DETAILED ACTION
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 amendment filed August 29, 2025 has been entered. Claims 1, 3, 4, 6-11, 13, 14, and 16-21 are pending; claims 2, 5, 12 and 15 are previously cancelled.
Applicant’s amendments and arguments are sufficient to overcome the rejection of the claims under 35 U.S.C. 112(a). It is clear that Applicant’s claimed invention utilizes readily available artificial intelligence/machine learning algorithms and training methods well-apprised by one of ordinary skill in the art before the effective filing date of the invention.
Applicant’s amendments and arguments are insufficient to overcome the rejection of the claims under 35 U.S.C. 101.
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, 3, 4, 6-11, 13, 14, and 16-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more. Each claim of amended claims 1-21 has been analyzed to determine whether it is directed to any judicial exceptions.
Step 2A, Prong 1
Each of the claims recites steps or instructions for generating a user-specific treatment, which is grouped as a mental process and/or mathematical concept. Accordingly, each of the claims recites an abstract idea.
Specifically, independent claims 1, 11, and 21 similarly recite the following limitation concepts:
one or more processors (additional element);
a scalp and hair analysis application (app) comprising computing instructions configured to execute on the one or more processors (additional element); and
an Al based learning model, accessible by the scalp and hair analysis app, and trained with training data comprising
(1) label training data defining scalp qualities scores of respective individuals, and
(2) feature training data comprising one or more features of a scalp region, a hair region, and a wash frequency for the respective individuals,
wherein each scalp quality score is assigned, as input into a machine learning algorithm for training the AI based learning model, to at least feature data for the scalp region, the hair region, and the wash frequency of at least one of the respective individuals, (additional element and/or evaluation, judgement, or observation and/or mathematical concept, data gathered),
the Al based learning model configured to output one or more scalp or hair predictions corresponding to the one or more features of the respective individuals (evaluation, judgement, or observation and/or extra-solution activity),
wherein the training data… (data gathered),
wherein the computing instructions of the scalp and hair analysis app when executed by the one or more processors, cause the one or more processors to:
receive user-specific data of a user… (data gathering),
analyze, by the Al based learning model, the user-specific data to generate a scalp or hair prediction value corresponding to the scalp or hair region of the user (evaluation, judgement, or observation),
generate, based on the scalp or hair prediction value, a user-specific treatment designed to address at least one feature based on the scalp or hair prediction value of the user's scalp or hair region (evaluation, judgement or observation), and
display, on a user interface, an image depicting a scalp or hair region as identified by the user, wherein the image is graphically annotated with one or more graphics on the user interface to indicate the scalp or hair prediction value for the at least one feature of the user (additional element, extra-solution activity).
As indicated above, the independent claims recite at least one step or instruction grouped as a mental process. Therefore, each of the independent claims recites an abstract idea. Each limitation grouped as a mental process (see italicized portions above) is addressed as follows:
An AI based learning model is claimed broadly enough such that the actions performed, aside from the processor and computing instruction language, recite an individual observing appropriate data gathered (i.e., training data and user-specific data), and performing evaluations thereon as required by, broadly, any learning model trained with the claimed input data. The limitation of an AI based learning model generating an output can be interpreted as the end-result of a series of mental process evaluation steps performed by the AI based learning model for multiple users and/or providing such an output as the extra-solution activity of data output.
The limitation of generating a user-specific treatment can be identified as further evaluation based on the observation of output of a previous mental process step, which is mere extension of the mental process.
The limitation of displaying on a user interface an annotated image is a step which is easily performed in pen and paper practice. For instance, an individual may observe the output of the AI based learning model and annotate a drawing of a user’s scalp with the appropriate data.
Alternatively or additionally, these steps describe the concept of using implicit mathematical formula(s) (i.e., mathematical steps required in evaluating an AI based learning model and/or training) to derive a conclusion based on input of medical data, which corresponds to concepts identified as abstract ideas by the courts, such as in Diamond v. Diehr. 450 U.S. 175, 209 U.S.P.Q. 1 (1981), Parker v. Flook. 437 U.S. 584, 19 U.S.P.Q. 193 (1978), and In re Grams. 888 F.2d 835, 12 U.S.P.Q.2d 1824 (Fed. Cir. 1989). The concept of the recited steps above is not meaningfully different than those mathematical concepts found by the courts to be abstract ideas.
