DETAILED ACTION
Notice of Pre-AIA or AIA Status
[1] 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
[2] 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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 16 July 2026 has been entered.
Notice to Applicant
[3] This communication is in response to the Amendment and the Request for Continued Examination (RCE) filed 16 July 2026. It is noted that this application benefits from Foreign Priority to European Patent Application Serial Nos. 22173564.0, 22181608.5, and 22182427.9, filed 16 May 2022, 28 June 2022, and 30 June 2022, respectively. Claims 2-3, 5, and 10 have been cancelled. Claims 1, 6, 11, 13, and 15 have been amended. Claims 1, 4, 6-9, and 11-16 are pending.
Response to Remarks/Amendment
[4] Applicant's remarks filed 16 July 2026 have been fully considered but they are not persuasive. The remarks will be addressed below in the order in which they appear in the noted response.
[i] In response to rejection(s) of claim(s) 1 and 4-16 (now claims 1, 4, 6-9, and 11-16 as presented by amendment) under 35 U.S.C. 101 as being directed to non-statutory subject matter as set forth in the previous Office Action mailed 18 May 2026, Applicant provides the following remarks:
"…It is respectfully submitted the claim is NOT DIRECTED to analyzing perceived emotions
observed in response to a flavor and ranking the relative responses, which can theoretically be
performed by a human mind. Instead, the claim is directed to determining relative ranking of the
ingredients in each composition with respect to the associated emotions. A human mind can
perform recording and analyzing emotional response to a composition as a whole, it is however
impossible to analyze the contribution of individual ingredients within the composition to the
emotional response. Relative ranking of the ingredients within the composition and determining
their impact is not performable in the human mind…"
Applicant further remarks:
“…the claim is directed to analyzing the contribution of individual ingredients within the composition to a certain emotional reaction. Determining such contribution of individual ingredients within the composition cannot be performed by human mental processing. Such analysis requires a trained gradient boosting decision tree device, which is trained to analyze a specific parameter, i.e., the relative ranking of the ingredients within the composition with respect to the associated emotion. The training of the gradient boosting decision tree device requires a specific database to produce a specific analysis. It is not possible, or at least not practical to perform such relative ranking…as defined in amended claim 1, simply cannot be performed with a human mind, even with the aid of a generic computer. The method requires a specialized database and a gradient boosting decision tree device trained on the database to produce a specific analysis. It is not possible, or at least not practical, to perform such relative ranking…”
In response, Examiner respectfully maintains that the claims as presented remain directed to ineligible subject matter. Under Eligibility Step 2A prong 1: (See MPEP 2106.04):
The claim(s), as presented by amendment, remain directed to the abstract idea of receiving and analyzing perceived emotions or sensations observed in response to a flavor or fragrance and ranking or valuing the relative responses, which is reasonably considered to be method of limited to claimed ineligible steps/processes performable by Human Mental Processing (e.g., concepts performed or performable in the human mind including observations, evaluations, judgements, or opinions). In particular, the general subject matter to which the claims are directed illustrates a sequence of actions in which human emotions and perceptions or particular flavor or fragrance components are observed and evaluated, which is an ineligible inventive process limited to claimed human mental observations and evaluations.
With respect to Examiner’s maintained conclusion that the claimed invention is directed to ineligible processes performable by Human Mental Processing, representative claim 1 as presented by amendment recites limitations including:
“…a step of providing…a set of exemplar data, comprising: a plurality of composition digital identifiers each of which being representative of a flavor or fragrance physical composition…a plurality of ingredient digital identifiers each of which being representative of a fragrant or flavor physical ingredient, wherein each one of said compositions is formed by at least two of said fragrant or flavor physical ingredients and a plurality of emotion identifiers each of which being representative of a category of emotion or sensation reaction, among a finite list of emotion or sensation reactions, of a human being to the materialized physical composition digital identifier, wherein each one of said compositions is associated with a perception value with respect to at least one of said emotion or sensation…determine for each one of said composition digital identifiers in said set of exemplar data a relative ranking among the flavor or fragrance physical ingredients of each composition relative to at least one emotion or sensation perceived by human beings exposed to said composition…determining…at least one value representative of a relative ranking of each flavor or fragrance physical ingredient represented by said ingredient digital identifiers in the input relative to at least one emotion or sensation…determining for each flavor or fragrance physical ingredient represented by said ingredient digital identifiers in the input, an impact value representative of an impact of said ingredient on said at least one emotion or sensation reaction…”
Respectfully, absent further clarification of the processing steps executed by the recited “computer interface” or “computing device” operating the “gradient boosting decision tree device” or “neural network device”, one of ordinary skill in the art would readily understand that observing human responses to compositions of flavors or fragrances and quantifying and recording the responses for the purposes of ranking flavors of fragrances with respect to emotional responses and/or perceptions are practicable/performable by employing by the human mental processing (See CyberSource Corp v. Retail Decisions, Inc., 654 F.3d 1366, 1373 (Fed. Cir. 2011) (“a method that can be performed by human thought alone is merely an abstract idea and is not patent eligible under 35 U.S.C 101) or by utilizing a generic computing system as a tool to assist in the performance of the noted calculations and/or observations, determinations, or judgements (see at least MPEP 2106.05(f)).
