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 .
Detailed Action
This Final Office Action is in response to Applicant’s filing of 12/05/2025.
The effective filing date of the present application is 03/20/2020.
Claims 1 – 20 are pending.
Response to Amendment
Applicant's reply and remarks of 12/05/2025 have been entered.
The examiner will address applicant's remarks at the end of this office action.
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.
At Step 1 of eligibility analysis, the claims recite a system and a method; thus, all claims fall within one of the four statutory categories as required.
At Step 2A, Prong One, of eligibility analysis, the claims set forth a method of retrieving data, analyzing that data, and determining an appropriate output based on that analysis. These actions describe the process for evaluating data and making a judgment based on that data. Because these actions recite limitations that can practically be performed in the human mind, they are considered to recite a mental process, which is an abstract idea.
Claim 11, which is illustrative of clam 1, contains elements that define this method and abstract idea (and are highlighted below):
A method for generating land responses from biological extractions, the method comprising:
retrieving, by a computing device, a biological extraction pertaining to a user, wherein the biological extraction contains at least an element of physiological data;
locating, by the computing device, a land descriptor wherein the land descriptor identifies a property;
generating, by the computing device, land machine-learning model, wherein generating the land machine-learning model comprises training the land machine-learning model with training data correlating biological extractions to property elements of a property, wherein the land machine-learning model receives the biological extraction and the land descriptor as an input and outputs property elements;
generating, by the computing device, the property elements, as a function of a trained land machine-learning model, wherein the property elements comprise a likelihood indication of contribution to a medical condition;
receiving, by the computing device, a user property preference;
determining, by the computing device, suitability of the property utilizing the generated property elements and the user property preference, wherein determining suitability comprises generating a property preference classifier configured to correlate the generated property elements to a user property preference; and
locating, by the computing device, as function of the property preference classifier, a property that is suitable for the user based on the generated property elements and the user property preference.
At Step 2A, Prong Two, the Examiner has determined that the identified abstract idea (judicial exception) is not integrated into a practical application because the additional elements are merely instructions to apply the abstract idea to a computer, as described in MPEP 2106.05(f). Further, in MPEP 2106.05(f) it is noted that "[use] of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general-purpose computer or computer components after the fact to an abstract idea does not integrate a judicial exception into a practical application or provide significantly more.” Therefore, according to the MPEP, this is not solely limited to computers but includes other technology that, recited in an equivalent to “apply it,” is a mere instruction to perform the abstract idea on that technology.
Claims 1 and 11 recite only the following additional elements:
An artificial intelligence system for generating land responses from biological extractions, the system comprising a computing device;
a land machine-learning model.
Certain elements are mere instructions to apply the abstract idea to a computer, per MPEP § 2106.05(f). Applicant has described a computing device generically within the disclosure, at Specification [0009] and Figure 1, as filed. Simply implementing the abstract idea on a generic computer is not a practical application of the abstract idea.
The claims include steps of a machine learning model; however, Applicant only recites nominal use by claiming inputs and outputs at a basic level. The inputs include “biological extraction” and “land descriptor”. These elements are broadly defined at Specification [0011 and 0055]. The use of a generic algorithm to model this collected data is applied on the general-purpose computer recited. As noted above, simply implementing the abstract idea on a generic computer is not a practical application of the abstract idea. The claims are directed to an abstract idea.
At Step 2B of analysis, the Examiner has determined that the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because they do not amount to more than simply instructing one to practice the abstract idea by using generically recited devices to perform the steps that define the abstract idea. As discussed above, the additional elements of (a computing device; a land machine-learning model), are recited at a high level of generality and are instructions to apply the exception on a computer. See MPEP § 2106.05(f).