The claims do not recite any limitations, aside from embodying such processes in a computer environment, which preclude such a process from being performed in the mind and/or by pen-and-paper practice.
The dependent claims merely include limitations that either further define the abstract idea (e.g. limitations relating to the data gathered or particular steps which are entirely embodied in the mental process) and amount to no more than generally linking the use of the abstract idea to a particular technological environment or field of use because they are merely incidental or token additions to the claims that do not alter or affect how the process steps are performed. Particularly, claims 9 and 19 merely recite post-solution data output.
In addition, these concepts are similar to court decisions of abstract ideas of itself: collecting, displaying, and manipulating data (Int. Ventures v. Cap One Financial), collecting information, analyzing it, and displaying certain results of the collection and analysis (Electric Power Group), collection, storage, and recognition of data (Smart Systems Innovations).
Step 2A, Prong 2
The above-identified abstract idea is not integrated into a practical application because the additional elements, either alone or in combination, generally link the use of the above-identified abstract idea to a particular technological environment or field of use. More specifically, the additional elements of a processor, an application, measurement device, and user interface are generically recited elements which do not improve the functioning of a computer, or any other technology or technical field.
The application is recited as computer instructions for carrying out the abstract idea on a processor. The processor is recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of performing calculations) such that it amounts no more than mere instructions to apply the exception using a generic computer component. The non-transitory computer readable medium of claim 21 is similarly interpreted.
The measurement device is similarly generically claimed, and its involvement amounts to no more than performing insignificant, extra-solution activity in the form of mere data gathering, which does not constitute an integration into a practical application. Examiner further notes that a measurement device is not explicitly required by the claim, but rather is a quality of the data input as training data.
The user interface is similarly generically claimed, and its involvement amounts to no more than performing insignificant, extra-solution activity in the form of mere data output, which does not constitute an integration into a practical application.
Thus, such additional elements do not serve to apply the above-identified abstract idea with, or by use of, a particular machine, effect a transformation or apply or use the above-identified abstract idea in some other meaningful way beyond generally linking the use thereof to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. Furthermore, the above-identified generically recited elements do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. For at least these reasons, the abstract idea is not integrated into a practical application.
Examiner notes that the step of “generate, based on the scalp or hair prediction value, a user-specific treatment designed to address at least one feature based on the scalp or hair prediction value of the user's scalp or hair region” is not a limitation which is considered an additional element separate from the abstract idea. Even so, such a limitation is not considered as integrating the claim into a judicial exception – the claim appears most relevant to applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition (see MPEP 2106.04(d)(2)); however, a treatment is merely claimed as generated, not having any particular output to effect a particular treatment or prophylaxis, and is considered merely an additional step of evaluation in the mental process.
Accordingly, the claims are each directed to an abstract idea.
Step 2B
None of the claims include additional elements that, when viewed as a whole, are sufficient to amount to significantly more than the abstract idea.
It is clear from the claims themselves and the specification that each independent claim limitation requires no improved computer resources and merely utilize already available computers with their already available basic functions to use as tools in executing the claimed process.
The additional element of a processor described generically in Applicant’s disclosure (Paragraph 0081: “the Al based learning model (e.g., Al based learning model108) may be trained, by one or more processors (e.g., one or more processor(s)104 of server(s)102 and/or processors of a computer user device, such as a mobile device) with the pixel data of a plurality of training images (e.g., image114) of the scalp or hair regions of respective individuals”). Thus, such an additional element may be considered a generic computer element.
The additional element of a user interface is understood to be merely a component of a generic computer (Paragraph 0089: “…an example user interface 504a as rendered on a display screen500 of a user computing device…”). Alternatively, the user interface is also described as rendered or implementable via a web interface (Paragraph 0090). In either case, Examiner refers to Intellectual Ventures I LLC v. Capital One Bank (USA), N.A., 792 F.3d 1363, 1366, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015) (“An abstract idea does not become nonabstract by limiting the invention to a particular field of use or technological environment, such as the Internet [or] a computer”).
