificially generated propagated signal. The computer storage medium can also be, or be included in, one or more separate physical components or media (e.g., solid-state memory that forms part of a device, disks, or other storage devices). As noted above, application programming interface (API) gateway 614 is coupled to one or more data sources 604-612.API gateway 614 is configured to determine permissions to one or more data sources 604-612 to allow extraction of information from the one or more data sources 604-612.” Accordingly, these additional elements do not integrate the abstract idea into a practical application because they are mere instructions to implement the abstract idea on a computer.
As per Step 2B of the subject matter eligibility analysis, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional elements are mere instructions to apply the abstract idea on a computer. When considered individually, these claim elements only contribute generic recitations of technical elements to the claims. It is readily apparent, for example, that the claim is not directed to any specific improvements of these elements and the invention is not directed to a technical improvement. When the claims are considered individually and as a whole, the additional elements noted above, appear to merely apply the abstract concept to a technical environment in a very general sense – i.e. a generic computer receives information from another generic computer, processes the information and then sends information back. In addition, when taken as an ordered combination, the ordered combination adds nothing that is not already present as when the elements are taken individually. Their collective functions merely provide generic computer implementation. Therefore, when viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a practical application of the abstract idea or that amount to significantly more than the abstract idea itself. The most significant elements of the claims, that is the elements that really outline the inventive elements of the claims, are set forth in the elements identified as an abstract idea. The fact that the generic computing devices are facilitating the abstract concept is not enough to confer statutory subject matter eligibility. Regarding the use of Natural Language Processing to evaluate the received data, the Examiner notes that this activity is recognized as well-understood, routine, and conventional in the art, which does not amount to significantly more than the abstract idea itself. See, e.g., Morsa, US 2006/0085408 (paragraph 0144: well -known-to-the-arts natural language processing (NLP) (computational linguistics) or some other method as is well known to the arts may be used). See also, Szabo, US Pat. No. 5,966,126 (col. 6, lines 57-62 and col. 28, lines 16-19: e.g., definitions may be produced in known manner, such as by explicit definition, or through use of assistive technologies, such as natural language translators; user defines a search using prior known techniques, such as natural language searching). Lastly, when the “machine learning” is evaluated as an additional element, this feature is recited at a high level of generality and encompasses well-understood, routine, and conventional prior art activity. See, e.g., Balsiger et al., US 2012/0054642, noting in paragraph [0077] that “Machine learning is well known to those skilled in the art.” See also, Djordjevic et al. US 2013/0018651, noting in paragraph [0019] that “As known in the art, a generative model can be used in machine learning to model observed data directly.” See also, Bauer et al., US 2017/0147941, noting at paragraph [0002] that “Problems of understanding the behavior or decisions made by machine learning models have been recognized in the conventional art and various techniques have been developed to provide solutions.” Accordingly, the use of machine learning to generate a learning model does not add significantly more to the claims.
The dependent claims further refine the abstract idea. These claims do not provide a meaningful linking to the judicial exception. Rather, these claims offer further descriptive limitations of elements found in the independent claims and addressed above – such as by describing the nature and content of the data that is received/sent. While these descriptive elements may provide further helpful context for the claimed invention these elements do not serve to confer subject matter eligibility to the invention since their individual and combined significance is still not significantly more than the abstract concepts at the core of the claimed invention.
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 (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 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)(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.
Claim(s) 1-3, 5, 8, 10-11, 13, 15-17, 19-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by US Pub. No. 2020/0269136 (hereinafter; Guru).