Applicant remarks:
"…while a general gradient boosting decision tree device might be considered as a generic computing device…training such a device on a specific set of data to determine a specific ranking is not generic…once trained, the model is no longer generic, and using the trained model as specified cannot be compared to using a generic computer. One simply cannot purchase a computer at the local BestBuy store, input a composition of ingredients, and expect to receive a relative ranking of the ingredients within the composition with respect to emotion/s. A generic computer or generic gradient boosting decision tree device is not capable of determining such a relative ranking or the impact of each ingredient within the composition…"
Applicant additionally remarks:
"…Claim 1 now specifically requires providing a database with a specific set of data and training the gradient boosting decision tree device with the data in the database to obtain a specific parameter, i.e., a relative ranking of each ingredient in each composition. Accordingly, the training of the gradient boosting decision tree is no longer limited to merely inputting/providing data to the device and receiving outputs from the trained model. Similarly, the step of determining a relative ranking of the input ingredients requires that the determination be carried out by the trained gradient boosting decision tree device, and this step is no longer limited to inputting/providing data to the device and receiving outputs from the trained model… "
Applicant further remarks:
"… the training step, as claimed, provides specific requirements for the training and is performed on a database having a specifically defined set of data. Thus, the training step, as claimed, cannot be compared to Example 47, claim 2 of the 2024 Guidance… the above claim was found to be ineligible since the claim did not provide any details on what continuous training data includes and that claim does not provide any details about how the trained ANN operates or how the detection is made. This is not the case with the current claim, which requires a database with a specific set of data, including compositions made of ingredients and associated with each composition a perception value with respect to emotion/s. This simply cannot be compared to the very generic term continuous training data the current claim requires training the gradient boosting decision tree device with the data in the database to determine for each composition a relative ranking of the individual ingredients relative to the associated emotion. The present claim specifies how the training is carried out, contrary to the above Example 47…"
Applicant remarks:
"… In Ex Parte Desjardins, Appeal No. 2024-000567 (PTAB September 26, 2025, Appeals Review
Panel Decision), the Appeals Review Panel (ARP) overall credited benefits to technological
improvements of machine learning technology as disclosed in the patent application specification.
Specifically, the ARP determined that the specification identified improvements as to how the
machine learning model itself operates, including training a machine learning model to learn new tasks while protecting knowledge about previous tasks to overcome the problem of "catastrophic forgetting" encountered in continual learning systems… In the instant case, the claim requires a database containing a specific set of data, including compositions made from ingredients and, for each composition, a perception value with respect to emotion(s). The claim also requires training the gradient boosting decision tree device with the data in the database to determine for each one composition a relative ranking of the individual ingredients relative to the associated emotion…”
In response, Examiner respectfully disagrees. With respect to considerations under Eligibility Step 2A prong 2 and Step 2B: (See MPEP 2106.04(d)):
As presented by amendment, additional technical elements of claim 1 that potentially integrate the claimed ineligible subject matter into a practical application of the claimed subject are limited to: “computer interface”, “computing device”, “database”, and “gradient boosting decision tree device”. With respect to these potential additional elements:
(1) The “computing device” and “gradient boosting decision tree device” are identified as engaged in an unspecified, general manner in the performance of each of the recited steps/functions.
(2) The “computer interface” is identified as displaying information and receiving inputs.
(3) The “database” is identified as being provided and having a set of exemplar data
As presented by amendment, claim 1 further includes/specifies that the gradient boosting decision tree device is trained to determine “…for each one of said composition digital identifiers in said set of exemplar data a relative ranking among the flavor or fragrance physical ingredients of each composition relative to at least one emotion or sensation perceived by human beings exposed to said composition…”, being provided with an input of digital identifiers selected from the database and determining relative ranking “…of each flavor or fragrance physical ingredient represented by said ingredient digital identifiers in the input relative to at least one emotion or sensation…”.
While Applicant remarks that the claimed invention is used in the determining the relative ranking of each flavor and is therefore no longer limited to inputting/providing data to the device and receiving outputs from the trained model, Examiner respectfully submits that the step as current constructed are limited to inputting identifiers to a device, training a gradient boosting decision tree model in generalized manner that remains limited to providing training data. With respect to applying or utilizing the trained model, the claims are limited to providing inputs to the trained model and receiving values/rankings from the model. While a trained model is obtained and a device is operated, considered in light of the supportive disclosure, the claimed steps do not include training of a machine learning model or operating a device of model beyond the mere provision of data (e.g., identifiers to the device and model).
With respect to the identification of the “gradient boosting decision tree device” and any potential machine learning processes, Examiner further notes the 2024 Guidance Update on Patent Subject Matter Eligibility, Including Artificial Intelligence (2024 AI SME Update) published in the Federal Register on 17 July 2024. In particular, Examiner respectfully directs Applicant’s attention to Example 47, claim 2. Specifically, the instant recitations of “operating…a trained gradient boosting decision tree” and “operating…a neural network” are analogous to the training of an artificial neural network based on input data and receiving continuous training data of Examiner 47. Reasonably, the training data and feedback data are limited to mere data gathering and generating an output at a high level of generality and, by extension, are reasonably understood to constitute insignificant extra solution activity (See MPEP 2106.05(g)). The recited training process is limited to a recitation of the inputs and outputs to be applied to an undefined training process absent any technical specificity regarding actual training. Accordingly, the recited machine-learning processes and associated training are performable using generic ML training processes, but fail to specify any technical steps in obtaining the results other than to state that the model is trained.