Dependent claims 2, 3, 5, 12, 13, and 15, contain further embellishments to the same abstract idea found in claims 1 and 11. Recitations to environment toxins, air quality, and weather conditions are enhancements of the data to be evaluated and generating an output for. These recitations are directed to the mental process – the abstract idea. Further to these claims, the only additional elements are the computing device and machine learning model of claims 1 and 11. This is simply linking the claims to using a computer as a tool to implement the abstract idea and are not sufficient to provide for integration into a practical application and/or significantly more. See MPEP 2106.05(f).
Dependent claims 4, 7, 14, and 17, contain further embellishments to the same abstract idea found in claims 1 and 11. Recitations to a group of users, and user geolocation further define the goal of the mental process; generate an output for users based on data modelling. Further to claims 7, and 17, is the use of the device’s geolocation feature. the only additional element is the device of claims 1 and 11, which, as detailed above, is simply a recitation to computer implementation. This is simply using the device in its ordinary capacity for tasks such as geolocating. See Specification [0056]. Therefore, these limitations do not amount to significantly more than the exception itself. See MPEP § 2106.05(f).
Dependent claims 6 and 16 contain further embellishments to the same abstract idea found in claims 1 and 11. Recitations to a historical record is a recitation to data, and is therefore, directed to the mental process of data evaluation. Further to these claims, the only additional elements is the computing device recited. This is simply linking the claims to using a computer as a tool to implement the abstract idea and are not sufficient to provide for integration into a practical application and/or significantly more. See MPEP 2106.05(f).
Dependent claims 8 and 18 contain further embellishments to the same abstract idea found in claims 1 and 11. Recitations to a land classifier is a recitation to more data, and is therefore, directed to the mental process of data evaluation. Further to these claims, is the use of this data as input to the machine learning model. However, Applicant only recites nominal use by claiming inputs and outputs at a basic level. The use of a generic algorithm to model this collected data is applied on the general-purpose computer recited; the claims are directed to the abstract idea.
Dependent claims 9, 10, 19, and 20, contain further embellishments to the same abstract idea found in claims 1 and 11. Recitations to unsuitability and a neutralizer element are all core facets on which to make a judgment. Therefore, they are directed to the abstract idea. Further to these claims, the only additional element is the system of claims 1 and 11, where, as detailed above, is simply a recitation to computer implementation. and is not sufficient to provide for integration into a practical application and/or significantly more. See MPEP 2106.05(f).
Therefore, for the reasons set above, claims 1 – 20 are directed to an abstract idea without integration into a practical application and without significantly more.
Response to Arguments
Applicant's arguments filed 12/05/2025 have been fully considered but they are not persuasive. Applicant’s arguments discuss rejection of prior claims under 35 U.S.C. § 101. See page 6. Applicant contends that the amened claims are allowable under Step 2A and/or 2B of eligibility analysis, and argues that the claims do not recite a mental process. See page 7. Based on the reasoning that follows, the Examiner respectfully disagrees with Applicant’s arguments.
Applicant’s arguments fist discuss Step 2A, Prong One, and points to steps of generating a learning model, generating property elements, and further training of a machine learning model. See pages 8 – 9. Applicant contends that these steps cannot be reasonably performed mentally. This argument is not persuasive. As the Examiner highlighted above, certain elements within amended claims 1 and 11 recite steps that can be performed mentally, and therefore are directed to an abstract idea. They include the retrieval and locating of data, as well as the generating and determining steps that describe data analysis. The other elements, (not highlighted above), and cited by Applicant, describe the argued aspect of a machine learning model. However, Applicant is using a modelling technique that is generic in nature, and is mere instruction to apply the process on a computer. In combination, the elements within the amended claims set forth a method of analyzing data and determining an output based on that analysis. Therefore, the claims describe the process for evaluating data and making a judgment based – which is an abstract idea.
