DETAILED ACTION
Status of Claims
This communication is a non-final action on the merits in response to the amendments and arguments filed on March 4, 2026. Claims 1-6, 8-13, 15-18, and 20 were amended. Claims 1-20 are currently pending and have been examined.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 March 4, 2026 has been entered.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Claims 1-7 are directed to a machine. Claims 8-14 are directed to an article of manufacture. Claims 15-20 are directed to a process. As such, each claim is directed to a statutory category of invention.
Step 2A Prong 1
The examiner has identified independent Claim 1 as the claim that represents the claimed invention for analysis and is similar to independent Claims 8 and 15.
Independent Claim 1 recites the following abstract ideas: “receive, from an interview subject, topic information associated with a topic; identify at least one relevant question set based on the topic information, wherein the at least one relevant question set comprises a set of questions relevant to the topic; provide the at least one relevant question set to the interview subject; in response to providing the at least one relevant question set to the interview subject: receive feedback from the interview subject, wherein the feedback is associated with relevance or organization of the questions in the at least one relevant question set; update the at least one relevant question set to generate an updated question set; and generate an interview template based on the updated question set; conduct an interview of the interview subject based on the interview template, wherein conducting the interview comprises providing the updated question set to the interview subject and capturing media content of the interview subject; demarcate, as the interview is conducted, the media content associated with each question of the updated question set; generate the demarcated media content, comprises question delimiters corresponding to the demarcated media content associated with each question, and comprises an introduction that includes a company name and logo and an ending that includes text or graphic information received from the interview subject; and
The limitations, as drafted, are a process that, under its broadest reasonable interpretation, relates to managing personal behavior or relationships or interactions between people including social activities, teaching, and following rules or instructions (i.e., receive, from an interview subject, topic information associated with a topic; identify at least one relevant question set based on the topic information, wherein the at least one relevant question set comprises a set of questions relevant to the topic; provide the at least one relevant question set to the interview subject; in response to providing the at least one relevant question set to the interview subject: receive feedback from the interview subject, wherein the feedback is associated with relevance or organization of the questions in the at least one relevant question set; update the at least one relevant question set to generate an updated question set; and generate an interview template based on the updated question set; conduct an interview of the interview subject based on the interview template, wherein conducting the interview comprises providing the updated question set to the interview subject and capturing media content of the interview subject; demarcate, as the interview is conducted, the media content associated with each question of the updated question set; generate the demarcated media content, comprises question delimiters corresponding to the demarcated media content associated with each question, and comprises an introduction that includes a company name and logo and an ending that includes text or graphic information received from the interview subject), but for the recitation of generic computer components (i.e., a device comprising memory storing instructions and one or more processors in communication with the memory, using and updating at least one trained machine learning model based on feedback, generating a demarcated video, and providing the demarcated video for download). If a claim limitation, under its broadest reasonable interpretation, relates to managing personal behavior or relationships or interactions between people including social activities, teaching, and following rules or instructions, but for the recitation of generic computer components, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas.
Accordingly, the claim recites an abstract idea.
Step 2A Prong 2
This judicial exception is not integrated into a practical application. Limitations that are not indicative of integration into a practical application include: (1) Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (MPEP 2106.05(f)), (2) Adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)), (3) Generally linking the use of the judicial exception to a particular technological environment or field of use (MPEP 2106.05(h)). In particular, the claim recites the additional elements of a device comprising memory storing instructions and one or more processors in communication with the memory, using and updating at least one trained machine learning model based on feedback, generating a demarcated video, and providing the demarcated video for download (in addition to the non-transitory CRM of Claim 8). The computer hardware is recited at a high level of generality (i.e., generic computers receiving and transmitting information, generic trained machine learning model identifying and transmitting information, and being updated based on feedback, and generation and download of a generic demarcated video) such that it amounts to no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application, since they do not involve improvements to the functioning of a computer or to any other technology or technical field (MPEP 2106.05(a)), they do not apply the abstract idea with, or by use of, a particular machine (MPEP 2106.05(b)), they do not effect a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)), and they do not apply or use the abstract idea in some other meaningful way beyond generally linking its use to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception (MPEP 2106.05(e)). Therefore, the claim is directed to an abstract idea without a practical application.