With respect to any similarity between the functionality of the instant claims and the basis for concluding that the technical features/functions presented in Appeals Review Panel decision in Ex Parte Desjardins, Appeal No. 2024-000567 (PTAB September 26, 2025), Examiner notes that basis for identifying an integrating technical element under Step 2 Prong 2 reside in the claimed functions of “…training a machine learning model to learn new tasks while protecting knowledge about previous tasks to overcome the problem of ‘catastrophic forgetting’ encountered in continual learning systems”. While Applicant contends that the output of the relative ranking of flavors of the instant claims as amended mirrors the integrating features of the claims at issue in Ex Parte Desjardins, Examiner respectfully submits that the instant claims are limited to the designated inputs and output of a generic machine learning model, absent any further clarification as to how the recited training and/or use of the model constitutes an improvement to underlying technology akin to the mechanisms overcoming ‘catastrophic forgetting’ of Ex Parte Desjardins.
Each of the above noted limitations states a result (e.g., ingredients and identifiers are inputted and displayed, ingredients are ranking based on observed responses, values of flavor or fragrance ingredients are obtained etc.) as associated with a respective “interface” or “computing device”. Beyond the general statement that the “computing device”, “gradient boosting decision tree device”, and “neural network device” are identified as engaged in an unspecified, general manner in the performance of each of the recited steps/functions, the limitations provide no further clarification with respect to the functions performed by the recited technical elements in producing the claimed result. A recitation of “by a device” or “upon an interface”, absent clarification of particular processing steps executed by the underlying technology to produce the result are reasonably understood to be an equivalent of “apply it”. The identified functions performed by the recited technology are limited to: (1) receiving and sending data via a computer network (e.g., receiving inputs); (2) storing and retrieving information and data from a generic computer memory (e.g., ingredients, response data, and “instructions”); (3) displaying and inputting data on a generic computer display (e.g., flavor or fragrance identifiers and responses); and (4) performing mental observations using the obtaining information/data (e.g., observing human responses to compositions of flavors or fragrances and quantifying and recording the responses) (See MPEP 2106.05(f)).
Accordingly, claim 1 is reasonably understood to be conducting standard, and formally manually performed process of receiving and analyzing perceived emotions or sensations observed in response to a flavor or fragrance and ranking or valuing the relative responses using the generic devices as tools to perform the abstract idea. The identified functions of the recited additional elements reasonably constitute a general linking of the abstract idea to a generic technological environment. The claimed receiving and analyzing perceived emotions or sensations observed in response to a flavor or fragrance and ranking or valuing the relative responses benefits from the inherent efficiencies gained by data transmission, data storage, and information display capacities of generic computing devices, but fails to present an additional element(s) which practical integrates the judicial exception into a practical application of the judicial exception.
[ii] Applicant’s remarks directed to previous rejection(s) of claim(s) 1 and 4-16 (now claims 1, 4, 6-9, and 11-16 as presented by amendment) under 35 U.S.C. 103 as being unpatentable as set forth in the previous Office Action mailed 18 May 2026 have been fully considered and are moot in light of newly added grounds of rejection responsive to the amendments to the subject claims. See revised rejection under 35 U.S.C. 103 presented below.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
[5] The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
With respect to each of the below listed limitations as presented by amendment, the recitation of the phrase “means of” invokes treatment under 35 U.S.C. 112(f) based on the use of the word “means” associated with the recited functional language presented as linked to the recited means. In accordance with treatment under 35 U.S.C. 112(f), the broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification.
As presented by amendment, system claim(s) 15 include(s):
[i] “…a means of inputting, upon a computer interface, at least two flavor or fragrance physical ingredient digital representation identifiers…” (Interpreted as limited by the associated structure, material, or acts provided by the Specification.; page(s) 11, line(s) 13-21, page(s) 29, line(s) 1-8; The means of inputting is understood to constitute the acts of manual and automatic input of digital identifiers using keyboard, mouse, touchscreen input devices).
[ii] “…a means for training a gradient boosting decision tree device upon the set of exemplar data to determine for each one of said composition digital identifiers in said set of exemplar data a relative ranking among the flavor or fragrance physical ingredients of each composition relative to at least one emotion or sensation perceived by human beings exposed to said composition…” (Interpreted as limited by the associated structure, material, or acts provided by the Specification.; page(s) 16, line(s) 10-30, page(s) 17, line(s) 1-9; The means for training is understood to constitute the acts performed via input devices and processor to enter identifiers and receive outputs and a trained model).
With respect to each of the below listed limitations as presented by amendment, the recitation of the phrase “step of” invokes treatment under 35 U.S.C. 112(f) based on the use of the word “step” associated with the recited functional language presented as linked to the recited step. In accordance with treatment under 35 U.S.C. 112(f), the broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification. The interpretation of the “step of” limitations is provided in the previous Office Action mailed 18 May 2026, herein incorporated in its entirety.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
[6] Previous rejection(s) of claim 10 under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement is moot as the claim has been cancelled.
[7] Previous rejection(s) of claim 10 under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention is moot as the claim has been cancelled.
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.
[8] Previous rejection(s) of claims 1-15 (now claims 1 and 4-16 as presented by amendment) under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter, specifically an abstract idea without significantly more has/have not been overcome by the amendments to the subject claims and is/are maintained. The statement of rejection below is reiterated as originally presented in the previous Office Action mailed 10 September 2025. The present amendments and remarks are addressed above under “Response to Remarks/Amendment”.
