DETAILED ACTION
Remarks
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
The Amendment filed 8/6/25 has been entered. Claims 1-10 and 32 are pending in the application and are under examination.
Claim Rejections - 35 USC § 101
Claims 1-10 and 32 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
STEP 1 = YES: The claimed invention is to a process, and thus fall under one of the four statutory categories (Step 1: YES).
STEP 2A, Prong 1 = YES: The claim(s) recite(s) a series of steps which can be practically performed by one or more humans through mental process (i.e., observation, evaluation, judgement, and/or opinion)(see MPEP § 2106.04(a)(2), subsection III) and/or certain methods of organizing human activity (i.e., managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) (see MPEP § 2106.04(a)(2), subsection II). Moreover, the claims recite steps akin to “collecting information, analyzing it, and displaying certain results of the collection and analysis,” where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind, which the court in Electric Power Group held to recite a mental process. Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016). This includes a series of steps defining a method, comprising:
receiving […] input data including a representation of at least one behavioral pattern (mental observation; interaction between individuals, including social activities and teaching);
correlating […] the at least one behavioral pattern to pattern data associated with a set of detectors from a plurality of detectors (mental evaluation and analysis; SPEC, par. 0012: “detector” can refer to data attributes associated with naturally occurring observable physical entities);
generating a first matrix for a first point in time based on the correlation between the at least one behavioral pattern and the pattern data associated with each detector from the set of detectors, the first matrix including at least the set of detectors (mental evaluation and analysis; SPEC, par. 0012: "matrix" can refer to an astrological chart);
generating a plurality of interactive objects for presentation […], each interactive object from the plurality of interactive objects associated with the set of detectors from the plurality of detectors, the plurality of interactive objects including a first interactive prompt . . . the first interactive prompt includes a speech output (mental evaluation and analysis);
in response to detecting a user interaction with at least one interactive object from the plurality of interactive objects, defining and storing a representation of a relationship between each detector from the set of detectors in the first matrix and the input data (mental evaluation and analysis; interaction between individuals, including social activities and teaching);
receiving feedback … and generated in response to the first interactive prompt (mental observation; interaction between individuals, including social activities and teaching);
generating . . . a second interactive prompt (mental evaluation and analysis);
receiving, from the second compute device, a third interactive prompt included in the plurality of interactive objects (mental observation; interaction between individuals, including social activities and teaching);
transforming the first matrix based on the relationship, to define a transformed matrix (mental evaluation and analysis; SPEC, par. 0012: "Translating a matrix" can refer to transforming an astrological chart of an entity to a modified chart and/or map);
synthesizing the transformed matrix to generate a motif of the at least one behavioral pattern (mental evaluation and analysis; SPEC, par. 0012: “Synthesizing a matrix" can refer to analyzing a matrix to extract information);
causing display of the motif of the at least one behavioral pattern […] (displaying the results of the mental evaluation and analysis; interaction between individuals, including social activities and teaching; SPEC, par. 0012: A "motif' can refer to visual patterns that can be represented as graphical representations);
receiving […] a second input data including a representation of a second at least one behavioral pattern (mental observation; interaction between individuals, including social activities and teaching);
correlating […] the second at least one behavioral pattern to pattern data associated with a second set of detectors from the plurality of detectors (mental evaluation and analysis); and
generating a second matrix for the first point in time based on the correlation between the second at least one behavioral pattern and the pattern data associated with each detector from the second set of detectors, the second matrix including at least the second set of detectors, wherein at least one detector from the first set of detectors is different from at least one detector from the second set of detectors (mental evaluation and analysis);
wherein the correlating the at least one behavioral pattern to the pattern data is based on a spatial position of each detector from the set of detectors at the first point in time (mental evaluation and analysis).
