AIA
Claims 1 3-8 10-22 examined. Claims benefit of provisional 63550435 filed 6 Feb 2024
Canceled 2 9
New 21 22
Amended 1 3 5 6 8 10 11 13 15 17 20
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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.
The claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. The claim(s) is/are directed to one or more abstract idea(s). The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the abstract idea(s).
Step 1: (MPEP 2106.03)
The claims 1-20 and dependents are directed to statutory classes (1 process 8 machine 17 manufacture). The claims herein are directed to subject matter which would be classified under one of the listed statutory classifications (i.e., 2019 Revised Patent Subject Matter Eligibility Guidance (hereinafter “PEG”) “PEG” Step 1=Yes).
Step 2A, Prong One: Evaluating whether the claim(s) recite(s) a judicial exception -- law of nature, natural phenomenon, abstract idea. (MPEP 2106.04).
CLAIM 1
1. A method, comprising:
O receiving a first set of inputs from one or more industry standard organizations, wherein the first set of inputs comprises data relating to life cycle assessment (LCA) of greenhouse gas (GHG) emissions
O using a first large language model (LLM) to generate a canonical mapping structure based on the first set of inputs
O receiving a second set of inputs from one or more industrial organizations, wherein the second set of inputs comprise activity data relating to one or more industrial activities performed by the one or more industrial organizations , wherein generating and presenting the visualization dashboard comprises
O using a second LLM to output a dynamic mapping classifier based on the second set of inputs and the canonical mapping structure generated by the first LLM
, wherein the dynamic mapping classifier is configured to map each of the activity data to a class of a plurality of classes and
O generating and presenting a visualization dashboard of outputs from the dynamic mapping classifier
, wherein generating and presenting the visualization dashboard comprises:
retrieving GHG emission data based on the activity data
determining an amount of GHG emissions for the plurality of classes based on the GHG emission data
determining, based on the amount of GHG emissions for the plurality of classes, a spatial arrangement, a size, or both for a plurality of visualizations corresponding to a respective class of the plurality of classes
generating a breakdown visualization for the plurality of classes based on the determined spatial arrangement, the size, or both.
bold = judicial exception [ apply it ]
CLAIM 1 8 17 – method, machine, manufacture math modeling of emissions from human behavior.
The invention is data gathering, the math, mental steps, organization of human behavior, and a display step. MPEP 2106. The claims takes the idea and simply ‘applies it’.
Collect info, analyze it, display certain results. 101 ineligible. Electric Power Grp (CAFC 2016)(EPG)
Alice clearinghouse via computer
Bilski hedge via computer
Here math, mental steps, organize human behavior via computer
The Claims: rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
The claims recite an idea,
1 Certain Methods of Organizing Human Activity
2 Math
3 Mental Steps.
19046693
19046693
EPG
O receiving a first set of inputs from one or more industry standard organizations, wherein the first set of inputs comprises data relating to life cycle assessment (LCA) of greenhouse gas (GHG) emissions
O using a first large language model (LLM) to generate a canonical mapping structure based on the first set of inputs
O receiving a second set of inputs from one or more industrial organizations, wherein the second set of inputs comprise activity data relating to one or more industrial activities performed by the one or more industrial organizations , wherein generating and presenting the visualization dashboard comprises
O using a second LLM to output a dynamic mapping classifier based on the second set of inputs and the canonical mapping structure generated by the first LLM , wherein the dynamic mapping classifier is configured to map each of the activity data to a class of a plurality of classes and
O generating and presenting a visualization dashboard of outputs from the dynamic mapping classifier , wherein generating and presenting the visualization dashboard comprises:
retrieving GHG emission data based on the activity data
determining an amount of GHG emissions for the plurality of classes based on the GHG emission data
determining, based on the amount of GHG emissions for the plurality of classes, a spatial arrangement, a size, or both for a plurality of visualizations corresponding to a respective class of the plurality of classes
generating a breakdown visualization for the plurality of classes based on the determined spatial arrangement, the size, or both.
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Collect
Info
Analyze
It
Display
certain
results
Step 2A, Prong Two: Identifying whether there are any additional elements recited in the claim beyond the judicial exception(s); and then evaluating those additional elements individually and in combination to determine whether they integrate the exception into a practical application. Prong Two distinguishes claims that are "directed to" the recited judicial exception from claims that are not "directed to" the recited judicial exception. (MPEP 2106.04).
The additional elements are claimed at a high level of generality. Applicant simply computer implements a business process, solving a business problem not a technical problem.
CLAIM 2 (canceled) 9 (canceled) 20
20. determine GHG emissions based on activity data; and wherein the processing system is configured to generate a breakdown visualization dashboard for the plurality of classes based on the amount of GHG emissions.
Examiner
Idea itself
Collect info, analyze it, display certain results. 101 ineligible. Electric Power Grp (CAFC 2016)(EPG)
CLAIM 3
3. The method of claim 2, where generating the breakdown visualization comprises determining relative sizes of the breakdown visualization for the plurality of classes based on the amount of GHG emissions for the plurality of classes.
