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 .
Style
In this action unitalicized bold is used for claim language, while italicized bold is used for emphasis.
Information Disclosure Statement
All information disclosure statements were submitted prior to the first action and are incompliance with the provisions of 37 C.F.R. § 1.97. Accordingly, they have been considered. If any references in the IDS were listed in an office action for a related application, any such office action is hereby requested. No related applications have been listed in the IDS.
Applicant Reply
“The claims may be amended by canceling particular claims, by presenting new claims, or by rewriting particular claims as indicated in 37 CFR 1.121(c). The requirements of 37 CFR 1.111(b) must be complied with by pointing out the specific distinctions believed to render the claims patentable over the references in presenting arguments in support of new claims and amendments. . . . The prompt development of a clear issue requires that the replies of the applicant meet the objections to and rejections of the claims. Applicant should also specifically point out the support for any amendments made to the disclosure. See MPEP § 2163.06. . . . An amendment which does not comply with the provisions of 37 CFR 1.121(b), (c), (d), and (h) may be held not fully responsive. See MPEP § 714.” MPEP § 714.02. Generic statements or listing of numerous paragraphs do not “specifically point out the support for” claim amendments. “With respect to newly added or amended claims, applicant should show support in the original disclosure for the new or amended claims. See, e.g., Hyatt v. Dudas, 492 F.3d 1365, 1370, n.4, 83 USPQ2d 1373, 1376, n.4 (Fed. Cir. 2007) (citing MPEP § 2163.04 which provides that a ‘simple statement such as ‘applicant has not pointed out where the new (or amended) claim is supported, nor does there appear to be a written description of the claim limitation ‘___’ in the application as filed’ may be sufficient where the claim is a new or amended claim, the support for the limitation is not apparent, and applicant has not pointed out where the limitation is supported.’)” MPEP § 2163(II)(A).
Non-Obvious Subject Matter under 35 U.S.C. § 103
Claims 1-20 are non-obvious in view of the prior art. This is not an indication of allowable subject matter under any other section.
The following is a list of the closest prior art:
Azer (Not All Claims are Created Equal: Choosing the Right Statistical Approach to Assess Hypotheses; 2020) teaches using graphs to evaluate hypotheses based on natural language. But Azer generally fails to teach the combination of operations including “creating a causality model by: generating a causal relationship model utilizing a plurality of hypotheses and a causal relationship between each of two or more pairs of hypotheses; obtaining pro and con sentiment scores for each hypothesis utilizing a scoring function; assigning the obtained pro and con sentiment scores to each hypothesis in the causal relationship model; and propagating the pro and con sentiment scores from leaf hypotheses to a root hypothesis utilizing axioms for causation types to test the propagating scores for reasonableness; and presenting final pro and con scores representing a prediction of the hypotheses to a user,” as substantially recited in all independent claims.
Baum (2015/0363702) teaches “[0128] The motivation for supporting the axiomatize feature is that users may have irreconcilable differences over the truth of some statements. Axiomatization allows them to define a variable representing the truth of a node, and to rate the rest of the graph under the assumption the axiomatized node is true or TE, and also to work out the rating consequences under the assumption it is false or NOT-TE. . . . [0132] The system may further maintain an additional datum “True” or “False” for each TE C node according to whether its condition would be true under the assumption that all the axiomatized nodes are true or respectively is false under this assumption that all the axiomatized nodes are true. As entries are made and edited in the data structure, the system may update the rating of nodes according to an algorithm. . . . [0343] An edge may be classified as Pro if it is an argument or assumption for a Pro node or if it is a challenge for a Con node. An edge may be classified as Con if it is an argument or assumption for a Con node or a challenge for a Pro node.” Baum ¶¶128, 132, 343. This teaches using trees to determine whether or not statements are true and references a pro and con arguments. But this generally fails to teach the combination of operations including “creating a causality model by: generating a causal relationship model utilizing a plurality of hypotheses and a causal relationship between each of two or more pairs of hypotheses; obtaining pro and con sentiment scores for each hypothesis utilizing a scoring function; assigning the obtained pro and con sentiment scores to each hypothesis in the causal relationship model; and propagating the pro and con sentiment scores from leaf hypotheses to a root hypothesis utilizing axioms for causation types to test the propagating scores for reasonableness; and presenting final pro and con scores representing a prediction of the hypotheses to a user,” as substantially recited in all independent claims.
