DETAILED ACTION
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . The following FINAL office action is in response to Applicant communication filed on 03/26/2026 regarding application 18/234,724. Claims 1, 10 and 19 have been amended. Claims 1-5, 7-14 and 16-20 are currently pending and have been rejected.
Response to Amendments
2. Applicant’s amendment filed on 03/26/2026 necessitated new grounds of rejection in this office action.
Response to 35 U.S.C. § 101 Arguments
3. Applicant’s 35 U.S.C. § 101 arguments, filed with respect to Claims 1-5, 7-14 and 16-20 have been fully considered, but they are found not persuasive (see Applicant Remarks, Pages 13-18, dated 03/26/2026). Examiner respectfully disagrees.
Argument #1:
(A). Applicant argues that Claims 1-5, 7-14 and 16-20 recite additional elements that integrate the judicial exception into a practical application under revised step 2a prong two of the 35 U.S.C. § 101 analysis (see Applicant Remarks, Pages 14-16, dated 03/26/2026). Examiner respectfully disagrees.
Specifically, Applicant argues that the amended claim limitation steps of “the generating of the minimal unsatisfied constraints set includes computing a series of conditional expressions for identifying a feasibility for the satisfying of the resource allocation” & “performing, based on the generated explanation for the infeasibility, an action that facilities the fulfillment of the request in a manner that overcomes the infeasibility” as shown in Independent Claims 1, 10 and 19 recite additional elements that integrate the judicial exception into a practical application under 35 U.S.C. § 101 step 2a prong 2 (see Applicant Remarks, Page 14, dated 03/26/2026). Examiner respectfully disagrees.
In response to Applicant’s remarks here for step 2a prong 2 via the 35 U.S.C. 101 analysis, Examiner notes that determining infeasibility, generating explanations, and revising requests are largely mathematical calculations and methods of organizing human activity (planning, organizing, adjusting data). The claims describe a process of "revising a request to re-specify resource allocation," which is an intellectual task that can be performed by a person (e.g., a human operator adjusting a scheduler) and thus constitutes an abstract mental process rather than a technical mechanism. The core of these claims involves identifying that a "request" is "infeasible" based on "constraints" and generating an explanation, adjusting inputs, and revising the request. This describes a logical process of constraint satisfaction or debugging, which is an abstract, mental, or mathematical process, not a technological improvement to the computer itself.
The steps—such as "generating by the at least one processor," "receiving an input," and "displaying allocation information"—refer to computing processes rather than a specific, unconventional computer architecture or improvement in computer functionality.
Insufficiency of "Iteration": The iterative loop of generating explanations and revising the request, while complex, simply automates a trial-and-error process, which is often considered an abstract mathematical calculation, not a transformation of the computer’s underlying operation.
These claims use functional language ("generating an explanation," "debugging mechanism," "iteratively executing") without specifying how the processor does this. "Generating... an explanation": This is a functional result. Any computer-implemented optimizer (e.g., linear programming solver) provides output indicating why a solution is infeasible (e.g., dual variables, shadow prices). "Debugging mechanism to revise the request": This is generic. It describes an iterative loop of changing inputs to achieve a solvable state, which is a foundational concept in computer science (e.g., automated constraint relaxation). "Third input that relates to an adjustment": This merely describes receiving user input to change parameters.
Moreover, these claims do not improve the speed, efficiency, or operation of the processor, memory, or network. Instead, it uses a generic processor to perform a logical function (debugging a request). The problem being solved (finding feasible resource allocation) is a business or mathematical problem, not a technical computer technology problem (like improving memory allocation speeds or processor architecture). The premise that "computer technology is not able to identify constraints that create an infeasible problem and generate explanations" is incorrect. Operations Research (OR) solvers (such as CPLEX, Gurobi, or open-source alternatives) have for decades identified "Infeasible Solutions," "Irreducible Inconsistent Subsystems (IIS)," and provided "IIS explanations" (diagnostics) to explain why a request is infeasible.