Examiner
Idea itself
Collect info, analyze it, display certain results. 101 ineligible. Electric Power Grp (CAFC 2016)(EPG)
CLAIM 4
4. The method of claim 1, wherein presenting the visualization dashboard comprises spatially arranging the outputs from the dynamic mapping class based on classes corresponding to the one or more industry standard organizations.
Examiner
Idea itself
Collect info, analyze it, display certain results. 101 ineligible. Electric Power Grp (CAFC 2016)(EPG)
CLAIM 5
5. The method of claim 1, wherein the first set of inputs comprise organization specific information.
Examiner
Idea itself
Collect info, analyze it, display certain results. 101 ineligible. Electric Power Grp (CAFC 2016)(EPG)
CLAIM 6
6. The method of claim 1, wherein the first set of inputs comprise a request for information relating to a product, and wherein the visualization dashboard indicates GHG emissions for a plurality of operations related to the product.
Examiner
Idea itself
Collect info, analyze it, display certain results. 101 ineligible. Electric Power Grp (CAFC 2016)(EPG)
CLAIM 7
7. The method of claim 6, wherein the one or more industry standard organizations indicate the plurality of operations that generate the GHG emissions.
Examiner
Idea itself
Collect info, analyze it, display certain results. 101 ineligible. Electric Power Grp (CAFC 2016)(EPG)
CLAIM 10
10. The system of claim 9, wherein the one or more processors are configured to generate the visualization based on the GHG emission values by:
determining relative sizes of the visualization for the one or more industrial activities based on the GHG emission values; and
generating the visualization based on the relative sizes.
Examiner
Idea itself
Collect info, analyze it, display certain results. 101 ineligible. Electric Power Grp (CAFC 2016)(EPG)
CLAIM 11
11. The system of claim 9, wherein the one or more processors are configured to generate the visualization based on the GHG emission values by: determining an arrangement of the visualization for the one or more industrial activities based on the GHG emission values; and generating the visualization based on the arrangement.
Examiner
Idea itself – math, mental steps, certain methods of organizing human activity
Collect info, analyze it, display certain results. 101 ineligible. Electric Power Grp (CAFC 2016)(EPG)
CLAIM 12
12. The system of claim 8, wherein the visualization dashboard displays a plurality of tornado plots corresponding to the activity data.
Examiner
Idea itself – math, mental steps, certain methods of organizing human activity
Collect info, analyze it, display certain results. 101 ineligible. Electric Power Grp (CAFC 2016)(EPG)
CLAIM 13
13. The system of claim 8, wherein the one or more processors are configured to generate the visualization based on a resolution size of a display that will display the visualization.
Examiner
Idea itself – math, mental steps, certain methods of organizing human activity
Collect info, analyze it, display certain results. 101 ineligible. Electric Power Grp (CAFC 2016)(EPG)
CLAIM 14
14. The system of claim 8, wherein the dynamic mapping classifier is configured to map the activity data to at least one of throughput of a product, transportation information, or financial information.
Examiner
Idea itself – math, mental steps, certain methods of organizing human activity
Collect info, analyze it, display certain results. 101 ineligible. Electric Power Grp (CAFC 2016)(EPG)
CLAIM 15
15. The system of claim 8, wherein the first set of inputs comprise organization specific information.
Examiner
Idea itself – math, mental steps, certain methods of organizing human activity
Collect info, analyze it, display certain results. 101 ineligible. Electric Power Grp (CAFC 2016)(EPG)
CLAIM 16
16. The system of claim 8, wherein the one or more processors are configured to receive the first set of inputs based on a user submitted prompt.
Examiner
Idea itself – math, mental steps, certain methods of organizing human activity
Collect info, analyze it, display certain results. 101 ineligible. Electric Power Grp (CAFC 2016)(EPG)
CLAIM 18
18. The non-transitory computer-readable medium of claim 17, wherein the one or more industry standard organizations comprise ISO 14040 or OPGEE.
Examiner
Idea itself – math, mental steps, certain methods of organizing human activity
Collect info, analyze it, display certain results. 101 ineligible. Electric Power Grp (CAFC 2016)(EPG)
CLAIM 19
19. The non-transitory computer-readable medium of claim 17, wherein the dynamic classifier is configured to categorize the second set of inputs as one industrial activity of the one or more industrial activities.
Examiner
Idea itself – math, mental steps, certain methods of organizing human activity
Collect info, analyze it, display certain results. 101 ineligible. Electric Power Grp (CAFC 2016)(EPG)
CLAIM 21
19. The non-transitory computer-readable medium of claim 8, wherein the spatial arrangement is configured to arrange the plurality of visualizations relatively closer to a center of the visualization board
Examiner
Idea itself – math, mental steps, certain methods of organizing human activity
Collect info, analyze it, display certain results. 101 ineligible. Electric Power Grp (CAFC 2016)(EPG)
CLAIM 22
19. The non-transitory computer-readable medium of claim 1, wherein generating the breakdown visualization comprises demarking double counting associated with the GHG emissions between at least two classes of the plurality of classes.
