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 .
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.
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.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “computing device...configured to...” in claim 1 and “the method...by a computing device...” in claim 11.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof. See figure 8 and associated paragraphs describing the computing device as including one or more processors for executing instructions stored in a storage device.
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
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected 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.
For example, claim 1 recites:
receive user data;
retrieve an alimentary profile;
determine, a nutrient imbalance in the user utilizing a machine learning module, wherein determining the nutrient imbalance comprises:
receiving user training data correlating user data elements to recommended change elements;
training a machine learning model as a function of the user training data;
outputting a recommended change to user's food supply as a function of the machine learning model; and
present the predicted alimentary element, alternative alimentary element and recommended change to user's food supply via a graphical user interface.
It is unclear whether all, some, or none of the recitations of “user” refer to the same user or to different users. The limitations “the predicted alimentary element,” “alternative alimentary element,” and “recommended change” are also unclear with respect to antecedent basis. Claim 11 is similar to claim 1 and has the same antecedent basis issues.
For example, claim 6 recites: “The apparatus of claim 1, wherein a discovery center experience score is calculated utilizing a machine learning module comprising: training, using the machine learning module using training data and a machine learning algorithm, wherein the machine learning module is configured to input user data and output a discovery center experience score.”
It is unclear whether, the machine learning module recited in claim 6 is the same or different from other recitations of the machine learning module recited in claims 1 and 6. Similar antecedent basis issues also pertain to the limitations “training data,” “user data,” and “a discovery center experience score.
It is further noted that dependent claims are rejected for the same reasons as the independent claims from which they depend. Also, claims 1 and 6 are provided as examples. However, antecedent basis issues are present throughout the claims with there being too many to note individually. For purposes of examination, the claims will be interpreted at a high level, and the rejections provided below are tentative, subject to appropriate correction of the claims.
Claim Rejections - 35 USC § 101 - Alice
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
[CLAIM 1]
An apparatus for predicting alimentary element ordering based on biological extraction, the apparatus comprising: a computing device, wherein the computing device is configured to:
(a) receive user data;
(b) retrieve an alimentary profile;
(c) determine, a nutrient imbalance in the user utilizing a machine learning module, wherein determining the nutrient imbalance comprises: receiving user training data correlating user data elements to recommended change elements; training a machine learning model as a function of the user training data; outputting a recommended change to user's food supply as a function of the machine learning model; and
(d) present the predicted alimentary element, alternative alimentary element and recommended change to user's food supply via a graphical user interface.
Claim interpretation: Under the broadest reasonable interpretation, the terms of the claim are presumed to have their plain meaning consistent with the specification as it would be interpreted by one of ordinary skill in the art. See Manual of Patent Examining Procedure (MPEP) 2111.
Regarding steps (a) and (b), user data and an alimentary profile are retrieved. The claim does not provide any details about the user data and the alimentary profile. User data thus simply refers to data related to a user, and alimentary profile refers to data related to food.
Regarding step (c), a nutrient imbalance in the user is determined using machine learning. A machine learning model is trained using training data associating user data with recommended changes. Output of the machine learning model is a recommended change to a user’s food supply. The claim does not provide any details about the machine learning model, how the training is performed, nor how the output is generated. Thus, the machine learning model is a generic machine learning model that takes user data as input (implied) and outputs a recommended change to the user’s food.
Regarding step (d), a predicted alimentary element, alternative alimentary element, and recommended change to user's food supply via a graphical user interface. This means that at least 2 food items and a recommended change to the user’s food are displayed on a graphical user interface.
Steps (a)-(d) are all recited as being implemented by a computing device (i.e., a computer). The recited computer is recited at a high level of generality, i.e., as generic computer performing generic computer functions.
The broadest reasonable interpretation of claim 1 is a method of determining a nutrient imbalance using a machine learning model trained to take user data as input and output a recommended change to the user’s food. User data and an alimentary profile are retrieved. At least 2 food items and a recommended change to the user’s food are displayed on a graphical user interface.