The following analysis is based on the framework for determining patent subject matter eligibility under 35 U.S.C. 101 established in the decisions of the Supreme Court in Mayo Collaborative Services v. Prometheus Labs., Incorporated and Alice Corporation Pty. Ltd. v. CLS Bank International, et al. (See MPEP 2106 subsection III and 2106.03-2106.05) and the 2024 Guidance Update on Patent Subject Matter Eligibility, Including Artificial Intelligence (2024 AI SME Update) published in the Federal Register, 17 July 2024. Claim(s) 1, 4, 6-9, and 11-16 as a whole is/are determined to be directed to an abstract idea. The rationale for this determination is explained below:
Abstract ideas are excluded from patent eligibility based on a concern that monopolization of the basic tools of scientific and technological work might serve to impede, rather than promote, innovation. Still, inventions that integrate the building blocks of human ingenuity into something more by applying the abstract idea in a meaningful way are patent eligible (See MPEP 2106.04).
Consistent with the findings of the Supreme Court in Mayo Collaborative Services v. Prometheus Labs., Incorporated and Alice Corporation Pty. Ltd. v. CLS Bank International, et al. ineligible abstract ideas are defined in groups, namely: (1) Mathematical Concepts (e.g., mathematical relationships, mathematical formulas or equations, and mathematical calculations; (2) Mental Processes (e.g., concepts performed or performable in the human mind including observations, evaluations, judgements, or opinions); and (3) Certain Methods of Organizing Human Activity. Groupings of Certain Methods of Organizing Human Activity include three sub-categories within the group, namely: (1) fundamental economic principles or practices; (2) commercial or legal interactions (e.g., agreements in the form of contracts, legal obligations, advertising, marketing or sales activities or behaviors, and business relations); (3) managing personal behavior or relationships or interactions between people (e.g., social activities, teaching, and following rules or instructions) (See MPEP 2106.04(a).
Eligibility Step 1: Four Categories of Statutory Subject Matter (See MPEP 2106.03): Independent claims 1 and 15 are directed to methods (see interpretation of claim 15 applied above) and are considered be properly directed to one of the four recognized statutory classes of invention designated by 35 U.S.C. 101; namely, a process or method, a machine or apparatus, an article of manufacture, or a composition of matter. While the claims, generally, are directed to recognized statutory classes of invention, each of method/process is subject to additional analysis as defined by the Courts to determine whether the particularly claimed subject matter is patent-eligible with respect to these further requirements. In the case of the instant application, each of claims 1 and 15 are determined to be directed to ineligible subject matter based on the following analysis/guidance:
Eligibility Step 2A prong 1: (See MPEP 2106.04): In reference to claim 1, the claimed invention is directed to non-statutory subject matter because the claim(s) as a whole, considering all claim elements both individually and in combination, do/does not amount to significantly more than an abstract idea. The claim(s) is/are directed to the abstract idea of receiving and analyzing perceived emotions or sensations observed in response to a flavor or fragrance and ranking or valuing the relative responses, which is reasonably considered to be method of limited to claimed ineligible steps/processes performable by Human Mental Processing (e.g., concepts performed or performable in the human mind including observations, evaluations, judgements, or opinions). In particular, the general subject matter to which the claims are directed illustrates a sequence of actions in which human emotions and perceptions or particular flavor or fragrance components are observed and evaluated, which is an ineligible inventive process limited to claimed human mental observations and evaluations.
The courts have previously identified subject matter limited to the implementation of steps/processes performable by Human Mental Processing and/or by a human using pen and paper to be ineligible abstract ideas (See CyberSource Corp v. Retail Decisions, Inc., 654 F.3d 1366, 1373 (Fed. Cir. 2011). Further, mental processes or concepts performed in the human mind including observation and evaluation are considered to be ineligible abstract ideas. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for a recitation of generic computer components, then the claim is still to be grouped as a mental process unless the limitation cannot practically be performed in the human mind (See MPEP 2106.04(a)(2)).
With respect to functions/steps limited to processes performable by Human Mental Processing and/or by a human using pen and paper, representative claim 1 recites:
“…a step of inputting…at least two flavor or fragrance physical ingredient digital representation identifiers, the resulting input corresponding to a physical composition digital identifier representative of a physical composition of physical flavor or fragrance ingredients, a step of …associate, to the input a physical composition digital identifier, at least one value representative of: a relative ranking among the input flavor or fragrance physical ingredient digital representation identifiers relative to at least one determined perceived emotion or sensation, a value representative of the perception, for at least one input flavor or fragrance physical ingredient digital representation identifier, for at least one determined perceived emotion or sensation, and/or a value representative of a class of flavor or fragrance ingredients in a classification of flavor or fragrance ingredients by perception of perceived emotion or sensation for at least one determined emotion or sensation perception and a step of providing…for the input physical composition digital identifier, at least one value obtained during the step of operating.…”
Respectfully, absent further clarification of the processing steps executed by the recited “computer interface” or “computing device” operating instructions (claim 1) and/or the “gradient boosting decision tree device” or “neural network device” (claims 2 and 3 respectively), one of ordinary skill in the art would readily understand that observing human responses to compositions of flavors or fragrances and quantifying and recording the responses for the purposes of ranking flavors of fragrances with respect to emotional responses and/or perceptions are practicable/performable by employing by the human mental processing (See CyberSource Corp v. Retail Decisions, Inc., 654 F.3d 1366, 1373 (Fed. Cir. 2011) (“a method that can be performed by human thought alone is merely an abstract idea and is not patent eligible under 35 U.S.C 101).