Frank (2016/0300252) teaches using trees to assign risk, but generally fails to teach the combination of operations including “creating a causality model by: generating a causal relationship model utilizing a plurality of hypotheses and a causal relationship between each of two or more pairs of hypotheses; obtaining pro and con sentiment scores for each hypothesis utilizing a scoring function; assigning the obtained pro and con sentiment scores to each hypothesis in the causal relationship model; and propagating the pro and con sentiment scores from leaf hypotheses to a root hypothesis utilizing axioms for causation types to test the propagating scores for reasonableness; and presenting final pro and con scores representing a prediction of the hypotheses to a user,” as substantially recited in all independent claims.
Textor (Robust causal inference using directed acyclic graphs: the R package ‘dagitty’, 2017) teaches using graphs to evaluate hypotheses. But Textor generally fails to teach the combination of operations including “creating a causality model by: generating a causal relationship model utilizing a plurality of hypotheses and a causal relationship between each of two or more pairs of hypotheses; obtaining pro and con sentiment scores for each hypothesis utilizing a scoring function; assigning the obtained pro and con sentiment scores to each hypothesis in the causal relationship model; and propagating the pro and con sentiment scores from leaf hypotheses to a root hypothesis utilizing axioms for causation types to test the propagating scores for reasonableness; and presenting final pro and con scores representing a prediction of the hypotheses to a user,” as substantially recited in all independent claims.
Cao (A Bottom-Up DAG Structure Extraction Model for Math Word Problems, 2021) teaches using directed acyclic graphs to convert natural language into equations. But Cao generally fails to teach the combination of operations including “creating a causality model by: generating a causal relationship model utilizing a plurality of hypotheses and a causal relationship between each of two or more pairs of hypotheses; obtaining pro and con sentiment scores for each hypothesis utilizing a scoring function; assigning the obtained pro and con sentiment scores to each hypothesis in the causal relationship model; and propagating the pro and con sentiment scores from leaf hypotheses to a root hypothesis utilizing axioms for causation types to test the propagating scores for reasonableness; and presenting final pro and con scores representing a prediction of the hypotheses to a user,” as substantially recited in all independent claims.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) and the claims as a whole, considering all claim elements both individually and in combination, do not amount to significantly more.
Step 1: Is the claim to a process, machine, manufacture, or composition of matter?
All claims are found to be directed to one of the four statutory categories, unless otherwise indicated in this action. With respect to claims 15-20, see Spec. ¶127.
Step 2A Prongs One and Two (Alice Step 1): According to Office guidance, claims that read on math do not recite an abstract idea at step 2A1, when the claims fail to refer to the math by name.1 The MPEP also equates “recit[ing] a judicial exception” with “state[ing]” or “describ[ing]” an abstract idea in the claims.2 Consistent with this guidance, an abstract idea may be first recited in a dependent claim even though the independent claims read on that abstract idea. Claim limitations which recite any of the abstract idea groupings set forth in the manual are found to be directed, as a whole, to an abstract idea unless otherwise indicated.3 The claims do not recite additional elements that integrate the abstract ideas into a practical application.4 To confer patent eligibility to an otherwise abstract idea, claims may recite a specific means or method of solving a specific problem in a technological field.5
Independent Claims:
1. A computer implemented method of hypothesis scoring based on causal relationships, comprising: (The claim as a whole is directed to mental processes. This limitation is merely in instruction to apply abstract ideas recited below using generic computer components.) creating causality model by: (Creating a model is a mental process.) generating a causal relationship model utilizing a plurality of hypotheses and a causal relationship between each of two or more pairs of hypotheses; (This reads on both math and on a mental process. Note that the Specification describes a user carrying out this step. See Spec. ¶24 (emphasis added) (“In one or more embodiments, a user can create a causal relationship model 100 with hypotheses. The causal relationship models can be expressed as directed acyclic graphs (DAGs) consisting of nodes110, with each node 110 associated with one of the hypothesis statements 121, 122, 123, 124, 125, 126, 127, 128, 129 (collectively referred to as "12X"), and edges 130 relating to the causations between hypotheses 12X, where three types of causation are introduced for expressing fine-grain causalities. The user can express causal relationship knowledge in the causal relationship model 100 by using three types of causations. Axioms can be used to formally express the degree of reasonable support for the hypotheses, as related by the three types of causation, where the axioms can be incorporated into the edges 130. External sentiment scores can be constrained to satisfy the axioms.”)) obtaining pro and con sentiment scores for each hypothesis utilizing a scoring function; (This reads on both math, and on a mental process.) assigning the obtained pro and con sentiment scores to each hypothesis in the causal relationship model; and (This reads on both math, and on a mental process.) propagating the pro and con sentiment scores from leaf hypotheses to a root hypothesis utilizing axioms for causation types to test the propagating scores for reasonableness; (This reads on both math, and on a mental process.) and presenting final pro and con scores representing a prediction of the hypotheses to a user. (Outputting of the result of the claimed mental processes is mere extra-solution activity.)