As discussed previously, each dependent claim merely recites steps which further define the abstract idea and data/data-processing steps and contain no additional elements. Examiner notes that the dependent claims recite limitations which are extra-solution or part of the abstract idea itself do not constitute significantly more. See MPEP 2106.05(a):
It is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements. See the discussion of Diamond v. Diehr, 450 U.S. 175, 187 and 191-92, 209 USPQ 1, 10 (1981)) in subsection II, below. In addition, the improvement can be provided by the additional element(s) in combination with the recited judicial exception. See MPEP § 2106.04(d) (discussing Finjan, Inc. v. Blue Coat Sys., Inc., 879 F.3d 1299, 1303-04, 125 USPQ2d 1282, 1285-87 (Fed. Cir. 2018)). Thus, it is important for examiners to analyze the claim as a whole when determining whether the claim provides an improvement to the functioning of computers or an improvement to other technology or technical field.
Like SAP America vs Investpic, LLC (Federal Circuit 2018), it is clear from the claims themselves and the specification that these limitations require no improved computer resources and merely utilize already available computers with their already available basic functions to use as tools in executing the claimed process. Therefore, the claims are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
The recitation of the above-identified additional limitations in the claims amount to mere instructions to implement the abstract idea on a computer. Simply using 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 provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); and TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Moreover, implementing an abstract idea on a generic computer does not add significantly more, similar to how the recitation of the computer in the claim in Alice amounted to mere instructions to apply the abstract idea of intermediated settlement on a generic computer.
For at least the above reasons, the claims are directed to applying an abstract idea on a general purpose computer without (i) improving the performance of the computer itself, or (ii) providing a technical solution to a problem in a technical field. In other words, none of the claims provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that these claims amount to significantly more than the abstract idea itself.
Taking the additional elements individually and in combination, the additional elements do not provide significantly more. Specifically, when viewed individually, the above-identified additional elements in the independent claims do not add significantly more because they are simply an attempt to limit the abstract idea to a particular technological environment (data processing of hair and scalp data). That is, neither the general computer elements nor any other additional element adds meaningful limitations to the abstract idea because these additional elements represent insignificant extra-solution activity. When viewed as a combination, these above-identified additional elements simply instruct the practitioner to implement the claimed functions with well-understood, routine and conventional activity specified at a high level of generality in a particular technological environment. As such, there is no inventive concept sufficient to transform the claimed subject matter into a patent-eligible application. As such, the above-identified additional elements, when viewed as whole, do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself. Thus, the claims merely apply an abstract idea to a computer and do not (i) improve the performance of the computer itself, or (ii) provide a technical solution to a problem in a technical field.
Therefore, none of the claims amounts to significantly more than the abstract idea itself.
Accordingly, the claims are not patent eligible and rejected under 35 U.S.C. 101 as being directed to abstract ideas implemented on a generic computer in view of the Supreme Court Decision in Alice Corporation Pty. Ltd. v. CLS Bank International, et al.
Response to Arguments
Applicant's arguments filed January 22, 2025 have been fully considered but they are not persuasive.
Regarding Applicant’s arguments directed to the Step 2A, Prong One of the USPTO’s 2019 PEG Guidance (Remarks, pages 12-14):
Applicant first refers to the USPTO’s August 2025 Memorandum issued to Technology Centers (TC’s) 2100, 2600, and 3600. The present application is currently examined within Technology Center 3791. While relevant, the issuance of the Memorandum to the listed TC’s address the particulars of artificial intelligence/machine learning (AI/ML) concepts relative to arts examined by such TCs.
Applicant further states that the steps of training an AI model to produce an output are steps which cannot be performed in the human mind. However, Examiner notes that such actions are identified as extra-solution steps of manipulating data in order for the additional element of an AI based learning model to carry out a series of evaluations thereon to arrive at a conclusion. The claim itself requires a “trained” AI based learning model; in other words, the claim does not require steps of training a model, but merely describes the data and calculations used to arrive at a model having certain parameters (i.e., trained). Even so, in the case that such steps are interpreted as mental processes necessary for the construction of the claimed AI based learning model capable of carrying out later claim limitations (e.g., outputting predictions, analyzing user-specific data, and generating a treatment), steps (1) and (2) merely define data which may be observed and/or evaluated, whereby the later claim limitations describing the actions of the AI based learning model are each actions performable in the human mind, but for the recitation of an AI based learning model. The broadest reasonable interpretation of an AI based learning model encompasses a series of evaluations and/or mathematical calculations. The simplest AI based learning model encompasses relatively simple models such as perceptron-based artificial neural networks, K-nearest neighbors, and basic regression models. The evaluations and/or mathematical calculations required by such models and related training algorithms are capable of being performed by the skilled artisan through pen and paper practice. As stated in the rejection, no limitations are provided which preclude the claimed processes from being performed in the mind and/or by pen-and-paper practice, aside from embodying such processes in a computer environment. Applicant’s mere statement that providing data for/ training a model is “fundamentally rooted in AI-related technology” is insufficient to demonstrate that any of the functional limitations claimed could not practically be performed by the human mind. While Applicant points to Example 39 as providing support that the training steps of a neural network do not recite a judicial exception, the scope of Applicant’s claim encompasses far simpler AI based models than the neural network receiving digitally-transformed image data described in Example 39.