The claimed method represents a "do it on a computer" scenario where an abstract process (identifying logical inconsistencies in constraints) is performed by "at least one processor." The steps constitute functional manipulations of data (infeasibility, constraints, inputs) rather than a technological improvement in the functioning of the computer itself.
The claimed invention for Claims 1, 10 and 19 are interpreted as using a computer to perform resource allocation adjustments, making it patent ineligible under 35 U.S.C. § 101 Step 2A Prong 2 as it does not inherently improve the technical functioning of the computer itself, but rather uses the computer to solve a business optimization problem. Therefore, Claims 1-5, 7-14 and 16-20 do not recite additional elements to integrate the judicial exception into a practical application and are patent ineligible.
Argument #2:
(B). Applicant argues that Claims 1-5, 7-14 and 16-20 “these newly claimed computer and AI-based constraint identifying and infeasibility determining features allow the system to compute expressions for identifying constraints to determine resource allocation feasibility, as well as generate and perform actions to facilitate the fulfillment of a request for a resource allocation. These AI-based features explicitly reduce the number of resources required by the system, thus improving the speed, performance, and efficiency of resource allocation technology” under revised step 2a prong two of the 35 U.S.C. § 101 analysis (see Applicant Remarks, 1st ¶ of Page 15, dated 03/26/2026). Examiner respectfully disagrees.
The core of the claims for Independent Claims 1, 10 and 19—identifying constraints, determining infeasibility, generating an explanation, and revising a request—is an abstract economic or business process of "identifying constraints in a resource allocation," which is a form of organizing human activity or a "mental process" performed by a computer. No Technical Improvement to the Computer Itself: While the claim asserts that AI improves efficiency, the AI is essentially being used as a "generic tool" to perform a known, logical, mathematical analysis (determining feasibility) faster, rather than improving the computer's internal functioning (e.g., changing memory management or processor speed directly). Result-Oriented vs. Specific Technology: The claims describe the result to be achieved (overcoming infeasibility and efficient resource allocation) rather than the specific technical method of doing so. Merely automating a business method with AI is not sufficient to transform the abstract idea into a practical application. Generic AI/Algorithm Usage: The AI-based features are described functionally ("generating," "determining," "performing"). Without detailing the specific unconventional "AI algorithm" (e.g., a novel neural network architecture designed specifically for this hardware constraint), the claim is just "token use of AI" to circumvent a 101 rejection. Step 2A Prong 2 Rejection: The additional elements (using a processor) for Independent Claims 1, 10 and 19 do not integrate the abstract idea into a practical application because they are mere instructions to apply a judicial exception under MPEP § 2106.05 (f) or a limiting field of use in a technology environment under MPEP § 2106.05 (h) for a computing device conducting a simulation or constraint satisfaction problem. Therefore, Claims 1-5, 7-14 and 16-20 do not recite additional elements to integrate the judicial exception into a practical application and are patent ineligible.
Argument #3:
(C). Applicant argues that Claims 1-5, 7-14 and 16-20 “the performance of an action that facilitates the fulfillment of the request in a manner that overcomes the infeasibility, based on the generated explanation for the infeasibility provides an additional step that integrates the claims into a practical application akin to the Supreme Court’s finding in Diamond v. Diehr, 450 U.S. 175, 188 (1981). These claimed features significantly enhance the ability of conventional technology to reduce resources for operation and produce a tangible action to accomplish this resource reduction, thereby improving the underlying performance of the technology and providing an additional step to integrate the claims into a practical application” under revised step 2a prong two of the 35 U.S.C. § 101 analysis (see Applicant Remarks, 1st ¶ of Page 15, dated 03/26/2026). Examiner respectfully disagrees.
While Applicant argues that the claimed "debugging mechanism" and "performance of an action that facilitates the fulfillment of the request" (overcoming infeasibility) provides an additional step that integrates a judicial exception into a practical application similar to Diamond v. Diehr, a counterargument under 35 U.S.C. § 101 Step 2A, Prong 2 (Alice/Mayo Framework) can be made based on the following: Reason #1. Failure to Improve Computer Functionality (Merely "Applying" an Abstract Idea).