The technical elements identified in claim 1 are limited to: “computer interface” and “computing device”. Claims 2 and 3 additionally introduce a “gradient boosting decision tree device” or “neural network device” as engaged in a general manner in the performance of each of the recited observation and evaluations processes. With respect to these potential additional elements:
(1) The “computing device”, “gradient boosting decision tree device”, and “neural network device” are identified as engaged in an unspecified, general manner in the performance of each of the recited steps/functions.
(2) The “computer interface” is identified as displaying information and receiving inputs.
Eligibility Step 2A prong 2: (See MPEP 2106.04(d)): Under step 2A prong two, Examiners are to consider additional elements recited in the claim beyond the judicial exception and evaluate whether those additional elements integrate the exception into a practical application. Further, to be considered a recitation of an element which integrates the judicial exception into a practical application, the additional elements must apply, rely on, or use the judicial exception in a manner that imposes meaningful limits on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the exception.
Additional elements of claim 1 that potentially integrate the claimed ineligible subject matter into a practical application of the claimed subject matter include: “computer interface” and “computing device”. Claims 2 and 3 additionally introduce a “gradient boosting decision tree device” or “neural network device”.
With respect to the above noted functions attributable to the identified additional elements, MPEP 2106.05 stipulates that: 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 – see MPEP 2106.05(f); and/or Generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h) serve as indications that the use of the technology recited does not indicate integration into a practical application of the judicial exception.
With respect to the identification of the “gradient boosting decision tree device” or “neural network device”, Examiner notes the 2024 Guidance Update on Patent Subject Matter Eligibility, Including Artificial Intelligence (2024 AI SME Update) published in the Federal Register on 17 July 2024. In particular, Examiner respectfully directs Applicant’s attention to Example 47, claim 2. Specifically, the instant recitations of “operating…a trained gradient boosting decision tree” and “operating…a neural network” are analogous to the training of an artificial neural network based on input data and receiving continuous training data of Examiner 47. Reasonably, the training data and feedback data are limited to mere data gathering and generating an output at a high level of generality and, by extension, are reasonably understood to constitute insignificant extra solution activity (See MPEP 2106.05(g)). The recited training process is limited to a recitation of the inputs and outputs to be applied to an undefined training process absent any technical specificity regarding actual training. Accordingly, the recited machine-learning processes and associated training are Accordingly, the recited machine-learning processes and associated training are performable using generic ML training processes, but fail to specify any technical steps in obtaining the results other than to state that the model is trained/obtained.
Each of the above noted limitations states a result (e.g., ingredients and identifiers are inputted and displayed, ingredients are ranking based on observed responses, values of flavor or fragrance ingredients are obtained etc.) as associated with a respective “interface” or “computing device”. Beyond the general statement that the “computing device”, “gradient boosting decision tree device”, and “neural network device” are identified as engaged in an unspecified, general manner in the performance of each of the recited steps/functions, the limitations provide no further clarification with respect to the functions performed by the recited technical elements in producing the claimed result. A recitation of “by a device” or “upon an interface”, absent clarification of particular processing steps executed by the underlying technology to produce the result are reasonably understood to be an equivalent of “apply it”. The identified functions performed by the recited technology are limited to: (1) receiving and sending data via a computer network (e.g., receiving inputs); (2) storing and retrieving information and data from a generic computer memory (e.g., ingredients, response data, and “instructions”); (3) displaying and inputting data on a generic computer display (e.g., flavor or fragrance identifiers and responses); and (4) performing mental observations using the obtaining information/data (e.g., observing human responses to compositions of flavors or fragrances and quantifying and recording the responses) (See MPEP 2106.05(f)).
Accordingly, claim 1 is reasonably understood to be conducting standard, and formally manually performed process of receiving and analyzing perceived emotions or sensations observed in response to a flavor or fragrance and ranking or valuing the relative responses using the generic devices as tools to perform the abstract idea. The identified functions of the recited additional elements reasonably constitute a general linking of the abstract idea to a generic technological environment. The claimed receiving and analyzing perceived emotions or sensations observed in response to a flavor or fragrance and ranking or valuing the relative responses benefits from the inherent efficiencies gained by data transmission, data storage, and information display capacities of generic computing devices, but fails to present an additional element(s) which practical integrates the judicial exception into a practical application of the judicial exception.
Eligibility Step 2B: (See MPEP 2106.05): Analysis under step 2B is further subject to the Revised Examination Procedure responsive to the Subject Matter Eligibility Decision in Berkheimer v. HP, Inc. issued by the United States Patent and Trademark Office (19 April 2018). Examiner respectfully submits that the recited uses of the underlying computer technology constitute well-known, routine, and conventional uses of generic computers operating in a network environment. In support of Examiner’s conclusion that the recited functions/role of the computer as presented in the present form of the claims constitutes known and conventional uses of generic computing technology, Examiner provides the following:
In reference to the Specification as originally filed, Examiner notes pages 37 and 38 and Fig. 1. In the noted disclosure, the Specification provides listings of generic computing systems, e.g., a general computing platform including exemplary servers, network configurations and various processor configuration which are identified as capable and interchangeable for performing the disclosed processes. The disclosure does not identify any particular modifications to the underlying hardware elements required to perform the inventive methods and functions. Accordingly, it is reasonably understood that this disclosure indicates that the hardware elements and network configurations suitable for performing the inventive methods are limited to commercially available systems at the time of the invention. Absent further clarification, it is reasonably understood that any modifications/improvements to the underlying technology attributable to the inventive method/system are limited to improvements realized by the disclosed computer-executable routines and the associated processes performed.