Independent claim 8 is rejected for the reasons given in the rejection of claim 1. The claim also recites “[a] computer system implementing a hypothesis scoring method based on causal relationships, comprising: one or more processors; a display operationally coupled to the one or more processors; and a computer memory operationally coupled to the one or more processors, wherein a hypothesis scoring tool is stored in the computer memory and configured to” carry out the operations recited in claim 1. This is merely an instruction to apply the judicial exception using generic computer components.
Independent claim 15 is rejected for the reasons given in the rejection of claim 1. The claim also recites “[a] computer program product for implementing a hypothesis scoring method based on causal relationships, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions are executable by a processor to cause a computer to” carry out the operations recited in claim 1. This is merely an instruction to apply the judicial exception using generic computer components.
Step 2B (Alice Step 2): The rejected claims do not recite additional elements that amount to significantly more than the judicial exception.
All additional limitations that do not integrate the claimed judicial exception into a practical application also fail to amount to significantly more, for the reasons given at step 2A2. All limitations found to be extra-solution activity at step 2A2 are found to be WURC, including limitations that read on mere data gathering, data storage, and data input/output/transfer. Claims 1, 8, and 15 substantially recite “presenting final pro and con scores representing a prediction of the hypotheses to a user.” Outputting information is WURC as explained in this paragraph. This finding is based on cases which have recognized that generic input-output operations, repetitive processing operations, and storage operations are WURC.6 Other aspects of generic computing have also been found to be WURC.7 Further, the description itself may provide support for a finding that claim elements are WURC. The analysis under § 112(a) as to whether a claim element is “so well-known that it need not be described in detail in the patent specification” is the same as the analysis as to whether the claim element is widely prevalent or in common use.8 Similarly, generic descriptions in the Specification of claimed components and features has been found to support a conclusion that the claimed components were conventional.9 Improvements to the relevant technology may support a finding that the claims include a patent eligible inventive concept. But some mechanism that results in any asserted improvements must be recited in the claim, and the Specification must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing the improvement.10 This applies to the dependent claims below.
Independent Claims:
2. The computer implemented method of claim 1, wherein the causal relationship is a contribution, an implication, or a supervenience that determines a method of propagating the pro and con scores. (This merely limits the way the mental process or math is implemented, but does not recite something other than a mental process or mathematical operation.)
3. The computer implemented method of claim 2, wherein an axiom for each of contribution, implication, and supervenience is applied to the pro and con score for each propagation. (This merely limits the way the mental process or math is implemented, but does not recite something other than a mental process or mathematical operation.)
4. The computer implemented method of claim 3, wherein the causal relationship model includes one or more topic words including a specific name with each of the plurality of hypotheses. (This limits the data used in the mental process, but the claim language merely limits to a field of use.)
5. The computer implemented method of claim 4, wherein pro and con sentiment scores are calculated for each of the plurality of hypotheses both with and without the specific name to produce g-scores and s-scores, and the g-scores and s-scores are merged. (This reads on a mental process, and on a mathematical operation.)
6. The computer implemented method of claim 5, wherein the pro and con sentiment scores are obtained by applying the scoring function to news articles. (Obtaining the pro and con sentiment scores by applying a scoring function to news articles reads on a mental process, and on a mathematical operation. Limiting the data used to news articles merely limits to a data environment associated with a field of use.)
7. The computer implemented method of claim 6, wherein the pro and con sentiment scores are propagated by subtracting the smaller of either the pro or con sentiment score from the larger of the pro or con sentiment score and adding the different to a same pro or con sentiment score of a down-stream hypothesis. (This reads on both a mathematical operation and on a mental process.)
For Rejections of claims 9-14, see rejection of claims 2-7, respectively.
For Rejections of claims 16-20, see rejection of claims 2-6, respectively.