Regarding Applicant’s arguments directed to the Step 2A, Prong Two of the USPTO’s 2019 PEG Guidance (Remarks, pages 14-16):
Applicant alleges that Examiner has not addressed the claims as a whole and has selectively picked certain elements to attack. On the contrary, Examiner has addressed each additional element which is not part of the abstract idea or extra-solution activity and is non-selective. See rejection above, particularly detailing each generically claimed additional element directed to either generic computer components or generically recited data-gathering elements. The judicial exception of “analyze…the user-specific data to generate a scalp or hair prediction value corresponding to the scalp or hair region of the user,” “generate, based on the scalp or hair prediction value, a user-specific treatment designed to address at least one feature based on the scalp or hair prediction value of the user's scalp or hair region” are both performed by “by the AI based learning model.” The trained model is used to generally apply the abstract idea without placing any limits on how the trained model functions. These limitations only recite the outcome of functional limitations (i.e., “analyze…,” “generate…”) and do not include details about how the analyzing and generating steps are accomplished. See MPEP 2106.05(f). While Applicant is particular regarding the training data itself, the training method itself as well as the model are left undetailed in the claims, with Applicant persuasively arguing that training and usage of known AI based learning models are both actions well-apprised by those of ordinary skill in the art (Remarks, pages 9-10).
The recitation of using a trained model merely indicates a field of use or technology in which the judicial exception is performed. Although the additional element of using a trained model limits the judicial exceptions of analyzing data and generating certain outputs, this type of limitation only confines the use of the abstract idea to a particular technological environment (i.e., AI based learning models), and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h).
Mere usage of a known technology (i.e., trained models) does not improve the underlying computer device – the computer merely implements the steps required by the model. Furthermore, the “configuration, adjustment, and adaptation of a given machine-learning network architecture” is inherent to how AI based learning models work, and not an improvement which arises from Applicant’s inventive concept. It is clear that, as a whole, the invention is directed to instructions to implement an abstract idea via generically-recited computer elements obtaining data from generically-recited sensors, and performing evaluations embodied by a generically recited and known concept (trained machine learning models) configured with previously obtained data.
Regarding Applicant’s arguments directed to the Step 2B of the USPTO’s 2019 PEG Guidance (Remarks, page 16):
Applicant does not argue specific limitations which are identified by Examiner as well-understood, routine, and conventional. As explained in Step 2A, Prong Two, the additional elements do not provide an inventive concept. An application is a set of computer instructions for carrying out the abstract idea. The processor is a generic computer component amounting to no more than an element with which to apply the judicial exception. The measurement device is nothing more than a generically-recited data-gathering tool. The user interface performs mere extra-solution data output. The AI based learning model encompasses 1) a well-known concept whose training would be well-apprised by the skilled artisan (see Remarks, pages 9-10), and 2) merely limiting the steps of the abstract idea in a particular technological environment. As per MPEP 2106.05: “An inventive concept ‘cannot be furnished by the unpatentable law of nature (or natural phenomenon or abstract idea) itself.’ Genetic Techs. Ltd. v. Merial LLC, 818 F.3d 1369, 1376, 118 USPQ2d 1541, 1546 (Fed. Cir. 2016).” It is clear that none of the additional elements, in combination with the judicial exception recited, achieves a combination which provides a patent eligible inventive concept.
Conclusion
THIS ACTION IS MADE FINAL. 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 JUSTIN XU whose telephone number is (571)272-6617. The examiner can normally be reached Mon-Fri 7:30-5:00.
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/JUSTIN XU/ Examiner, Art Unit 3791