While the above noted disclosure serves to provide sufficient explanation of technical elements required to perform the inventive method using available computing technology, the disclosure does not appear to identify any particular modifications or inventive configurations of the underlying hardware elements required to perform the inventive methods and functions. Accordingly, it is reasonably understood that the disclosure indicates that the hardware elements and network configurations suitable for performing the inventive methods are limited to commercially available systems at the time of the invention. Further, absent further clarification, it is reasonably understood that any modifications/improvements to the underlying technology attributable to the inventive method/system are limited to improvements realized by the disclosed computer-executable routines and the associated processes performed.
The claims specify that the above identified generic computing structures and associated functions/routines include:
(1) The “computing device”, “gradient boosting decision tree device”, and “neural network device” are identified as engaged in an unspecified, general manner in the performance of each of the recited steps/functions.
(2) The “computer interface” is identified as displaying information and receiving inputs.
While Examiner acknowledges that the noted limitations are computer-implemented, Examiner respectfully submits that, in aggregate (e.g., “as a whole”) they do not amount to significantly more than the abstract idea/ineligible subject matter to which the claimed invention is primarily directed.
While utilizing a computer, the claimed invention is not rooted in computer technology nor does it improve the performance of the underlying computer technology. The computer-implemented features of the claimed invention noted above are reasonably limited to: (1) receiving and sending data via a computer network (e.g., receiving inputs); (2) storing and retrieving information and data from a generic computer memory (e.g., ingredients, response data, and “instructions”); (3) displaying and inputting data on a generic computer display (e.g., flavor or fragrance identifiers and responses); and (4) performing mental observations using the obtaining information/data (e.g., observing human responses to compositions of flavors or fragrances and quantifying and recording the responses).
The above listed computer-implemented functions are distinguished from the generic data storage, retrieval, transmission, and data manipulation/processing capacities of the generic systems identified in the Specification solely by the recited identification of particular data elements that are of utility to a user performing the specific method of receiving and analyzing perceived emotions or sensations observed in response to a flavor or fragrance and ranking or valuing the relative responses. In summary, the computer of the instant invention is facilitating non-technical aims, i.e., receiving and analyzing perceived emotions or sensations observed in response to a flavor or fragrance and ranking or valuing the relative responses, because it has been programmed to store, retrieve, and transmit specific data elements and/or instructions that is/are of utility to the user. The non-technical functions of receiving and analyzing perceived emotions or sensations observed in response to a flavor or fragrance and ranking or valuing the relative responses benefit from the use of computer technology, but fail to improve the underlying technology.
In support, the courts have previously found that utilization of a computer to receive or transmit data and communications over a network and/or employing generic computer memory and processor capacities store and retrieve information from a computer memory are insufficient computer-implemented functions to establish that an otherwise unpatentable judicial exception (e.g. abstract idea) is patent eligible. With respect to the determinations of the Courts regarding using a computer for sending and receiving data or information over a computer network and storing and retrieving information from computer memory, see at least: receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362; sending messages over a network OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); receiving and sending information over a network buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93 and see performing repetitive calculations, Flook, 437 U.S. at 594, 198 USPQ2d at 199; and Bancorp Services v. Sun Life, 687 F.3d 1266, 1278, 103 USPQ2d 1425, 1433 (Fed. Cir. 2012) with respect to the performance of repetitive calculations does not impose meaningful limits on the scope of the claims.
Independent claim 15 is directed to a second iteration of the inventive method (See interpretation of claim 15 above) and is rejected for substantially the same reasons, in that the generically recited computer components in the apparatus/system and computer readable media claims add nothing of substance to the underlying abstract idea.
Dependent claims 4, 6-9, 11-14, and 16, when analyzed as a whole are held to be ineligible subject matter and are rejected under 35 U.S.C. 101 because the additional recited limitation(s) fail(s) to establish that the claimed invention is not directed to an abstract idea.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
[9] Claim(s) 1, 4, 6-9, and 11-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zahn et al. (United States Patent Application Publication No. 2023/0259363 hereinafter ‘Zahn’) in view of Lelievre et al. (United States Patent Application Publication No. 2021/0193271 hereinafter ‘Lelievre’).