The claim limitations of Independent Claims 1, 10 and 19 are directed to an abstract idea—specifically, the mental process of identifying a conflict (infeasibility), determining a solution, and revising a plan. While performed by a computer, the steps do not improve the functioning of the computer itself (e.g., faster processing, better memory management). The "debugging" and "re-specifying" steps described are generic computer functions (receiving input, recalculating, displaying) that are merely used to automate a decision-making process, which does not constitute a technical improvement in computer technology.
Reason #2: Lack of Concrete "Practical Application" (Unlike Diehr). In Diamond v. Diehr, the computer was integrated into a physical, chemical process (curing rubber) to improve a tangible, real-world outcome. The current claims focus on an intangible "request" and "allocation information." The "action that facilitates fulfillment" is a generic instruction to re-allocate, rather than a tangible transformation of matter or a physical, industrial process. The invention lacks a "particular machine" or physical transformation, making it analogous to the "intermediary" function found ineligible in Alice Corp v. CLS Bank. Furthermore, according to MPEP § 2106.04 (d) I: Relevant Considerations for Evaluating Whether Additional Elements Integrate the Judicial Exception into a Practical Application, Examiner cites the following: “It is notable that mere physicality or tangibility of an additional element or elements is not a relevant consideration in Step 2A Prong Two. As the Supreme Court explained in Alice Corp., mere physical or tangible implementation of an exception does not guarantee eligibility. Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 573 U.S. 208, 224, 110 USPQ2d 1976, 1983-84 (2014) ("The fact that a computer ‘necessarily exist[s] in the physical, rather than purely conceptual, realm,’ is beside the point"). See also Genetic Technologies Ltd. v. Merial LLC, 818 F.3d 1369, 1377, 118 USPQ2d 1541, 1547 (Fed. Cir. 2016) (steps of DNA amplification and analysis are not "sufficient" to render claim 1 patent eligible merely because they are physical steps).”
Reason #3: "Insignificant Post-Solution Activity". The generation of an explanation for infeasibility and subsequent revision is described as an iterative process—essentially a "calculate, then readjust" method. According to Diehr, simply reciting a mathematical formula (or logical rule) and adding the words "apply it with a computer" is insufficient. The debugging and revising steps are simply "insignificant post-solution activity" that do not "significantly more" than the underlying abstract algorithm of identifying constraints and recalculating solutions. Additionally, certain/particular claim limitations in Independent Claims 1, 10 and 19 recite steps of “receiving data” when evaluated as additional elements, these activities at most amount to insignificant extra-solution activities (see MPEP § 2106.05 (g)), which have been recognized as Well-Understood, Routine and Conventional (WURC), and thus insufficient to add significantly more to the abstract idea. See MPEP § 2106.05(d) ii - 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 (utilizing an intermediary computer to forward information); 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).
Reason #4: Preemption of Fundamental Economic/Logic Principles. The claimed method is directed to fundamental logical constraints (e.g., supply vs. demand, resource scheduling). Allowing a patent on a broad, automated method of "debugging a request" to "overcome infeasibility" would preempt all uses of computers to automatically adjust resource allocations, restraining the use of a basic tool of modern human ingenuity.
Applicant argues the following points: “These features enhance the ability of conventional technology to reduce resources for operation and produce tangible action to accomplish this resource reduction, thereby improving the underlying performance of the technology and providing an additional step to integrate the claims into a practical application” (see Applicant Remarks, 1st ¶ of Page 15, dated 03/26/2026). Examiner respectfully disagrees.
Examiner responds by stating that these claims involve receiving inputs, generating explanations for infeasibility, adjusting information, and iterative debugging. These steps are characteristic of "methods of organizing human activity" (e.g., managing resource constraints) or "mental processes" (e.g., analyzing why a plan failed). Even if the goal is to reduce resources, the process of debugging a resource request via iterative adjustment is an abstract, intellectual, or administrative process that can be performed mentally or with generic computer tools.