Step 1: This part of the eligibility analysis evaluates whether the claim falls within any statutory category. See MPEP 2106.03. The claim recites an apparatus. Thus, the claim is to a machine, which is one of the statutory categories of invention. (Step 1: YES, also applicable to claims 2-10).
Step 2A, Prong One: This part of the eligibility analysis evaluates whether the claim recites a judicial exception. As explained in MPEP 2106.04, subsection II, a claim “recites” a judicial exception when the judicial exception is “set forth” or “described” in the claim.
(c) determine, a nutrient imbalance in the user utilizing a machine learning module, wherein determining the nutrient imbalance comprises: receiving user training data correlating user data elements to recommended change elements; training a machine learning model as a function of the user training data; outputting a recommended change to user's food supply as a function of the machine learning model – Step (c) may be practically performed in the human mind using observation, evaluation, judgment, and/or opinion. For example, the determining can be performed mentally (or with the aid of pen and paper) by reviewing (i.e., observing) user data associated with recommended changes, then deciding on a recommended change based on the review. Thus, this limitation falls within the mental processes grouping of abstract ideas. (Step 2A, Prong One: YES).
Step 2A, Prong Two: This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. See MPEP 2106.04(d).
The claim recites additional limitations in steps (a) receive user data; (b) retrieve an alimentary profile; and (d) present the predicted alimentary element, alternative alimentary element and recommended change to user's food supply via a graphical user interface. These limitations are mere data gathering and output recited at a high level of generality, and thus is insignificant extra-solution activity. See MPEP 2106.05(g) (“whether the limitation is significant”). In addition, all uses of the recited judicial exceptions require such data gathering and output, and, as such, these limitations do not impose any meaningful limits on the claim. These limitations amount to necessary data gathering and output. See MPEP 2106.05.
The claim also recites additional limitations in step (c): determine, a nutrient imbalance in the user utilizing a machine learning module, wherein determining the nutrient imbalance comprises: receiving user training data correlating user data elements to recommended change elements; training a machine learning model as a function of the user training data; outputting a recommended change to user's food supply as a function of the machine learning model.
MPEP 2106.05(f) provides the following considerations for determining whether a claim simply recites a judicial exception with the words “apply it” (or an equivalent), such as mere instructions to implement an abstract idea on a computer: (1) whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished; (2) whether the claim invokes computers or other machinery merely as a tool to perform an existing process; and (3) the particularity or generality of the application of the judicial exception.
As explained above, the claim is directed to determining a nutrient imbalance using a machine learning model trained to take user data as input and output a recommended change to the user’s food. User data and an alimentary profile are retrieved. At least 2 food items and a recommended change to the user’s food are displayed on a graphical user interface. Paragraph 3 of applicant’s specification discloses that the problem being addressed is that “individuals may wade through a variety of options that are not beneficial to the user.” Paragraphs 17 and 18 of applicant’s specification discloses a solution the problem. A user is provided with an alternative alimentary element that is more beneficial than a predicted alimentary element, where the user’s alimentary profile is used to indicate which alimentary elements are beneficial and which alimentary elements are harmful to the user’s overall health. The claim does not recite such a solution. Since none of the steps in the claim are directed to a solution to a problem, the claim fails to recite details of how a solution to a problem is accomplished.
The claim also does not provide any details about the machine learning model, how the training is performed, nor how the output is generated. Thus, the machine learning model is a generic machine learning model that takes user data as input and outputs a recommended change to the user’s food. Thus, the additional limitations invoke the machine learning model merely as a tool for making predictions and to generally apply the abstract idea without placing any limits on how they function. Therefore, the additional limitations provide nothing more than mere instructions to implement an abstract idea on a “machine” (i.e., generic computer). See MPEP 2106.05(f).
Further, steps (a)-(d) are recited as being performed by a computing device (i.e., computer). The computer is recited at a high level of generality and used as a tool to perform generic computer functions. See MPEP 2106.05(f). In these limitations, the computer is used to perform an abstract idea, as discussed above in Step 2A, Prong One, such that it amounts to no more than mere instructions to apply the exception using a generic computer. See MPEP 2106.05(f).