Step 2B
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when considered separately and as an ordered combination, they do not add significantly more (also known as an “inventive concept”) to the exception. The additional elements of using computer hardware (a device comprising memory storing instructions and one or more processors in communication with the memory, using and updating at least one trained machine learning model based on feedback, generating a demarcated video, and providing the demarcated video for download (in addition to the non-transitory CRM of Claim 8)) amounts to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. Therefore, the claim is not patent-eligible.
Dependent claims 2, 4-5, 9, 11-12, 16, and 18-19 recite providing various items “for download,” and dependent claims 4, 11, and 18 recite “comprising at least one hyperlink.” The additional elements are generic technology (i.e., downloads and hyperlink) used to implement the abstract idea, and they do not integrate the abstract idea into a practical application, nor are they sufficient to amount to significantly more than the abstract idea when considered both individually and as an ordered combination.
Dependent claims 3, 6-7, 10, 13-14, 17, and 20 do not include any additional elements beyond those identified above. They further define the abstract idea that is present in their respective independent claims and hence are abstract for at least the reasons presented above. As such, they do not integrate the abstract idea into a practical application, nor are they sufficient to amount to significantly more than the abstract idea when considered both individually and as an ordered combination.
Therefore, dependent claims 2-7, 9-14, and 16-20 are directed to an abstract idea, and do not include additional elements that integrate the abstract idea into a practical application, or that are sufficient to amount to significantly more than the abstract idea. Thus, the aforementioned claims are not patent-eligible.
Allowable Subject Matter
Claims 1-20 would be allowable if rewritten or amended to overcome the rejection under 35 U.S.C. 101 set forth in this Office action.
Stewart, in combination with the other references relied upon, teaches receiving, from an interview subject, topic information associated with a topic, identifying, using at least one trained machine learning model, at least one relevant question set based on the topic information, wherein the at least one relevant question set comprises a set of questions relevant to the topic, providing the at least one relevant question set to the interview subject, receiving feedback from the interview subject, wherein the feedback is associated with relevance or organization of the questions in the at least one relevant question set, updating the at least one trained machine learning model based on the feedback, updating the at least one relevant question set, generating an interview template based on the at least one relevant question set, conducting an interview based on the interview template, wherein conducting the interview comprises providing the at least one relevant question set to the interview subject and capturing media content of the interview subject, generating a video based on the captured media content, wherein the video comprises an introduction that includes a company name and logo and an ending that includes text or graphic information received from the interview subject, and providing the video for download. However, the combination of references does not teach updating, using the updated at least one trained machine learning model, the at least one relevant question set to generate an updated question set, generating an interview template based on the updated question set, conduct an interview of the interview subject, wherein conducting the interview comprises providing the updated question set, demarcating, as the interview is conducted, the media content associated with each question of the updated question set, generating a demarcated video based on the demarcated media content, wherein the demarcated video comprises question delimiters corresponding to the demarcated media content associated with each question.
The closest NPL, “Automatic Skill-Oriented Question Generation and Recommendation for Intelligent Job Interviews,” teaches a system for automatically generating skill-oriented interview questions using machine learning. However, it does not teach receiving feedback from an interview subject and updating the question set to generate an updated question set, then conducting an interview of the interview subject comprising providing the updated question set, or capturing media content of the interview subject, demarcating the media content, and generating a demarcated video based on the demarcated media content.