To pass Step 2A Prong Two, a claim must improve the functioning of the computer itself, rather than just using a computer to perform an abstract task. These claims describe a method of debugging a request, but it does not specify how the computer's internal architecture, memory, or processing speed is improved. The "debugging mechanism" is likely a high-level software application (e.g., an optimizer) rather than an improvement to computer technology itself. "Applying" an Abstract Idea on a Generic Computer. Merely implementing an abstract, iterative process on a computer does not make it eligible. The steps—receiving a third input, iterative executing, displaying information—are functional descriptions performed by generic, computing components. The claim does not improve the technology, but rather "applies" an abstract concept (re-specifying resource allocation) using routine computer functions. Failure to Impose a "Meaningful Limit". These claims lack specific, technical constraints that restrict the scope to a concrete application. These claims use broad, functional language ("generating an explanation," "performing a debugging mechanism") that essentially preempts the concept of iterative debugging of resource allocation, without defining the specific technical, non-conventional implementation required to avoid preemption. "Extra-Solution Activity" is Insignificant. Data gathering or displaying information (e.g., "displaying allocation information") is considered "extra-solution activity" that does not transform an abstract idea. The steps of generating an explanation and displaying information are merely outputting the results of the mathematical optimization, which is not enough to constitute a concrete technical solution under 2A Prong Two.
These arguments focus on why Claims 1-5, 7-14 and 16-20, as a whole, is directed to an abstract idea and lacks the required specific improvement to computer technology, thus failing to integrate the idea into a "practical application."
Argument #4:
(D). Applicant argues that Claims 1-5, 7-14 and 16-20 “that the above-described improvements made by these features integrate the claims into a practical application and the 35 U.S.C. § 101 rejection should be withdrawn for reasons similar to those set forth by the Appeals Review Panel (ARP) in its decision on request for rehearing in Ex parte Desjardins et. al. under revised step 2a prong two of the 35 U.S.C. § 101 analysis (see Applicant Remarks, 2nd ¶ of Page 15, dated 03/26/2026). Examiner respectfully disagrees.
While Desjardins provides a stronger path for AI and software patentability, Examiner providing the following counterarguments under 35 U.S.C. § 101 by focusing on the following: Result-Oriented" Language vs. Technical Implementation. The claims are viewed as merely listing desired results (e.g., "generating an explanation," "debugging mechanism") without sufficiently detailing the specific technical steps of how the computer generates the explanation or how the debugging algorithm functions. Examiner notes that these steps are "results-oriented" claims that monopolizes the abstract idea of "solving an infeasible allocation". Examiner contends that the "debugging mechanism" is claimed at a high functional level and does not describe how the revision occurs, making it a "result-based" claim rather than a "technical solution".
Merely Using a Computer as a Tool”: Examiner interprets that these claims simply apply a mathematical algorithm (e.g., optimization/scheduling) on a generic computer to manage data, and that identifying "infeasibility" is simply an abstract "gathering information" step, which is ineligible.
Lack of Explicit Technical Improvement in the Specification. Even if the claims hint at improvement, the specification must explain the technical solution. If the specification does not explicitly teach how the debugging mechanism operates to reduce computation time, improve resource efficiency, or reduce memory footprint, the claims do not meet the "technical solution to a technical problem" requirement under Step 2A, Prong 2. These claims do not show improved "processing speed," "reduced memory usage," or "improved data transmission speed"—the typical metrics for "improvement to computer functionality"—but rather a better business outcome (efficient resource allocation).