Even when viewed in combination, the above-noted additional limitations do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES).
Step 2B: This part of the eligibility analysis evaluates whether the claim as a whole amounts to significantly more than the recited exception i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. See MPEP 2106.05.
As explained with respect to Step 2A, Prong Two, the additional limitations involving the machine learning model in step (c) are at best mere instructions to “apply” the abstract idea, which cannot provide an inventive concept. See MPEP 2106.05(f).
Also, as explained with respect to Step 2A, Prong Two, the additional limitations in steps (a), (b), and (c) were found to be insignificant extra-solution activity because they were determined to be necessary data gathering and output. However, a conclusion that an additional limitation is insignificant extra-solution activity in Step 2A, Prong Two should be re-evaluated in Step 2B. See MPEP 2106.05, subsection I.A. At Step 2B, the evaluation of the insignificant extra-solution activity consideration takes into account whether or not the extra-solution activity is well understood, routine, and conventional in the field. See MPEP 2106.05(g).
Here, the additional limitations are recited at a high level of generality and amount to receiving or transmitting data over a network and is thus well-understood, routine, conventional activity. See MPEP 2106.05(d)(II)(i). See also TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages 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).
Further, as discussed in Step 2A, Prong Two above, the recitation of a computer to perform limitations (a)-(d) amounts to no more than mere instructions to apply the exception using a generic computer component.
Even when considered in combination, the above-noted additional limitations represent mere instructions to implement an abstract idea or other exception on a computer, which do not provide an inventive concept. (Step 2B: NO).
[CLAIMS 2-7]
Step 2A, Prong One: No further abstract ideas recited. (Step 2A, Prong One: YES).
Step 2A, Prong Two: No further additional limitations recited. Claims 2-7 merely describe the content of the received user data recited in claim 1. (Step 2A, Prong Two: NO). (Step 2A: YES).
Step 2B: No further additional limitations recited. (Step 2B: NO).
[CLAIMS 8 and 9]
Step 2A, Prong One: No further abstract ideas recited. (Step 2A, Prong One: YES).
Step 2A, Prong Two: No further additional limitations recited. Claims 8 and 9 merely describe the content of the recommended change recited in claim 1. (Step 2A, Prong Two: NO). (Step 2A: YES).
Step 2B: No further additional limitations recited. (Step 2B: NO).
[CLAIM 10]
Step 2A, Prong One: No further abstract ideas recited. (Step 2A, Prong One: YES).
Step 2A, Prong Two: No further additional limitations recited. Claim 10 merely describes the content of the nutrient imbalance recited in claim 1. (Step 2A, Prong Two: NO). (Step 2A: YES).
Step 2B: No further additional limitations recited. (Step 2B: NO).
[CLAIMS 11-20]
Step 1: The claims recite a method. Thus, the claims are to a process, which is one of the statutory categories of invention. (Step 1: YES).
Step 2A, Prong One: See the analysis provided above for claims 1-10 which are substantially similar.
Step 2A, Prong Two: See the analysis provided above for claims 1-10, which are substantially similar. (Step 2A, Prong Two: NO). (Step 2A: YES).
Step 2B: See the analysis provided above for claims 1-10, which are substantially similar. (Step 2B: NO).
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Avery et al (US Pub. 20210241881).
