DETAILED ACTION
This Office Action is in reply to Applicants response after non-final rejection received on February 23, 2026. Claim(s) 1, 4-6, and 8-20 is/are currently pending in the instant application.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
The Examiner acknowledges the Applicants amendments to claims 1, 6, and 18 and the cancelation of claims 2, 3, and 7 in the response filed on February 23, 2026.
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, 4-6, and 8-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claims 1, 4-6, and 8-20 are directed to one of the four statutory classes of invention (e.g. process, machine, manufacture, or composition of matter). The claims include a system or “apparatus”, method or “process”, or product or “article of manufacture” and is a system for managing distributed resources which is a process (Step 1: YES).
The Examiner has identified independent system Claim 1 as the claim that represents the claimed invention for analysis and is similar to independent system Claims 6 and 18. Claim 1 recites the limitations of (abstract ideas highlighted in italics and additional elements highlighted in bold)
receive, from a plurality of distributed computing devices, first data associated with the plurality of distributed computing devices indicating work performed associated with a first work request;
calculate, using a first machine learning model, a score associated with the first work request based on the first data;
determine whether the score is greater than or equal to a threshold score representing work to be performed;
responsive to determining that the score is greater than or equal to the threshold score:
generate a first message canceling the first work request; and
transmit the first message to at least one distributed computing device of the plurality of distributed computing devices;
receive feedback from at least one distributed computing device, the feedback comprising a second message refusing to cancel the first work request or a third message accepting the cancellation of the first work request;
train the machine leaning model using the feedback; and
calculate future scores using the trained first machine learning model.
These limitations, under their broadest reasonable interpretation, cover performance of the limitation as “Certain Methods of Organizing Human Activity”. Receiving data, calculating a score, comparing to a threshold, generate and transmit a message, receive feedback and calculate a score recites managing personal behavior or relationships. Accordingly, the claim recites an abstract idea. The distributed system management in Claim 1 is just applying generic computer components to the recited abstract limitations. The meeting system in Claim 18 is just applying generic computer components to the recited abstract limitations. Claims 6 and 18 are also abstract for similar reasons. (Step 2A-Prong 1: YES. The claims are abstract)
Claim 18: receive, from one or more user devices associated with one or more users, meeting data regarding a meeting and user data, wherein one of the users is a meeting organizer;
calculate, using content analysis by a first machine learning model, a meeting score, from the meeting data;
determine whether the meeting score is greater than or equal to a meeting threshold score;
responsive to determining that the meeting score is greater than or equal to the meeting threshold score:
generate a first graphical user interface for polling the one or more users regarding whether the meeting should be held;
transmit the first graphical user interface to the one or more user devices for display;
receive results for a poll regarding whether the meetings should be held from the one or more user devices;
determine whether the meeting should be held based on an organizational policy;
train the first machine learning model based on the results of the poll;
responsive to determining that the meeting should be held:
generate a second graphical user interface notifying the one or more users that the meeting will be held;
transmit the second graphical user interface to the one or more user devices for display; responsive to determining that the meeting should not be held:
generate a third graphical user interface notifying the one or more users that the meeting will not be held; and
transmit the third graphical user interface to the one or more user devices for display; and
calculate future meeting scores using the trained first machine learning model.
These limitations, under their broadest reasonable interpretation, cover performance of the limitation as “Certain Methods of Organizing Human Activity”. Receiving data, calculating a score, comparing to a threshold, generating a poll, receiving data from the poll and, making a decision on a meeting and calculating future scores recites managing personal behavior or relationships. Accordingly, the claim recites an abstract idea. The distributed system management in Claim 18 is just applying generic computer components to the recited abstract limitations. The meeting system in Claim 1 is just applying generic computer components to the recited abstract limitations. Claims 1 and 6 are also abstract for similar reasons. (Step 2A-Prong 1: YES. The claims are abstract)
This judicial exception is not integrated into a practical application. In particular, the claims only recite one or more processors and a memory in communication with the processor, machine learning model, user device, and graphical user interfaces (Claims 1, 6, and 18). The computer hardware is recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Therefore claims 1, 6, and 18 are directed to an abstract idea without a practical application. (Step 2A-Prong 2: NO. The additional claimed elements are not integrated into a practical application)
The claims do 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. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a computer hardware amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. See Applicant’s specification para. [0076, 0080, 0068, 0016] about implementation using general purpose or special purpose computing devices ([0076]; The user device 402 can include one or more of a mobile device, smart phone, general purpose computer, tablet computer, laptop computer, telephone, public switched telephone network (PSTN) landline, smart wearable device, voice command device, other mobile computing device, or any other device capable of communicating with the network 406 and ultimately communicating with one or more components of the data system 408.
[0080]; For example, the network 406 may be the Internet, a private data network, virtual private network (VPN) using a public network, and/or other suitable connection(s) that enable(s) components in the system 400 environment to send and receive information between the components of the system 400.] and MPEP 2106.05(f) where applying a computer as a tool is not indicative of significantly more.
[0068] Machine learning models may include a neural network model, a generative adversarial model (GAN), a recurrent neural network (RNN) model, a deep learning model (e.g., a long short-term memory (LSTM) model), a random forest model, a convolutional neural network (CNN) model, a support vector machine (SVM) model, logistic regression, XGBoost, and/or another machine learning model.)