All dependent claims are rejected as containing the material of the claims from which they depend.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-20 are rejected 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. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention.
Generally: separately listed claim elements are construed as distinct components, all claim terms must be given weight, and there is presumed to be a difference in meaning and scope when different words or phrases are used in separate claims. Since different term or phrases are presumed to differ in scope and each term or phrase in the claims must find clear support in the description, a description of a single element in the Specification may fail to support multiple claim terms. “[C]laims must ‘conform to the invention as set forth in the remainder of the specification and the terms and phrases used in the claims must find clear support or antecedent basis in the description so that the meaning of the terms in the claims may be ascertainable by reference to the description.’ 37 C.F.R. § 1.75(d)(1).” Phillips v. AWH Corp., 415 F.3d 1303, 1316 (Fed. Cir. 2005) (as cited in MPEP § 2111). Further, a lack of lack of detail in the Specification describing how a claimed result is achieved can support a finding that the Applicant was not in possession of the claimed invention at the time of filing, notwithstanding verbatim support. “It is not enough that one skilled in the art could write a program to achieve the claimed function because the specification must explain how the inventor intends to achieve the claimed function to satisfy the written description requirement. See, e.g., Vasudevan Software, Inc. v. MicroStrategy, Inc., 782 F.3d 671, 681-683, 114 USPQ2d 1349, 1356, 1357 (Fed. Cir. 2015) (reversing and remanding the district court’s grant of summary judgment of invalidity for lack of adequate written description where there were genuine issues of material fact regarding "whether the specification show[ed] possession by the inventor of how accessing disparate databases is achieved"). If the specification does not provide a disclosure of the computer and algorithm in sufficient detail to demonstrate to one of ordinary skill in the art that the inventor possessed the invention a rejection under 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph, for lack of written description must be made.” MPEP § 2161.01(I). “An original claim may lack written description support when (1) the claim defines the invention in functional language specifying a desired result but the disclosure fails to sufficiently identify how the function is performed or the result is achieved[.] See Ariad Pharms., Inc. v. Eli Lilly & Co., 598 F.3d 1336, 1349-50 (Fed. Cir. 2010) (en banc). The written description requirement is not necessarily met when the claim language appears in ipsis verbis in the specification. ‘Even if a claim is supported by the specification, the language of the specification, to the extent possible, must describe the claimed invention so that one skilled in the art can recognize what is claimed. The appearance of mere indistinct words in a specification or a claim, even an original claim, does not necessarily satisfy that requirement.’” MPEP § 2163.03.
Claims 1, 8, and 15 substantially recite “creating a causality model by: generating a causal relationship model” together with various other operations. The Specification does not support two models used together in this way. The Specification only mentions “a causality model” once. Spec. ¶30. See Spec. ¶¶1-135. Nothing in paragraph 30 provides support for creation of a causality model by generating a separate model and other operations recited in claim 1. Since the rest of the Specification fails to mention the claimed “causal relationship model,” claims reciting the causal relationship model in the claimed combination are not supported by the disclosure.
All dependent claims are rejected as containing the limitations of the claims from which they depend.
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 8-14 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 pre-AIA the applicant regards as the invention.
Claims 1, 8, and 15 substantially recite “creating a causality model by: generating a causal relationship model” together with various other operations. It is not clear whether the “causality model” and the “causal relationship model” refer to distinct models, as would be consistent with separately recited elements in a claim. Alternatively, based on the Specification’s disclosure of one overall model in a given embodiment, the similarly named models could refer to separate operations carried out on a single model. However, if the claim language is as separate operations, it is not clear how “creating” and “generating” are distinguished. A third option is interpreting the claim language as merely being redundant, based on the disclosure. The Specification only mentions “a causality model” in one location, but does not clearly distinguish this model from the “causal relationship model” mentioned numerous times in the Specification. This synonymous usage in the Specification tends to show the terms refer to the same model. There are at least three different, inconsistent but similarly reasonable ways of reading the claim. Therefore the claim scope is indefinite.