Referring to claim 1, Avery discloses An apparatus for predicting alimentary element ordering based on biological extraction, the apparatus comprising: a computing device, wherein the computing device is configured to [fig. 6, server 502 comprises processor 612 and memory 620]:
receive user data [pars. 71, 72, 85-90; various user data is collected];
retrieve an alimentary profile [pars. 71, 72, 85-90; the user’s current and past diet parameters are received];
determine, a nutrient imbalance in the user utilizing a machine learning module [, wherein determining the nutrient imbalance comprises: receiving user training data correlating user data elements to recommended change elements; training a machine learning model as a function of the user training data; outputting a recommended change to user's food supply as a function of the machine learning model [pars. 90-92; a nutrition assessment is performed and recommendations are generated for the user using one or more trained machine learning models; the user data is provided as input and one or more changes to the user’s diet are recommended based on changes or lack of changes observed in the user’s health in response to the user’s current diet]; and
present the predicted alimentary element, alternative alimentary element and recommended change to user's food supply via a graphical user interface [par. 92; the recommended changes to the user’s diet are provided to the user via a prepopulated user interface, along with updated and new recipes].
Referring to claim 2, Avery discloses The apparatus of claim 1, wherein the user data comprises a discovery center experience score [nonfunctional descriptive material (see MPEP 2111) – the discovery center score describes the user data, which is received but not used for anything functional].
Referring to claim 3, Avery discloses The apparatus of claim 2, wherein the discovery center experience score comprises information related to user brain health optimization [nonfunctional descriptive material (see MPEP 2111) – the information related to user brain health optimization describes the user data, which is received but not used for anything functional].
Referring to claim 4, Avery discloses The apparatus of claim 3, wherein information related to user brain health optimization comprises a cognitive assessment [nonfunctional descriptive material (see MPEP 2111) – the cognitive assessment describes the user data, which is received but not used for anything functional].
Referring to claim 5, Avery discloses The apparatus of claim 2, wherein the discovery center experience score is a function of at least one discovery center experience of a user [nonfunctional descriptive material (see MPEP 2111) – the discovery center experience describes the user data, which is received but not used for anything functional].
Referring to claim 6, Avery discloses The apparatus of claim 1, wherein a discovery center experience score is calculated utilizing a machine learning module comprising: training, using the machine learning module using training data and a machine learning algorithm, wherein the machine learning module is configured to input user data and output a discovery center experience score [par. 92; note the one or more trained machine learning models; nonfunctional descriptive material (see MPEP 2111) – the discovery center experience score describes the user data, which is received but not used for anything functional].
Referring to claim 7, Avery discloses The apparatus of claim 2, wherein the discovery center experience score is weighed [nonfunctional descriptive material (see MPEP 2111) – the discovery center experience score describes the user data, which is received but not used for anything functional].
Referring to claim 8, Avery discloses The apparatus of claim 1 wherein the recommended change to user's food supply comprises a temporal attribute [nonfunctional descriptive material (see MPEP 2111) – the temporal attribute describes the recommended change, which is presented to the user but not used for anything functional].
Referring to claim 9, Avery discloses The apparatus of claim 8, wherein the temporal attribute comprises an optimal mealtime [nonfunctional descriptive material (see MPEP 2111) – the optimal mealtime describes the recommended change, which is presented to the user but not used for anything functional].
Referring to claim 10, Avery discloses The apparatus of claim 1, wherein the nutrient imbalance comprises a vitamin deficiency [nonfunctional descriptive material (see MPEP 2111) – the vitamin deficiency describes the nutrient imbalance, which is not used for anything functional].
Referring to claim 11, see the rejection for claim 1, which incorporates the claimed method.
Referring to claim 12, see the rejection for claim 2.
Referring to claim 13, see the rejection for claim 3.
Referring to claim 14, see the rejection for claim 4.
Referring to claim 15, see the rejection for claim 5.
Referring to claim 16, see the rejection for claim 6.
Referring to claim 17, see the rejection for claim 7.
Referring to claim 18, see the rejection for claim 8.
Referring to claim 19, see the rejection for claim 9.
Referring to claim 20, see the rejection for claim 10.
Conclusion
The following prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Grimmer et al. (US Pub. 20180240542) discloses food recommendations based on user health data.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GRACE PARK whose telephone number is (571)270-7727. The examiner can normally be reached M-F 8AM-5PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, TAMARA KYLE can be reached at (571)272-4241. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Grace Park/Primary Examiner, Art Unit 2144