Generic Computer" Implementation: Here, Examiner argues that the steps (receiving input, determining, displaying) are conventional computer activities and that the "debugging mechanism" is executed on a generic, computer, failing to provide "something more" to transform the abstract idea. Distinguishing from Desjardins (Catastrophic Forgetting). The Appeals Review Panel (ARP) in Desjardins focused on a very specific technical problem: "catastrophic forgetting" in machine learning. Examiner interprets that the present invention, while involving debugging, does not provide the same level of concrete, structural improvement to a machine learning model's training architecture. Moreover, Desjardins applies to specific, low-level technical improvements in machine learning training (e.g., data structure adjustments), whereas this invention operates at a higher application/scheduling level, which is a common subject for 35 U.S.C. § 101 rejection.
Argument #5:
(E). Applicant argues that Claims 1-5, 7-14 and 16-20 “the panel held that because the claimed system used less storage capacity and enabled a reduction in system complexity, the claims reflected sufficient improvement so as to be integrated into a practical application. See ARP’s decision on request for rehearing in Ex parte Desjardins et. al. (Appeal No. 2024-000567, dated September 26, 2025). Similarly, the instant application uses AI to reduce the number of required resources, ultimately reducing system complexity and improving speed and performance” (see Applicant Remarks, 2nd ¶ of Page 15 and 1st ¶ of Page 16, dated 03/26/2026). Examiner respectfully disagrees.
In response to Applicant’s remarks, Examiner notes that while the application focuses on "generating an explanation for the infeasibility" and "debugging," this is analogous to a human mental process (analyzing why something failed) rather than a technical improvement, despite the AI usage. Counterargument (Desjardins Step 2A Prong 1): Examiner argues that the claims are "directed to" the abstract idea of diagnostic analysis or mathematical optimization, placing the burden on the applicant to prove the claim recites a specific improvement to the machine learning model itself, not just the output.
Reducing System Complexity/Improving Speed" (101 Prong 2). The assertion that AI reduces resources, complexity, and improves performance must be explicitly supported by the claims, not just the description. Under the Desjardins framework, merely claiming "reducing system complexity" or "improving speed" is insufficient if the claim does not recite how the AI accomplishes this technical improvement. If the claim merely uses AI to identify a problem, and a human or generic computer solves it, the ARP may find it does not integrate into a practical application, as the claim lacks a "technical solution to a technical problem"
"Adjusting First/Second Information" (101 Prong 2). The process of "adjusting" constraints in a loop might be viewed as a generic "collecting and analyzing data" step. The panel in Desjardins stressed that the claims must reflect an improvement to the operation of the computer (e.g., more efficient training, less memory usage). Examiner argues that looping through input adjustments is a generic computer function and not a specific, non-obvious, algorithmic improvement to the computer's operation, thus failing the integration test in Prong 2. Even if the AI overcomes an infeasibility (e.g., finding a viable allocation), the Examiner argues that this is an "economic" or "business" optimization rather than a "technical" one. The Desjardins decision specifically distinguished between "training the machine learning model" (patentable) and simply using a model to make a business decision (potentially not patentable). If the "action that facilitates fulfillment" is a business calculation, it may fail under the Desjardins standard.
Argument #6:
(F). Applicant argues that Claims 1-5, 7-14 and 16-20 recite additional elements that amount to significantly more than the recited judicial exceptions under step 2B of the 35 U.S.C. § 101 analysis (see Applicant Remarks, Pages 16-17, dated 03/26/2026). Examiner respectfully disagrees.
In response, Examiner refers Applicant to Examiner’s 35 U.S.C. § 101 analysis section (e.g., Claim Rejections - 35 USC § 101) shown below for step 2a prong 2 and step 2B particularly for Independent Claims 1, 10 and 19. The claims do not recite additional elements that amount to significantly more than the recited judicial exceptions, because they are merely directed to the particulars of the abstract idea and likewise do not add significantly more to the above-identified judicial exceptions. The limitations are directed to limitations referenced in MPEP § 2106.05I.A. that are not enough to qualify as significantly more when recited in these claims with the abstract idea which include: (1) adding the words “apply it” (or an equivalent) with the judicial exception, (2) or mere instructions to implement an abstract idea on a computer by requiring the use of software to tailor information and provide the results to the user on a computer, and (3) generally linking the use of the judicial exception to a particular technological environment or field of use.