Claim 8 recites “A computer system implementing a hypothesis scoring method based on causal relationships, comprising: . . . and configured to create a causality model by: . . . generate[] obtain[] . . . assign[] . . . propagate[] . . . determine[] . . . present[] . . . .” The deletions are noted. However, the claims are indefinite because the verbs at the beginning of each indent in the body of the claim are written in the present instead of present progressive (i.e. “create a causality model by generate” instead of “create a causality model by generating.”) This gives the impression that the operations associated with each of these verbs are not being carried out by the computer system in the preamble. Since it is not clear whether or not the computer system in the preamble must carry out the operations in the body of the claim, the claim scope is indefinite. This also makes it unclear whether the claim mixes statutory categories. (i.e. a system for carrying out a method, and a separate method.) Using the present progressive by adding “ing” in place of the hard brackets above will overcome this rejection.
All dependent claims are rejected as containing the limitations of the claims from which they depend.
Response to Arguments
Applicant's arguments filed 10/16/2025 have been fully considered but they are not persuasive.
Rejections under § 101:
Examiner disagrees with Applicant’s position. However, it must be noted that the Applicant Remarks clearly articulate valid points and are generally very well written. Examiner appreciates the level of clarity.
Applicant finds the claims in SRI International, Inc., v. Cisco Systems, Inc. 930 F.3d 1295 (Fed. Cir. 2017) are similar to the claims in the present application. Based on this position Applicant asserts that the claims under examination are patent eligible. Rem. 14. In SRI, Cisco (“Appellant”) asserted that SRI’s claims were “so general that they encompass steps that ‘people can go through in their heads.’” SRI at 1304. The court disagreed, stating “the human mind is not equipped to detect suspicious activity by using network monitors and analyzing network packets, as recited in the claims.” SRI at 1304. See also Rem. 14. Applicant asserts that the Court was responding to Cisco’s position that “the steps were analogous to a guard who analyze [sic] movements in and out, detect suspicious activity, and draft reports on these incidents.” Rem. 14, apparently citing page 28 of an unpublished document in Westlaw (WL 4392745). Examiner does not have access to Westlaw and therefore cannot rely on this statement by Applicant. If unpublished documents are to be relied upon in support of Applicant arguments, they must be submitted together with the Applicant Remarks. Further, the Court in SRI responded to three separate arguments from Appellant. The argument cited to WL 4392745 is closer to the Court’s characterization of Appellant’s first argument, based on Electric Power. SRI at 1304. In response to that argument, the Court distinguished SRI’s claims based on their inclusion of operations that provided an improvement to the device itself. SRI at 1304 (“Here, the claims actually prevent the normal, expected operation of a conventional computer network. Like the claims in DDR, the claimed technology ‘overrides the routine and conventional sequence of events’ by detecting suspicious network activity, generating reports of suspicious activity, and receiving and integrating the reports using one or more hierarchical monitors.”) The present claims seem closer to Electric Power, using a computer in its ordinary capacity to implement an abstract idea, rather than being directed to an improvement to the device itself. Notably, the Court in SRI did not indicate that a mental process being carried out on a conventional computer are patent eligible, simply because the human mind is not equipped to carry out computer operations.
Applicant states “if a vast majority of the population could only accomplish ‘creating a causality model’ by using a pencil and paper and not in their head, then the fact that pencil and paper make the step doable is not relevant.” Rem. 16. In support of this legal theory, Applicant cites the MPEP. The Manual states, “the use of a physical aid . . . to help perform a mental step . . . does not negate the mental nature of the limitation, but simply accounts for variations in memory capacity from one person to another.” Applicant’s theory is consistent with the direction in the Manual, but the manual does not direct examiners to parse the portion of the population which is capable of carrying out mental operations without a pencil a paper when evaluating a mental process. Under Applicant’s theory, as best understood, some significant portion of the population must be able to implement a claimed set of operations without a pencil and paper if the operations are to read on an abstract idea. It is submitted that the MPEP would state this explicitly if there were any basis for such a legal theory. The MPEP is silent to any such requirement. Since the MPEP fails to site any basis for this language, the basis for this language is not clear. Without a clear direction from the MPEP or any basis that could be used to clarify the language of the Manual, Applicant’s legal theory is based on mere speculation. Applying a legal theory based on speculation would be improper. If Applicant is aware of the case which provides support for this line in the Manual, it may be submitted in support of Applicant’s position. Further, the Remarks do not provide any specific facts or reasoning which would support a determination that only a small part of the population could implement a mental process which reads on the claim language. As evidence that creation of a causality model is beyond the limitations of the human mind, Applicant cites Figure 2 of the Specification. The claims do not recite all of the elements of Figure 2 so, even under Applicant’s theory, the inability to store all the information of figure 2 in one’s mind is irrelevant to the issue of claim eligibility. Further, as Figure 2 demonstrates and Applicant admits, “the use of a physical aid (such as pencil and paper) would make ‘creating a causality model’ doable.” Rem. 16.