Regarding claims 1/14/19, Guru discloses:
An electronic communication method; system with adaptive personalization and coaching, (Guru [0011] discloses the determination of personalized advice or training for users of an application.) the method comprising the steps of: using an application programming interface (API) gateway, (Guru [0032] discloses the use of an application programming interface.) determining permissions to one or more data sources; (Guru discloses permitted data usage and access in at least [0036]; [0042]; [0065].) using a data extraction engine, extracting information from the one or more data sources to obtain extracted information related to a user; (Guru [0049] discloses a deep neural network that extracts useful information.) using a goal determination module, analyzing the extracted information to determine user preferences, user biases, and goals information for the user; (Guru [0012] discloses information can be provided as input as well, as may relate to one or more goals of the player, a player type, a skill level of the player, etc. The selected model can take the input information and infer, or otherwise generate, one or more actions or strategies to be taken by the player in order to achieve a determined goal, or at least making progress toward that goal; The types of advice or coaching given can vary depending upon factors such as the goals, skill level, and preferences of the player, and the types of advice given to a specific player can change over time as that player's skill set or preferences change.) training a virtual assistant module to account for the user preferences, user biases, and goals information when generating personalized coaching information, wherein the virtual assistant module is configured to generate personalized coaching information using an artificial intelligence protocol; (Guru [0029] discloses In at least some embodiments, such an approach can help to provide a machine learning—or artificial intelligence-based virtual coach, which can assist players, such as e-sports gamers, in learning and/or improving their gameplay for at least certain games.) using the trained virtual assistant module, generating personalized coaching information based on the user preferences, user biases, and goals information; (Guru [0021] discloses examples of advice or guidance that a virtual coach might provide to a gamer in accordance with various embodiments. As mentioned, the types of advice provided can depend in part upon factors such as the type of player, player skill level, player or game goal, or whether the advice is provided in a real-time or offline fashion, among other such options.) transmitting the personalized coaching information to a user device; (Guru [0075] discloses The server(s) may also be capable of executing programs or scripts in response requests from user devices.) receiving user feedback from the user device related to the personalized coaching information; (Guru [0070] discloses An example training process can suggest different hyperparameter configurations based on feedback for the performance of previous configurations.) and further training the virtual assistant module to adapt generation of the personalized coaching information based on the user feedback. (Guru [0012] discloses Approaches in accordance with various embodiments provide for the determination of personalized advice or training for users of an application. In particular, various embodiments provide a virtual coach that can help teach, train, or improve the skills of users of an application, such as a gaming application. Data can be obtained that demonstrates how skilled users utilize an application, such as how professional players play a specific game. This data can be used to train one or more machine learning models, for example, that can then provide inferences as to actions that should be taken in the game based on that training.)
Regarding claim 2, Guru discloses:
The method of claim 1, wherein the step of using the goal determination module comprises using natural language processing (NLP) to analyze the extracted information.
Regarding claim 3, Guru discloses:
The method of claim 1, wherein the step of using the goal determination module comprises using a context determination engine to determine a context associated with the extracted information. (Guru [0047] discloses a deep learning or neural learning system that needs to be trained while also assigning context to objects.)
Regarding claim 5, Guru discloses:
The method of claim 1, further comprising establishing a communication between the user device and a participant device. (Guru [0034] discloses communication between participants.)
Regarding claim 8, Guru discloses:
The method of claim 1, further comprising a step of updating user information based on the personalized coaching information. (Guru [0023] discloses updating information and advice.)
Regarding claim 10, Guru discloses:
The method of claim 1, further comprising monitoring the one or more data sources for additional information related to the user preferences, user biases, and goals information. (Guru [0012] discloses the types of advice given to a specific player can change over time as that player's skill set or preferences change.)
Regarding claim 11, Guru discloses:
The method of claim 1, further comprising repeating the steps of: using the data extraction engine, extracting information from the one or more data sources to obtain extracted information; using the goal determination module, determining user preferences and goals based on the extracted information; using the virtual assistant module, generating personalized coaching information based on the user preferences and goals; and transmitting the personalized coaching information to the user device. (See at least Guru Figs. 4-5.)
Regarding claim 13, Guru discloses:
The method of claim 1, further comprising, using machine learning, classifying segments of the extracted information. (Guru [0047-0049] disclose the use of machine learning and deep neural networks for classification.)
Regarding claim 15, Guru discloses:
The system of claim 14, further comprising a database comprising user information. (Guru [0012] discloses player data and user input data.)
Regarding claim 16, Guru discloses:
The system of claim 14, further comprising a user interface, wherein the user interface is configured to receive a command from the user to endorse, suspend, and/or change a frequency of receipt of personalized coaching information by a user device. (Guru [0018]; [0031] disclose user inputs.)