With respect to (currently amended) claim 1, Zahn discloses a method of determination of an emotion or sensation perception in relation to an exposure to a flavor or fragrance ingredients, comprising: a step of providing a database having a set of exemplar data (Zahn et al.; paragraphs [0043][0057]-[0060] [0062]; See at least input training data provided to neural network machine learning training process/device. See further database including associations among identifiers for components and samples), comprising: a plurality of composition digital identifiers each of which being representative of a flavor or fragrance physical composition (Zahn et al.; paragraphs [0032] [0057] [0066] [0087]; See at least sample identifiers, component identifiers, and sample attributes as inputs to the sensory perception model. See further inputs for two or more samples/components to be compared for sensory responses), a plurality of ingredient digital identifiers each of which being representative of a fragrant or flavor physical ingredient, wherein each one of said compositions is formed by at least two of said fragrant or flavor physical ingredients (Zahn et al.; paragraphs [0066]-[0067] [0087]; See at least composition identifiers based on sample attributes including mixed ingredients) and a plurality of emotion identifiers each of which being representative of a category of emotion or sensation reaction, among a finite list of emotion or sensation reactions, of a human being to the materialized physical composition digital identifier (Zahn et al.; paragraphs [0068]-[0069] [0082] [0087]; See at least sensory outputs and composition identifiers associated with emotion or sensory identifiers), wherein each one of said compositions is associated with a perception value with respect to at least one of said emotion or sensation (Zahn et al.; paragraphs [0067]-[0068] [0087]; See at least sensory categorizations); training a gradient boosting decision tree device upon the set of exemplar data to determine for each one of said composition digital identifiers in said set of exemplar data a relative ranking among the flavor or fragrance physical ingredients of each composition relative to at least one emotion or sensation perceived by human beings exposed to said composition (Zahn et al.; paragraphs [0058]-[0060] [0068]-[0070] [0103]; See at least neural network trained to provide outputs of comparative scoring, rating, or ranking or samples and sample components in terms of sensory response and predicted sensory response by panelists and model) and a step of providing said gradient boosting decision tree device with an input including at least two ingredient digital identifiers selected from said database, wherein the resulting input corresponding to a physical composition digital identifier representative of a physical composition of physical flavor or fragrance ingredients (Zahn et al.; paragraphs [0058]-[0060] [0062]; See at least input data provided to neural network machine learning training and application/use of the process/device and associated sample and composition testing models),
a step of determining with the trained gradient boosting decision tree device at least one value representative of a relative ranking of each flavor or fragrance physical ingredient represented by said ingredient digital identifiers in the input relative to at least one emotion or sensation (Zahn et al.; paragraphs [0058]-[0060] [0068]-[0070] [0103]; See at least neural network trained to provide outputs of comparative scoring, rating, or ranking or samples and sample components in terms of sensory response and predicted sensory response by panelists and model).
Claim 1 has been further amended to include “…a step of determining for each flavor or fragrance physical ingredient represented by said ingredient digital identifiers in the input, an impact value representative of an impact of said ingredient on said at least one emotion or sensation reaction…”.
With respect to this element, while Zahn discloses process including training and utilizing machine learning models using composition, ingredient/component, and sensory response indicators/identifiers that results in models capable of measuring intensity of contributions of components in a composition relative to other components with respect to a measured sensory response, Zahn fail to expressly state that a relative impact of a component is directly measured relative to the impact of another component.
However, as evidenced by Lelievre, it is well-known in the art apply machine learning processes to determine a relative contribution of individual ingredients to the olfactive response associated with ingredients within a composition (Lelievre et al.; paragraphs [0013]-[0020] [0040]-[0045] [0068] [0130] [0196]; See at least machine learning processes applied to fragrance compositions to derive relative contributions, i.e., impact, of specified ingredients on the olfactive response to the composition. See further listing of ingredients in a ranking of relative contribution of each ingredient).
It would have been obvious to one of ordinary skill in the art at the time the invention was made to have modified the training and utilizing of machine learning models to generate models capable of measuring intensity of contributions of components in a composition relative to other components of Zahn by further including well-known application of machine learning processes to determine a relative contribution of individual ingredients to the olfactive response associated with ingredients within a composition as taught by Lelievre. The instant invention is directed to a system and method of evaluating human responses to flavor and fragrance stimuli. As Zahn disclose the use of training and utilizing of machine learning models to generate models capable of measuring intensity of contributions of components in a composition relative to other components in the context of a system and method for evaluating human responses to flavor and fragrance stimuli and Lelievre similarly discloses the utility of applying machine learning processes to determine a relative contribution of individual ingredients to the olfactive response associated with ingredients within a composition, the teachings are reasonably considered to have been derived from analogous references and applied in the manner disclosed by the respective references. Accordingly, one of ordinary skill in the art would have been motivated to make the noted combination/modification as rationalized by combining prior art elements accordingly to known methods to yield the predictable results of ensuring simplified and accurate separate assessments of contributions of ingredients to a desired olfactory effect for a composition thereby improving the usability an accuracy of developing marketable compositions having the customer response.
Claims 2 and 3 are cancelled.
With respect to claim 4, Zahn discloses a method in which the exemplar data further comprises, associated with at least one physical composition digital identifier, at least one digital identifier representative of: a gender of the human being exposed to the materialized physical composition, a country of origin of the human being exposed to the materialized physical composition (Zahn et al.; paragraphs [0062]; See at least panelist attributes including demographics), a type of use of the materialized physical composition, a composition chemical base used to support the materialized physical composition, and/or a dosage for at least one physical ingredient flavor or fragrance physical ingredient represented by the corresponding digital representation identifier (Zahn et al.; paragraphs [0051]-[0052] [0085]-[0087]; See at least sample composition and mixture including components).
Claim 5 is cancelled.
With respect to claim 6, Zahn discloses a method comprising, downstream of the step of determining a numerical value representative of an emotion or sensation reaction impact, a step of providing at least one alternative flavor or fragrance physical ingredient digital representation identifier for at least one input flavor or fragrance physical ingredient digital representation identifier to form an alternative physical composition digital identifier as function of the value representative of an emotion or sensation reaction impact associated to said input and alternative flavor or fragrance physical ingredient digital representation identifier (Zahn et al.; paragraphs [0067]-[0068] [0099]-[0103]; See at least mixture modeling and lists of sensory outputs including flavor and smell attributes and characterizations. See further scaling or scoring of relative intensities of sensory responses to components also in terms of flavor and smell attributes).