Applicant states that the language of paragraph 24 of the Specification has been incorrectly interpreted. In support of this position two quotations are offered. Rem. 17, first paragraph, last three lines. These quotes will be given weight when they are cited.
Applicant states that the claims overcome the technical problem of “making predictions via hypothesis for specific entities without sufficient data.” Rem. 18. Even using Applicant’s characterization, this reads on a mental process. Further, this problem, as characterized in the Remarks, is not technical in nature.
The remarks indicate that the technical solution is to combine various hypotheses by using their relationships to one another to make predictions. This reads on a mental process. As best understood, the technical solution described in the remarks refers to combining two hypotheses to determine the likelihood of an occurrence (e.g. traffic is slow in the snow and traffic is slow during rush hour, so the likelihood of bad traffic on a snowy day at 5PM is very high.) Certainly, one could envision versions of this complex enough to avoid reading on a mental process, but the claims do not currently require this level of complexity. Note also that improvements cannot come from the mere application of a mental process using generic computing technology.
Applicant goes through many of the claim limitations and asserts that the combination provides an improvement to the technology. But the asserted improvements, as best understood, are directed to a better way of making decisions. See Rem. 17-23. An advance in the realm of abstract ideas is ineligible for patenting.
Rejections under § 112:
No specific arguments are offered. The rejection may be overcome as indicated in the rejection above.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PAUL M KNIGHT whose telephone number is (571) 272-8646. The examiner can normally be reached Monday - Friday 9-5 ET.
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PAUL M. KNIGHT
/PAUL M KNIGHT/Examiner, Art Unit 2148
1 This distinction between claims which read on math and claims which recite an abstract idea is based on official USPTO Guidance. The 2019 Subject Matter Eligibility (SME) Examples instructs examiners that a claim reciting “training the neural network” where the background describes training as “using stochastic learning with backpropagation which is a type of machine learning algorithm that uses the gradient of a mathematical loss function to adjust the weights of the network” “does not recite any mathematical relationships, formulas, or calculations.” See 2019 SME Example 39, PP. 8-9 (emphasis added). In this example, the plain meaning of “training the neural network” read in light of the disclosure reads on backpropagation using the gradient of a mathematical loss function. See MPEP § 2111.01. In contrast, the 2024 SME Examples instructs examiners that a claim reciting “training, by the computer, the ANN . . . wherein the selected training algorithm includes a backpropagation algorithm and a gradient descent algorithm” does recite an abstract idea because “[t]he plain meaning of [backpropagation algorithm and gradient descent algorithm] are optimization algorithms, which compute neural network parameters using a series of mathematical calculations.” 2024 PEG Example 47, PP. 4-6. The Memorandum of August 4, 2025; Reminders on evaluating subject matter eligibility of claims under 35 U.S.C. 101, P. 3 also directs examiners that “training the neural network” recited in Example 39 merely “involve[s] . . . mathematical concepts” and contrasts claim 2 of example 47 as “referring to [specific] mathematical calculations by name[.]” (Emphasis added.)
2 “For instance, the claims in Diehr . . . clearly stated a mathematical equation . . . and the claims in Mayo . . . clearly stated laws of nature . . . such that the claims ‘set forth’ an identifiable judicial exception. Alternatively, the claims in Alice Corp. . . . described the concept of intermediated settlement without ever explicitly using the words ‘intermediated’ or ‘settlement.’” MPEP § 2106.04(II)(A).
3 “By grouping the abstract ideas, the examiners’ focus has been shifted from relying on individual cases to generally applying the wide body of case law spanning all technologies and claim types. . . . If the identified limitation(s) falls within at least one of the groupings of abstract ideas, it is reasonable to conclude that the claim recites an abstract idea in Step 2A Prong One.” MPEP § 2106.04(a). See also MPEP 2104(a)(2).
4 Step 2A prongs one and two are evaluated individually, consistent with the framework in the MPEP. Evaluation of relationships between abstract ideas and additional elements in one location promotes clarity of the record.