wherein the input data includes at least one of a birth time, a birth date, or a place of birth (mental observation; interaction between individuals, including social activities and teaching);
wherein the input data includes at least one of a birth time, a birth date, and a place of birth (mental observation; interaction between individuals, including social activities and teaching);
wherein the input data is a first input data, the at least one behavioral pattern is a first at least one behavioral pattern, and the set of detectors is a first set of detectors (mental observation; interaction between individuals, including social activities and teaching);
wherein each detector from the set of detectors is associated with a parameter from a plurality of parameters and an area of operation from a plurality of areas of operation, the pattern data being a combined representation of the plurality of parameters and the plurality of areas of operations (mental evaluation and analysis);
wherein the generating the plurality of interactive objects is based at least in part on a plurality of parameters, each parameter from the plurality of parameters being associated with a detector from the set of detectors (mental evaluation and analysis);
wherein translating the first matrix includes replacing at least one detector from the set of detectors in the first matrix with at least a portion of the input data based at least in part on the relationship between each detector from the set of detectors in the first matrix and the input data (mental evaluation and analysis);
wherein the synthesizing the transformed matrix includes determining a degree of interaction between the at least the portion of the input data and at least a further at least a portion of the input data replacing a further at least one detector from the set of detectors in the transformed matrix (mental evaluation and analysis); and
wherein the motif of the at least one behavioral pattern includes a representation of the degree of interaction between at least the portion of the input data and at least the other portion of the input data (mental evaluation and analysis).
The steps identified above are akin to mental processes and/or interactions between individuals, and thus fall within an enumerated category of abstract ideas. Note that even if most humans would use a physical aid (e.g., pen and paper) to help them complete the recited steps above, including collecting information related to behavior patterns, analysis steps of the collected information, and presentation of the results of that analysis to another person, the use of such physical aid does not negate the mental nature of these limitations. Therefore, the claims recite an abstract idea (Step 2A, Prong 1: YES).
STEP 2A, Prong 2 = NO: This judicial exception is not integrated into a practical application.
To the extent the claims recite additional elements related to defining a computer environment to implement the abstract idea above (i.e., defining the abstract idea identified under Prong 1 as performed at a processor of a compute device, via a graphical user interface (GUI) including certain steps being performed via the processor (e.g., field programmable gate array (FPGA); application specific integrated circuit (ASIC); compression processor; or encryption processor) of a compute device (e.g., first compute device or second compute device that is remote to the first compute device)), they are recited at a high level of generality such that they do not amount to a particular machine or technical improvement thereof, nor do they represent an improvement in any other technology. Rather, the generic manner which these additional elements are claimed amount to mere instructions to implement the abstract idea in a computer environment comprising a processor and GUI, i.e., field of use, to perform the steps identified under Prong 1 as an abstract idea, and thus do not integrate the judicial exception into a practical application. Additionally, the recited processor types do not create patent eligibility because they are an existing technology used for their already available basic function, as evidenced by the lack of technical detail defining how they perform the corresponding steps. This is evidenced by the Specification, which discloses alternative embodiments of the processor as either a general-purpose processor or one of the claimed processor types, with no apparent technical improvement for any of the recited types of processors (SPEC, par. 0034). Moreover, neither the claims, nor the specification further define any of these processors by particular structure, configuration, or underlying functionality, but rather merely refers to each by name alone as alternatives to a general-purpose processor. Therefore, these additional elements do not integrate the judicial exception into a practical application.
To the extent the claims recite additional elements related to the use of machine learning to implement the abstract idea above (i.e., generating a trained machine learning model, certain prompts being generated by the trained machine learning model, updating the trained machine learning model based on the user interaction to generate an updated machine learning model, and generating a second interactive prompt via the processor and using the updated machine learning model; storing at least one of the trained machine learning model or the updated machine learning model at a second compute device remote from the first compute device; the updating the trained machine learning model to generate the updated machine learning model further based on the feedback; and wherein the trained machine learning model includes a neural network), the claims are not claiming machine learning itself. Rather, the claims rely on the use of generic machine learning technology in carrying out the claimed method of generating interactive prompts. The machine learning technology described in the application is conventional, as the specification demonstrates. See, e.g., SPEC, par. 0027 (“the prompt generator 218 can include and/or comprise a trained model (e.g., a machine learning model, neural network, stochastic model, probabilistic model, and/or the like)”). Neither the claims, nor the specification further describe the machine learning model with any technical detail, but instead merely refer to it by name (e.g., neural network) in conjunction with a function recited in a result-based manner to be performed. This includes a lack of disclosure defining how the trained machine learning model is generated or updated. Additionally, the claims employ only generic computing machines and processors. See SPEC, par.0034: “The processor can be, for example, a general-purpose processor, Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), a processor board, and/or the like”). Moreover, one of ordinary skill in the art would recognize that iterative training, i.e., updating, a machine learning model is incident to the very nature of machine learning. Instead of disclosing a specific implementation of a solution to a problem in the software arts, the only thing the claims disclose about the use of the machine learning is that machine learning is used in a new environment. This new environment is generating interactive prompts. The broadest reasonable interpretation of an “interactive prompt” includes a question, which as provided under Prong 1, can be practically performed by mental process and interactions between individuals, and thus the machine learning merely serves as a tool to perform an otherwise abstract idea. Therefore, these additional elements do not integrate the judicial exception into a practical application.