Examiner
Idea itself – math, mental steps, certain methods of organizing human activity
Collect info, analyze it, display certain results. 101 ineligible. Electric Power Grp (CAFC 2016)(EPG)
The claim says one is to take the idea and “apply it” with generic elements generally applied.
This judicial exception is not integrated into a practical application. In particular, the claim only recites additional elements – e.g. processor 8 medium 17 to perform data gathering -- recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of ranking information based on a determined amount of use) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. MPEP 2106.05 is “iii. Mere automation of manual processes”. See (MPEP 21056.05 “vi. Instructions to display two sets of information on a computer display in a non-interfering manner”).
The claim is also the idea of ensemble learning (1st LLM, 2nd LLM) followed by display (dashboard).
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Step 2B: Identifying whether there are any additional elements (features/limitations/steps) recited in the claim beyond the judicial exception(s), and then evaluating those additional elements individually and in combination to determine whether they contribute an inventive concept (i.e., amount to significantly more than the judicial exception(s)). (MPEP 2106.05)
The claim recites additional elements – e.g. to perform data gathering (MPEP 2106.05 “Adding insignificant extra-solution activity to the judicial exception, e.g., mere data gathering in conjunction with a law of nature or abstract idea such as a step of obtaining information about credit card transactions so that the information can be analyzed ”), MPEP 2106.05 (“iii. Mere automation of manual processes”).
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element e.g. processor 8 medium 17 amounts to no more than mere instructions to apply the exception using a generic computer component. See (MPEP 21056.05 “vi. Instructions to display two sets of information on a computer display in a non-interfering manner”). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim is not patent eligible.
Prior art
The independent claims include
O using a first large language model (LLM) to generate a canonical mapping structure based on the first set of inputs
O receiving a second set of inputs from one or more industrial organizations, wherein the second set of inputs comprise activity data relating to one or more industrial activities performed by the one or more industrial organizations
O using a second LLM to output a dynamic mapping classifier based on the second set of inputs and the canonical mapping structure generated by the first LLM
A
The claimed first LLM and second LLM do appear in the art, but not the prior art.
TnT-LLM: Text Mining at Scale with Large Language Models
https://arxiv.org/abs/2403.12173
shows phase 1 Fig 2 (≈ claimed first LLM) and phase 2 Fig 3 (≈ claimed second LLM)
but the date is 18 March 2024. That date is after the effective date of this application.
Examiner did find limitations in the art, but not the prior art.
B
Knowledge graph-based mapping and recommendation to automate life cycle assessment - ScienceDirect
https://www.sciencedirect.com/science/article/pii/S1474034624004002
Knowledge graph-based mapping and recommendation to automate life cycle assessment
Advanced Engineering Informatics
Volume 62, Part B,
but the date is October 2024. That date is after the effective date of this application.
LLM is not mentioned but there is a 2 stage approach 3.4 associated with LCA)
Examiner did find limitations in the art, but not the prior art.
Response to Remarks
Applicant amendment and remarks fully considered but not fully persuasive.
As to Applicant remarks
Claims do not recite math
Examiner
The claims’ ensemble learning (first LLM … second LLM) is math plus mere display.
As to Applicant remarks
Claims do not recite mental processes
Examiner
The claims’ ensemble learning (first LLM … second LLM) is mental steps doable with pencil and paper plus mere display.
Examiner rejected based on Certain Methods of Organizing Human Activity.
Applicant didn’t disagree, so for purposes of appeal Applicant agrees with that much of the rejection.
As to Applicant remarks
Claims recite integrate practical application
Examiner
Claim 1 has no processor, no computer and could be done with pencil and paper. It can’t be integrated with additional elements b/c there are none.
The claim says one is to take the idea and “apply it” with generic elements generally applied.
This judicial exception is not integrated into a practical application. In particular, the claim only recites additional elements – e.g. processor 8 medium 17 to perform data gathering -- recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of ranking information based on a determined amount of use) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. MPEP 2106.05 is “iii. Mere automation of manual processes”. See (MPEP 21056.05 “vi. Instructions to display two sets of information on a computer display in a non-interfering manner”).
As to Applicant remarks
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Examiner
To the contrary unfortunately,
1 Applicant persuasively argues that the claim is about a business problem (business to focus) to which Applicant offers a business solution ie Certain Methods of Human Activity.
Even at that, argument calls for
2 speculation (may accelerate) and
3 steps not positively recited (allowing) for
4 mere intended results (to focus).
Collect info, analyze it, display certain results. 101 ineligible. Electric Power Grp (CAFC 2016)(EPG)
As to Applicant remarks
Example 37 remarks p13-14
Examiner
Analogy to 37 is not apt; GUI interaction there is absent here.
As to Applicant remarks
Claims recite an Inventive concept
Examiner
Instead applicant claims an abstract idea and nothing more (claim 1) and in the other independent claims simply implements an idea using a computer as a tool.
Point of Contact
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BREFFNI X BAGGOT whose telephone number is (571)272-7154. The examiner can normally be reached M-F 8a-10a, 12p-6p.
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BREFFNI BAGGOT
Primary Examiner
Art Unit 3621
/BREFFNI BAGGOT/Primary Examiner, Art Unit 3621
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