Applicant next argues Step 2A, Prong Two, analysis. See page 9. Analysis here evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception or whether the claim is “directed to” the judicial exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. See MPEP 2106.05(a) through (c), and MPEP 2106.05(e) through (h). The instant amended claim recites the additional elements identified earlier; namely, the system comprising a computing device; a land machine-learning model. These elements are broadly defined at Specification [0011 and 0057]. The use of a generic algorithm to model this collected data is applied on the general-purpose computer recited. As noted above, simply implementing the abstract idea on a generic computer is not a practical application of the abstract idea. The claims are directed to an abstract idea. Applicants newly added limitation of generate the property elements is defined at [0071] as “data”, thereby, further describing use of a model to learn patterns to make decisions. Merely reciting training of a machine learning model without significant details of the training algorithm is describing nominal use of the modeling technique. Further, merely outputting a result from the model without significant details of how the model operates to obtain these results is not enough to show integration into a practical application. Applicant’s arguments are not persuasive.
Applicant next points to the July 2024 Subject Matter Eligibility Example 47 (claim 3) and Example 48 (claim 2). See pages 9 – 10. These citations and Applicant’s arguments are not persuasive. Regarding Example 47, claim 3); the disclosed system detects network intrusions and takes real-time remedial actions, including dropping suspicious packets and blocking traffic from suspicious source addresses. The background section further explains that the disclosed system enhances security by acting in real time to proactively prevent network intrusions. Steps (d)-(f) provide for improved network security using the information from the detection to enhance security by taking proactive measures to remediate the danger by detecting the source address associated with the potentially malicious packets. No such additional elements are present within the instant amended claims that serve to improve the training of a learning model, nor improve any technology employed to generate land responses. Applicant’s use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general-purpose computer or computer components after the fact to an abstract idea does not integrate a judicial exception into a practical application or provide significantly more.
Regarding Example 48, claim 2); similar to the above discussion, these claim recitations include steps (f) and (g), which are directed to creating a new speech signal that no longer contains extraneous speech signals from unwanted sources. The claimed invention reflects this technical improvement by including these features. Further, converting clusters into separate speech waveforms and generating a mixed speech signal from the separate speech waveforms are not insignificant extra-solution activity, mere instructions to apply the exception, or mere field of use limitations. Rather, these steps reflect the improvement described in the disclosure. Again, no such additional elements are present within the instant amended claims that serve to improve the training of a learning model, nor improve any technology employed to generate land responses. Applicant’s use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general-purpose computer or computer components after the fact to an abstract idea does not integrate a judicial exception into a practical application or provide significantly more. Applicant’s arguments are not persuasive.
Applicant’s final argument discusses Step 2B analysis. See page 11. Applicant argues that the amended claims reflect the types of meaningful technological enhancement recognized as patent eligible under Berkheimer. The Examiner respectfully disagrees with Applicant. Evaluation here requires considering additional elements both individually and in combination to ensure that they amount to significantly more than the judicial exception itself. Here, the Examiner has determined that the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because they do not amount to more than simply instructing one to practice the abstract idea by using generically recited devices to perform the steps that define the abstract idea. As discussed above, the additional elements of (a computing device; a land machine-learning model), are recited at a high level of generality and are instructions to apply the exception on a computer. See MPEP § 2106.05(f). Applicant’s arguments are not persuasive.
Conclusion
Regarding claims 1 – 20, prior art does not teach nor suggest a system or method as claimed. The Examiner points to and maintains a conclusion detailed within the Office Action filed 06/05/2025. Accordingly, the current claim set is distinguished over prior art.
Noting that patentability of any claimed invention under 35 U.S.C. §§ 102 and 103 with respect to the prior art is neither required for, nor a guarantee of, patent eligibility under 35 U.S.C. 101, the Examiner points to other rejections within this Office Action.
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 DON EDMONDS whose telephone number is (571) 272-6171. The examiner can normally be reached M-F 8am-4pm EST.
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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.
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DONALD J. EDMONDS
Examiner
Art Unit 3629
/SARAH M MONFELDT/Supervisory Patent Examiner, Art Unit 3629