With respect to claim 7, Zahn discloses a method in which the step of providing at least one alternative flavor or fragrance physical ingredient digital representation identifier is configured to further provide at least one value representative of a concentration of at least one said alternative flavor or fragrance physical ingredient digital representation identifier (Zahn et al.; paragraphs [0069] [0076] [0099] [0105]; See at least panelist and model predictions of sensory response and comparative scoring, ratings, and rankings of components and samples. See further data collected using at least component and sample identifiers).
With respect to claim 8, Zahn discloses a method in which the step of providing at least one alternative flavor or fragrance physical ingredient digital representation identifier is configured to further provide a minimum and/or a maximum value representative of a concentration of at least one said alternative flavor or fragrance physical ingredient digital representation identifier (Zahn et al.; paragraphs [0051]-[0052] [0085]-[0087]; See at least sample composition including concentrations and mixture including components).
With respect to claim 9, Zahn discloses a method comprising a step of assembling a physical composition corresponding to the input physical composition digital identifier or of providing the input physical composition digital identifier to a system configured to assemble physical compositions (Zahn et al.; paragraphs [0051]-[0052] [0085]-[0087]; See at least sample composition and mixture including components).
Claim 10 is cancelled.
With respect to claim 11, Zahn discloses a method in which the step of assembling a database comprises: a step of exposure at least one human being to a physical composition of flavor or fragrance physical ingredients, a step of measuring the emotion or sensation perception of said at least one human being exposed to said physical composition and a step of recording, in a database, a value representative of the measured perceived emotion or sensation in association to the group of flavor or fragrance physical ingredient digital representation identifiers representative of the physical ingredients used to for the composition used during the step of exposure (Zahn et al.; paragraphs [0069] [0076] [0087] [0099] [0105]; See at least panelist and model predictions of sensory response and comparative scoring, ratings, and rankings of components and samples. See further data collected using at least component and sample identifiers. See further sensory data stored in database).
With respect to claim 12, Zahn discloses a method which comprises a step of substituting an input flavor or fragrance physical ingredient digital representation identifiers by a different and equivalent flavor or fragrance physical ingredient digital representation identifiers, said equivalence being defined in a database of equivalent flavor or fragrance physical ingredient digital representation identifiers (Zahn et al.; paragraphs [0067]-[0068] [0099]-[0103]; See at least mixture modeling and lists of sensory outputs including flavor and smell attributes and characterizations. See further scaling or scoring of relative intensities of sensory responses to components also in terms of flavor and smell attributes).
With respect to claim 13, Zahn discloses a method in which the step of operating comprises: a first step of associating, by a computing device, at least one olfactive or taste descriptor to at least one input flavor or fragrance physical ingredient digital representation identifier and a second step of associating, by a computing device, at least one perceived emotion or sensation as a function of at least one olfactive or taste descriptor associated to at least one input flavor or fragrance physical ingredient digital representation identifier (Zahn et al.; paragraphs [0051]-[0052] [0085]-[0087]; See at least sample composition and mixture including components. See further database).
With respect to claim 14, Zahn discloses a method in which at least one emotion or sensation perception is representative of a perception of health or hygiene benefit associated to the exposition to the physical composition (Zahn et al.; paragraphs [0067]-[0068] [0099]-[0103]; See at least descriptors and scaling or scoring of relative intensities of sensory responses to components also in terms of flavor and smell attributes. At least a perception of “salty” can be considered a health-related descriptor).
With respect to claim 16, Zahn discloses a method in which the step of operating is configured to associate, to the input a physical composition digital identifier, at least one value representative of a value representative of the perception, for at least one input flavor or fragrance physical ingredient digital representation identifier, for at least one determined perceived emotion or sensation, and/or a value representative of a class of flavor or fragrance ingredients in a classification of flavor or fragrance ingredients by perception of perceived emotion or sensation for at least one determined emotion or sensation perception (Zahn et al.; paragraphs [0068]-[0070] [0103]; See at least comparative scoring, rating, or ranking or samples and sample components in terms of sensory response and predicted sensory response by panelists and model).
Claims 15, as presented by amendment, substantially repeat subject matter addressed above with respect to amended claim 1 as directed to the enabling system. With respect to these elements, Zahn discloses enabling the disclosed method employing analogous systems and executable instructions (See at least Zahn paragraphs [0051][0059]). Accordingly, claim 15 is rejected under the applied teachings, conclusions obviousness, and rationale to modify as discussed above with respect to claim 1.
Conclusion
[10] The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Cited PATENT Literature:
Smith et al., METHOD FOR ATTRIBUTING OLFACTORY TONALITIES TO OLFACTORY RECEPTOR ACTIVATION AND METHODS FOR IDENTIFYING COMPOUNDS HAVING THE ATTRIBUTED TONALITIES, United States Patent Application Publication No. 2023/0065799, paragraphs [0097]-[0103]: Relevant Teachings: Smith discloses a system/method that includes steps/functions for testing individual fragrances within a test compound including functions of swapping and changing relative concentrations of ingredients within a test compound to determine olfactory changes in perception based on the changed ingredients.
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/ROBERT D RINES/Primary Examiner, Art Unit 3625
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