Response to Arguments
Applicant’s Argument Regarding 35 USC 101 Rejection of Claims 1-20:
Step 2A, Prong 1: Applicant respectfully submits that independent claims 1, 8, and 15 are not merely directed to organizing human activity on a generic computer. Instead, claims 1, 8, and 15 are more properly understood to be directed to specific, unconventional, and technical methods of generating and refining digital content that improve the functioning of a computer system. In particular, the claimed inventions do not merely automate a known manual process. They require an iterative, technical feedback loop to "update the at least one trained machine learning model based on the feedback" and "update, using the updated at least one trained machine learning model, the at least one relevant question set." Moreover, the claimed inventions solve the technical problem of manual video editing by performing specific data processing operations during the interview itself. Instead of a human manually scrubbing through a raw video file after the fact to find where an answer starts and stops, the claimed system is specifically configured to "demarcate, as the interview is conducted, the media content associated with each question of the updated question set." The system then uses this real-time data to "generate a demarcated video based on the demarcated media content, wherein the [demarcated] video comprises question delimiters corresponding to the demarcated media content." A human does not mathematically demarcate digital media content in real-time while conversing to embed structural question delimiters into a generated video file. This is a highly specific data processing operation rooted in computer technology. For at least these reasons, Applicant respectfully submits that the claims do not recite an abstract idea of a certain method of organizing human activity. Therefore, Applicant respectfully submits that independent claims 1, 8, and 15, and the claims depending therefrom, are patent eligible under 35 U.S.C. § 101, at least at Step 2A, Prong 1 of the Alice/Mayo test.
Step 2A, Prong 2:
At least [0036] of the application as originally filed describes that use of the claimed inventions provides a significant improvement over manual, conventional methods of performing candidate video assessments and are necessarily rooted in computer technology and, thus, improve a computer's ability to generate video.
Independent claims 1, 8, and 15 recite, or similarly recite, "identify, using at least one trained machine learning model, at least one relevant question set," "receive feedback from [an] interview subject of the questions in the at least one relevant question set," "update the at least one trained machine learning model based on the feedback," "update, using the updated at least one trained machine learning model, the at least one relevant question set to generate an updated question set," "generate an interview template based on the updated question set," "conduct an interview of the interview subject based on the interview template," "demarcate, as the interview is conducted, the media content associated with each question of the updated question set," and "generate a demarcated video based on the demarcated media content, wherein the video comprises question delimiters corresponding to the demarcated media content associated with each question." This is not a mere or generic use of a computing system, as claims 1, 8, and 15 recite and bring together the one or more trained machine learning models to identify and update a question set, and update the one or more trained machine learning models based on feedback for the question set. Thus, claims 1, 8, and 15 recite a particular system that integrates the alleged abstract ideas into a practical application that meaningfully limits the alleged abstract ideas by using a particular machine comprising particular components in a particular manner. Therefore, claims 1, 8, and 15 apply or use the alleged judicial exception in a meaningful way by linking the use of the judicial exception to a particular technological environment of using one or more trained machine learning models to identify and update a question set, and updating the one or more trained machine learning models based on feedback for the question set, such that the claims as a whole are more than a drafting effort designed to monopolize the alleged abstract idea. Id. at $2106.04(d). Moreover, these steps tie the operations to the one or more processors' ability to use and update machine learning models and to generate video. These steps add meaningful limitations to the alleged abstract idea and, therefore, add significantly more to the alleged abstract idea than mere computer implementation. By this, claims 1, 8, and 15 go beyond generically using a computer.
Moreover, independent claims 1, 8, and 15 recite, or similarly recite, "identifying, using at least one trained machine learning model, at least one relevant question set," updating the at least one trained machine learning model based on… feedback" on the at least one relevant question set, and "updating, using the updated at least one trained machine learning model, the at least one relevant question set," which Applicant respectfully submits is a practical application of the alleged abstract idea. The Director of the U.S. Patent and Trademark Office (USPTO), John Squires, convened an Appeals Review Panel (ARP) to issue a precedential decision in Ex parte Desjardin that vacates a Patent Trial and Appeal Board (PTAB) panel's decision to issue a new ground of rejection under 35 U.S.C. §101 that had not been raised by the patent examiner. The decision instead found the claims to be directed to an eligible invention. The PTAB panel found no additional elements or combination of elements in the claims that may have integrated the abstract idea into a practical application. The ARP disagreed. Citing a foundational patent eligibility case for software-related inventions, Enfish V. Microsoft, the ARP reemphasized that claims directed to an improvement in the functioning of a computer or an improvement to another technology or technical field are patent eligible. Moreover, it noted that Enfish recognized that much of the advancements made in computer technology consist of improvements to software that may not be defined by physical features but rather by logical structures and processes. Turning to the specification of the application on appeal, the ARP found that it identified several technological improvements, including "effectively [learning] new tasks in succession whilst protecting knowledge about previous tasks," "using less storage capacity," and "having reduced system complexity." Therefore, the ARP was persuaded that the claims were directed to an improvement to how the machine learning model at issue operates, and the ARP decision thus found that the claims recited a practical application of the abstract idea and were therefore patent eligible. The Present Application in at least [0069], [0084], and [0089] indicate that updating the one or more trained machine learning models can improve the one or more trained machine learning models' ability to generate better question sets. Therefore, the claims are directed to an improvement to how the claimed machine learning systems operate and, thus, as found in Ex parte Desjardin, the claims recite a practical application of the alleged abstract idea and are therefore patent eligible. For at least these reasons, Applicant respectfully submits that independent claims 1, 8, and 15 are directed to a practical application of the alleged abstract idea. Therefore, Applicant respectfully submits that independent claims 1, 8, and 15, and the claims depending therefrom, are patent eligible under 35 U.S.C. §101, at least at Step 2A, Prong 2 of the Alice/Mayo test.