To the extent the claims recite additional elements related to a physical component for providing data input and output (i.e., receiving or capturing information identified under Prong 1 as an abstract idea from the second compute device, or via a graphical user interface (GUI), a touchscreen or microphone at a second compute device, or captured via a sensor, and presenting information identified under Prong 1 as an abstract idea via the GUI or via a speaker at a second compute device), the claims do not recite a particular manner of receiving and displaying information via the GUI. Rather, the claimed data input and output via the GUI are recited at a high level of generality without any technical detail defining either a particular GUI nor an improvement in GUI technology. Instead, the GUI is recited as merely performing the result-based function in each instance. Thus, the claimed additional elements defining the data input and output as being via a GUI amounts to insignificant pre-solution data input activity (i.e., receiving input data via the GUI) and insignificant post-solution data output activity (i.e., presenting via the GUI). Therefore, the recitation of receiving and displaying information via a GUI in the claims does not integrate the judicial exception into a practical application. Therefore, these additional elements do not integrate the judicial exception into a practical application.
It should be noted that because the courts have made it clear that mere physicality or tangibility of an additional element or elements is not a relevant consideration in the eligibility analysis, the physical nature of the physical components identified above does not affect this analysis. See MPEP 2106.05(I) for more information on this point, including explanations from judicial decisions including Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 224-26 (2014). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application and the claim is directed to the judicial exception. Therefore, the claims are directed to an abstract idea (Step 2A, Prong 2: YES).
STEP 2B = NO: The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because as provided under Prong 2, the additional elements are recited at a high level of generality, and for the purpose of insignificant pre and post-solution activity. Moreover, the specification of the instant application further demonstrates that the additional elements are recited for their well-understood, routine and conventional functionality, which refers to elements of the computer system in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. § 112(a)(e.g., see par. 0016 disclosing [s]ome non- limiting examples of the smart virtual assistant device 104 include intelligent personal assistants (e.g., Google AssistantTM, Amazon AlexaTM, Amazon EchoTM, SiriTM, Blackberry AssistantTM, etc.), computers (e.g., desktops, personal computers laptops etc.), tablets and e-readers (e.g., Apple iPad®, Samsung Galaxy® Tab, Microsoft Surface®, Amazon Kindle®, etc.), mobile devices and smart phones (e.g., Apple iPhone®, Samsung Galaxy®, Google Pixel®, etc.), etc.; see par. 0027 disclosing the prompt generator 218 can include and/or comprise a trained model (e.g., a machine learning model, neural network, stochastic model, probabilistic model, and/or the like); and par. 0034 disclosing [t]he processor can be, for example, a general-purpose processor, Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), a processor board, and/or the like). The specification does not provide any technical detail regarding these embodiments of the compute device, processors, or machine learning that amounts to a technical improvement based on the high level of generality which they are disclosed. In most, if not all cases, these elements are described by name alone, and thus represent known technology. Moreover, the claims lack any technical detail defining any unconventional arrangement of these elements. Thus, the additional elements defining the field of use as a computer-implemented environment using well-understood, routine, and conventional computer components and trained machine learning model amounts to merely automating a manual process, which the courts have held to be insufficient in showing an improvement in computer-functionality. See Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1055, 123 USPQ2d 1100, 1108-09 (Fed. Cir. 2017); see also LendingTree, LLC v. Zillow, Inc., 656 Fed. App'x 991, 996-97 (Fed. Cir. 2016) (non-precedential). Therefore, the claims are not directed to significantly more than the abstract idea (Step 2B: NO).
Therefore, claims 1-10 and 32 are not directed to patent eligible subject matter.
RESPONSE TO ARGUMENTS
35 USC § 101 – Rejections
Applicant's arguments filed 8/6/25 have been fully considered but they are not persuasive. Applicant arguments amount to conclusory statements with no supporting reasoning, and thus are not persuasive. Accordingly, the rejection is maintained.
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 extension fee 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 James Hull whose telephone number is 571-272-0996. The examiner can normally be reached on Monday-Friday from 8:00am to 5:00pm MST.
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/JAMES B HULL/Primary Examiner, Art Unit 3715