Regarding claim 17, Guru discloses:
The system of claim 14, further comprising a context determination engine to determine a context of the extracted information. (Guru [0047] discloses a deep learning or neural learning system that needs to be trained while also assigning context to objects.)
Regarding claim 20, Guru discloses:
The system of claim 19, wherein the one or more data sources comprise one or more of a communication server, a text server, an email server, a document server, and a social media server. (Guru [0012; [0032] disclose a game server.)
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, 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 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 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.
Claim(s) 4, 6-7, 9, 12, 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Guru in view of US Pub. No. 2021/0043099 (hereinafter; Du).
Regarding claim 4, although Guru discloses a system for personalized coaching, Guru does not specifically disclose sentiment. However, Du discloses the following limitations:
The method of claim 1, wherein the step of using the goal determination module comprises using a sentiment analysis engine to determine a sentiment associated with the extracted information, wherein the personalized coaching information is further generated based on the sentiment. (Du discloses sentiment in at least [0013].)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the system for training of Guru with the artificial intelligence personal assistants of Du in order to provide collaborate modes of coaching (Du abstract) because the references are analogous since they both fall within Applicant's field of endeavor and are reasonably pertinent to the problem with which Applicant is concerned.
Regarding claim 6, although Guru discloses a system for personalized coaching, Guru does not specifically disclose regulatory and standards information. However, Du discloses the following limitations:
The method of claim 1, further comprising transmitting regulatory and standards information to the user device. (Du discloses standards in at least [0039].)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the system for training of Guru with the artificial intelligence personal assistants of Du in order to provide collaborate modes of coaching (Du abstract) because the references are analogous since they both fall within Applicant's field of endeavor and are reasonably pertinent to the problem with which Applicant is concerned.
Regarding claim 7, although Guru discloses a system for personalized coaching, Guru does not specifically disclose frequency of coaching. However, Du discloses the following limitations:
The method of claim 1, further comprising: receiving, from the user device, a selected frequency of receipt of the personalized coaching information for the user; adapting a frequency of generation of the personalized coaching information based on the selected frequency. (Du discloses frequency of coaching in at least [0054].)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the system for training of Guru with the artificial intelligence personal assistants of Du in order to provide collaborate modes of coaching (Du abstract) because the references are analogous since they both fall within Applicant's field of endeavor and are reasonably pertinent to the problem with which Applicant is concerned.
Regarding claim 9, although Guru discloses a system for personalized coaching, Guru does not specifically disclose frequency of coaching. However, Du discloses the following limitations:
The method of claim 1, further comprising:(Du discloses frequency of coaching in at least [0054].)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the system for training of Guru with the artificial intelligence personal assistants of Du in order to provide collaborate modes of coaching (Du abstract) because the references are analogous since they both fall within Applicant's field of endeavor and are reasonably pertinent to the problem with which Applicant is concerned.
Regarding claim 12, although Guru discloses a system for personalized coaching, Guru does not specifically disclose topics. However, Du discloses the following limitations:
The method of claim 1, further comprising determining one or more topics associated with the extracted information. (Du discloses topics in at least [0065]; [0075-0079].)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the system for training of Guru with the artificial intelligence personal assistants of Du in order to provide collaborate modes of coaching (Du abstract) because the references are analogous since they both fall within Applicant's field of endeavor and are reasonably pertinent to the problem with which Applicant is concerned.
Regarding claim 18, although Guru discloses a system for personalized coaching, Guru does not specifically disclose sentiment. However, Du discloses the following limitations:
The system of claim 14, further comprising a sentiment analysis engine to determine a sentiment of the extracted information. (Du discloses sentiment in at least [0013].)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the system for training of Guru with the artificial intelligence personal assistants of Du in order to provide collaborate modes of coaching (Du abstract) because the references are analogous since they both fall within Applicant's field of endeavor and are reasonably pertinent to the problem with which Applicant is concerned.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to FRANCIS Z SANTIAGO-MERCED whose telephone number is (571)270-5562. The examiner can normally be reached M-F 7am-4:30pm EST.
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/FRANCIS Z. SANTIAGO MERCED/Examiner, Art Unit 3625
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