Additionally, certain/particular claim limitations in Independent Claims 1, 10 and 19 recite steps of “receiving data” when evaluated as additional elements, these activities at most amount to insignificant extra-solution activities (see MPEP § 2106.05 (g)), which have been recognized as Well-Understood, Routine and Conventional (WURC), and thus insufficient to add significantly more to the abstract idea. See MPEP § 2106.05(d) ii - 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 (utilizing an intermediary computer to forward information); 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).
Moreover, the Federal Circuit’s recent BSG Tech LLC v. Buyseasons Inc. decision (Aug. 15, 2018) a similar argument, noting that: “But the relevant inquiry is not whether the claimed invention as a whole is unconventional or non-routine. At Step two, we “search for an ‘inventive concept’… that is sufficient to ensure that the patent in practice amounts to significantly more than a patent upon the [ineligible concept] itself.” But this simply restates what we have already determined is an abstract idea. At Alice step two, it is irrelevant whether considering historical usage information while inputting data may have been non-routine or unconventional as a factual matter. As a matter of law, narrowing or reformulating an abstract idea does not add “significantly more” to it. See SAP Am., Inc. v. InvestPic, LLC, No. 2017-2081, slip op. at 14 (Fed. Cir. 2018). Therefore, Applicant’s suggestion that a specific limitation (or the claimed invention as a whole) must be shown to be well-understood, routine and conventional to support the conclusion of subject matter ineligibility is not persuasive.
Applicants argue that the claims are patent-eligible under step 2B and contain an inventive concept due to the lack of application of prior art against Appellants’ claims (see Applicant Remarks, Page 17, dated 03/26/2026). Examiner respectively disagrees. Examiner submits that the question of novelty and non-obviousness evidence (application of prior art) is not relevant to the question of determining whether the claims as constructed contain an inventive concept. Lastly, Examiner cites the case of (Two-Way Media v. Comcast, (Fed. Cir. 2017)) and the District Court from this case concluded that “the proffered materials are irrelevant to the § 101 motion for judgment on the pleadings. None of the proffered materials addresses a § 101 challenge to claims of the asserted patents. The novelty and non-obviousness of the claims under §§ 102 and 103 does not bear on whether the claims are directed to patent-eligible subject matter under § 101. . . . Because the proffered materials are irrelevant to the instant§ 101 issue, I have not considered them.” The appeal to Federal Circuit Court affirmed the District Court’s ruling that “eligibility and novelty are separate inquiries.”
Examiner also refers to MPEP § 2106.05 (a): “Relevant Considerations for Evaluating Whether Additional Elements Amount to An Inventive Concept” which notes that “It is notable that mere physicality or tangibility of an additional element or elements is not a relevant consideration in Step 2B. As the Supreme Court explained in Alice Corp., mere physical or tangible implementation of an exception is not in itself an inventive concept and does not guarantee eligibility: The fact that a computer "necessarily exist[s] in the physical, rather than purely conceptual, realm," is beside the point. There is no dispute that a computer is a tangible system (in § 101 terms, a "machine"), or that many computer-implemented claims are formally addressed to patent-eligible subject matter. But if that were the end of the § 101 inquiry, an applicant could claim any principle of the physical or social sciences by reciting a computer system configured to implement the relevant concept. Such a result would make the determination of patent eligibility "depend simply on the draftsman’s art," Flook, supra, at 593, 98 S. Ct. 2522, 57 L. Ed. 2d 451, thereby eviscerating the rule that "‘[l]aws of nature, natural phenomena, and abstract ideas are not patentable,’" Myriad, 133 S. Ct. 1289, 186 L. Ed. 2d 124, 133).”