5 “In short, first the specification should be evaluated to determine if the disclosure provides sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. The specification need not explicitly set forth the improvement, but it must describe the invention such that the improvement would be apparent to one of ordinary skill in the art. Conversely, if the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology. Second, if the specification sets forth an improvement in technology, the claim must be evaluated to ensure that the claim itself reflects the disclosed improvement. That is, the claim includes the components or steps of the invention that provide the improvement described in the specification. . . . It should be noted that while this consideration is often referred to in an abbreviated manner as the ‘improvements consideration,’ the word ‘improvements’ in the context of this consideration is limited to improvements to the functioning of a computer or any other technology/technical field, whether in Step 2A Prong Two or in Step 2B.” MPEP 2106.04(d)(1). See also Koninklijke KPN N.V. v. Gemalto M2M GmbH, 942 F.3d 1143, 1150-1152 (Fed. Cir. 2019).
6 See MPEP § 2106.05(d)(II) listing operations including “receiving or transmitting data,” “storing and retrieving data in memory,” and “performing repetitive calculations” as WURC.
7 “But ‘[f]or the role of a computer in a computer-implemented invention to be deemed meaningful in the context of this analysis, it must involve more than performance of 'well-understood, routine, [and] conventional activities previously known to the industry.’ Content Extraction, 776 F.3d at 1347-48 (quoting Alice, 134 S. Ct at 2359). Here, the server simply receives data, ‘extract[s] classification information . . . from the received data,’ and ‘stor[es] the digital images . . . taking into consideration the classification information.’ See ‘295 patent, col. 10 ll. 1-17 (Claim 17). . . . These steps fall squarely within our precedent finding generic computer components insufficient to add an inventive concept to an otherwise abstract idea. Alice, 134 S. Ct. at 2360 (‘Nearly every computer will include a 'communications controller' and a 'data storage unit' capable of performing the basic calculation, storage, and transmission functions required by the method claims.’); Content Extraction, 776 F.3d at 1345, 1348 (‘storing information’ into memory, and using a computer to ‘translate the shapes on a physical page into typeface characters,’ insufficient confer patent eligibility); Mortg. Grader, 811 F.3d at 1324-25 (generic computer components such as an ‘interface,’ ‘network,’ and ‘database,’ fail to satisfy the inventive concept requirement); Intellectual Ventures I, 792 F.3d at 1368 (a ‘database’ and ‘a communication medium’ ‘are all generic computer elements’); BuySAFE v. Google, Inc., 765 F.3d 1350, 1355 (Fed. Cir. 2014) (‘That a computer receives and sends the information over a network—with no further specification—is not even arguably inventive.’).” TLI Commc'ns LLC v. AV Auto., LLC, 823 F.3d 607, 614 (Fed. Cir. 2016), Emphasis Added.
8 “The analysis as to whether an element (or combination of elements) is widely prevalent or in common use is the same as the analysis under 35 U.S.C. 112(a) as to whether an element is so well-known that it need not be described in detail in the patent specification. See Genetic Techs. Ltd. v. Merial LLC, 818 F.3d 1369, 1377, 118 USPQ2d 1541, 1546 (Fed. Cir. 2016) (supporting the position that amplification was well-understood, routine, conventional for purposes of subject matter eligibility by observing that the patentee expressly argued during prosecution of the application that amplification was a technique readily practiced by those skilled in the art to overcome the rejection of the claim under 35 U.S.C. 112, first paragraph)[.]” MPEP § 2106.05(d)(I).
9 “Similarly, claim elements or combinations of claim elements that are routine, conventional or well-understood cannot transform the claims. (Citing BSG Tech LLC v. BuySeasons, Inc., 899 F.3d 1281, 1290-1291 (Fed. Cir. 2018)). When the patent's specification ‘describes the components and features listed in the claims generically,’ it ‘support[s] the conclusion that these components and features are conventional.’ Weisner v. Google LLC, 51 F.4th 1073, 1083-84 (Fed. Cir. 2022); see also Beteiro, LLC v. DraftKings Inc., 104 F.4th 1350, 1357-58 (Fed. Cir. 2024).” Broadband iTV, Inc. v. Amazon.com, Inc., 113 F.4th 1359 (Fed. Cir. 2024)
10 “If it is asserted that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes, a technical explanation as to how to implement the invention should be present in the specification. That is, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. The specification need not explicitly set forth the improvement, but it must describe the invention such that the improvement would be apparent to one of ordinary skill in the art. Conversely, if the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology.” MPEP § 2106.05(a).