[0016] The systems and methods described herein also utilize, in some instances, graphical user interfaces, which are necessarily rooted in computers and technology. Graphical user interfaces are a computer technology that allows for user interaction with computers through touch, pointing devices, or other means.
Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Thus claims 1, 6, and 18 are not patent eligible. (Step 2B: NO. The claims do not provide significantly more)
Dependent claims 2-5, 7-17, 19, and 20 further define the abstract idea that is present in their respective independent claims 1, 6, and 18 and thus correspond to Certain Methods of Organizing Human Activity and hence are abstract for the reasons presented above. The dependent claims do not include any additional elements that integrate the abstract idea into a practical application or are sufficient to amount to significantly more than the judicial exception when considered both individually and as an ordered combination. The dependent claims include steps or processes which are similar to that disclosed in MPEP 2106.05(d), (f), (g), and/or (h) which include activities and functions the courts have determined to be well-understood, routine, and conventional when claimed in a generic manner, or as insignificant extra solution activity, or as merely indicating a field of use or technological environment in which to apply the judicial exception. Therefore, the claims 2-5, 7-17, 19, and 20 are directed to an abstract idea. Thus, the claims 1-20 are not patent-eligible.
Response to Arguments
The Applicants remarks begin on page 8 of the response on February 23, 2026. The response begins with a summary of the claims and the interview held on February 19, 2026.
The arguments start with the rejection under 35 U.S.C § 102 (remarks page 9) where ethe Applicant states that the reference of Liu fails to disclose the amended limitations of the claim. Similarly, the argument with respect the rejection under 35 U.S.C § 103 is similar with the Applicant arguing that the references do not teach or suggest the amended claim limitations.
The Examiner has withdrawn the rejections under 35 U.S.C § 102 and 103 at this time.
The arguments move on to the rejection under 35 U.S.C § 101 (remarks page 10) where the Applicant states that the claims are amended to recite improvements to the functioning of a computer or improvement to another technology or technical field. The argument specifically state that the claims “recite an improvement to systems for proactively recognizing inefficient uses of resources and time”. Further citing the specification where “it can be difficult to tell whether an activity is going to be inefficient use of time or resources until after that activity occurs”, and where the solution details machine leaning models that proactively determine whether activities are efficient use of resources based on feedback. Applicants arguments for claims 6 and 18 are similar where the Applicant argues the claims are directed to a technical improvement recognizing inefficient uses of resources and time through feedback and training of machine learning models.
The Examiner is not in agreement. First, the courts have made it clear that the use of a computer in a generalized fashion related to efficiency does not meaningfully limit the otherwise abstract claims. In order for the addition of a machine to impose a meaningful limit on the scope of a claim, it must play a significant part in permitting the claimed method to performed, rather than function solely as an obvious mechanism for permitting a solution to be achieve more quickly, i.e. through the utilization of a computer for performing calculations. SiRF Tech., Inc. Regarding the claims, the determination of use of time, and potentially other resources, as efficient or inefficient is not more than an observation and judgement determination. The use of a computer, and or a machine learning model in a generic and known nature, does not overcome the abstract concept.
Also, this is not a technical solution to a technical problem, rather a technical solution to a business problem of time management. The determinations made by a generic computer and an a model running on said computer does not impose meaningful limits on the scope of the claims. Additionally, the claim of feedback to the model is user feedback in cancelling the meeting or a poll question of the usefulness of the meeting. In this case the system is not making the determinations related to efficiency and useful ness rather processing the inputs of the individuals who have responded to the poll or meeting invite. The model is not actually making determinations on it’s own but leveraging the user inputs related to the usefulness or efficiency of the meeting being scheduled.
Also, limitation of training the model is only adding one input to the training dataset and this does not include details or evidence of the improvement to the model. At best the model is changing the parameters of the model but not changing how the model operates. Further, the claims and the specification do not include a clear adjustment to the model which is providing an improved output.
The arguments move to the APR review of In re Desjardins to argue that claim 1 recites a training step based on feedback and calculating a score using the machine learning model. Applicant claims this is a technical improvement to the efficient use of resources and an improvement to system performance based on updated parameters of a machine learning model.
The Examiner disagrees. First, the technical improvement is for efficient use of resources which is not a technical problem, rather a business problem using a technical solution. Further, the determination is not being performed by the model, rather by the humans inputting the feedback of poll results into the model. This means the system is not operating or determining all on it’s own. It’s involving human feedback which is making the determinations and then applying them to the model. Also, the model is “trained” but does not show improvement to the model, rather adjustments to the model parameters. Ergo, the model stays the same and operates the same way and the parameters within the model are adjusted based on the human responses. This is not more than use of a computer as a tool to perform the abstract idea. This does not integrate the judicial exception into a practical application.
In summary, the rejections under 35 U.S.C § 102 and 103 are withdrawn at this time. The rejection under 35 U.S.C § 101 remains. The claims are not allowed.
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 DYLAN C WHITE whose telephone number is (571)272-1406. The examiner can normally be reached M-F 7:30-4:00 EST.
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/DYLAN C WHITE/Primary Examiner, Art Unit 3625 March 24, 2026.