Examiner’s Response: Applicant’s arguments have been fully considered but they are not persuasive.
Step 2A, Prong 1: The steps of updated a trained machine learning model based on feedback, and updating a question set using the model do not provide an improvement to the functioning of a computer system. Rather, this is using a generic machine learning model in its ordinary capacity. Further, regarding solving the technical problem of manual video editing by performing specific data processing operations during the interview itself, this is a recitation of an improvement to the abstract idea itself, rather than a recitation of an improvement to the functioning of a computer or a technical improvement to video editing technology. Further, the specification does not provide details of how the claimed invention provides an improvement to the functioning of computers or to video editing technology. The claims are directed to the Certain Methods of Organizing Human Activity grouping of abstract ideas, as they are directed to receiving topic information, identifying a relevant question set, providing the question set to an interview subject, receiving feedback from the interview subject, updating the question set, generating an interview template, and conducting an interview of the interview subject based on the template. The additional elements are recited in a generic manner, used as tools to implement the abstract idea.
Step 2A, Prong 2:
As previously stated, the specification, including paragraph [0036], does not provide any details of how the claimed invention provides any improvement to the functioning of a computer, or to video editing technology. Also, regarding the steps of using a trained machine learning model, receiving feedback from a user, updating the model based on the feedback, and updating a question set using the updated mode, the machine learning model is recited at a high level of generality, used in its ordinary capacity, as a tool to implement the abstract idea of identifying and updating an interview question set based on feedback from an interview subject. Regarding the steps of demarcating media content as an interview is conducted and generating a demarcated video, this is also using video and video editing technology in a generic manner, as tools to implement the abstract idea of conducting and recording an interview.
Regarding Ex parte Desjardins, the claimed invention provided an improved way of training a machine learning model that protected the model’s knowledge about previous tasks while allowing it to effectively learn new tasks, the specification identified improvements as to how the machine learning model itself operates, and the claims further reflected the improvement disclosed in the specification. Regarding the present claims, the specification, including paragraphs [0069], [0084], and [0089], does not provide any details of how the claimed invention provides any improvement to a technology or a technical field. Updating a machine learning model based on feedback is using a machine learning model in its ordinary capacity and training a model in a generic manner.
The claimed invention does not pertain to an improvement in the functioning of the computer itself or any other technology or technical field. Thus, the additional elements do not integrate the abstract idea into a practical application.
Applicant’s Argument Regarding 35 USC 103 Rejections of Claims 1-20: Independent claims 1, 8, and 15 have been amended, and no combination of the cited art teaches or suggests the amended features.
Examiner’s Response: Applicant’s arguments have been fully considered and are persuasive. The rejection has been withdrawn.
Conclusion
The prior art made of record and not relied upon, considered pertinent to applicant’s disclosure or directed to the state of art, is listed on the enclosed PTO-892.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KARMA EL-CHANTI whose telephone number is (571)272-3404. The examiner can normally be reached T-Sa 10am-6pm ET.
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, Sarah Monfeldt can be reached at (571)270-1833. 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.
/KARMA A EL-CHANTI/Examiner, Art Unit 3629 /SARAH M MONFELDT/Supervisory Patent Examiner, Art Unit 3629
Prosecution Insights