The claims in this case are distinguishable from Bascom and do not satisfy the Step 2B requirement for an inventive concept. The Federal Circuit in Bascom distinguished claims that are "directed to an abstract idea implemented on generic computer components, without providing a specific technical solution beyond simply using generic computer concepts in a conventional way" (which are ineligible) from those that offer a "specific, discrete implementation of the abstract idea". The current claim limitations—generating an explanation for infeasibility, determining an issue, receiving input, performing a debugging mechanism, and iteratively executing—describe conventional, high-level, and routine data processing steps. These are functional steps that could be performed by any generic computer system, rather than a specific, technical improvement to computer functionality (like the unique, remote filtering arrangement in Bascom).
The Bascom court emphasized that the inventive concept was found in the specific location (remote ISP server) and customizable nature of the filtering, which overcame logistical problems of previous, less-efficient filtering systems. The subject claims recite a general "debugging mechanism" and "iterative execution" without defining a specific, non-conventional arrangement that creates a new technical effect. The claim is essentially "using a computer to analyze, re-analyze, and fix a problem," which is a "generic computer implementation" of the abstract idea of a "logical troubleshooting process," failing to meet the requirement for a "non-conventional" ordering.
The Bascom patent passed 101 because it offered a technological solution to a problem unique to the Internet (namely, preventing "one-size-fits-all" or "hackable" filtering). The instant claims address an abstract logistical issue—resource allocation constraint—rather than a technical problem with the underlying computer hardware or software. The "debugging mechanism" is essentially automating a mental process of checking for errors. Therefore, the combination of steps merely organizes information rather than providing a technical, unconventional solution to a computer-specific problem. The Bascom court noted the order of the specific filtering steps made the claim "more than a drafting effort designed to monopolize the [abstract idea]". The steps described (Detect -> Explain -> Debug -> Repeat) are a conventional, logical flow of any "solver" or "debugger" algorithm. Adding "iterative" functionality or "receiving input" to a generic computer process does not transform that process into an inventive concept merely because it is done in a specific sequence.
The claimed invention is directed to an abstract idea, and the additional elements, both individually and in combination, fail to provide the "significantly more" required by Alice/Mayo Step 2B, as they describe computer tasks performed in a predictable manner. Therefore, Claims 1-5, 7-14 and 16-20 do not recite additional elements that are significantly more than the recited judicial exception and thus are patent ineligible under 35 U.S.C. § 101 step 2B.
Argument #7:
(G). Applicant argues that Claims 1-5, 7-14 and 16-20 do not recite an abstract idea, law of nature of natural phenomenon under revised step 2a prong one of the 35 U.S.C. § 101 analysis (see Applicant Remarks, Bottom of Page 17 and 1st ¶ of Page 18, dated 03/26/2026). Examiner respectfully disagrees.
In response to Applicant’s remarks here, Examiner notes that the claim limitations of Independent Claims 1, 10 and 19 recites "mixed-integer optimization" to "determine a least number of possible conditions," "computing a series of conditional expressions," and "identifying a feasibility for the satisfying of the resource allocation." These steps are fundamental mathematical algorithms and calculations. According to MPEP § 2106.04(a)(2), claims that recite mathematical formulas, equations, or calculations fall within the mathematical concepts grouping. The claims are directed to a mathematical algorithm for solving constraint satisfaction problems (CSPs). The process of determining a "minimal unsatisfied constraints set" by evaluating "conditional expressions" to identify feasibility can be performed in the human mind, or via pen and paper, and thus falls under the "mental processes" grouping.
As recently affirmed in Recentive Analytics, Inc. v. Fox Corp. (Fed. Cir. Apr. 18, 2025), applying generic AI or mathematical models (like optimization algorithms) to a new data environment (like resource allocation) does not make the claim patent-eligible if it lacks a specific, concrete technical improvement to the technology itself. The claim merely uses AI as a tool to solve an abstract, mathematical resource allocation problem, which is a method of organizing human activity or a mathematical exercise.
Here, the claim limitations of Independent Claims 1, 10 and 19 are directed to the abstract idea of optimal constraint satisfaction and feasibility analysis for resource allocation using mathematical optimization as well as analyzing and troubleshooting data, or a method of managing resource allocation/scheduling. The core concept of the claims pertains to analyzing constraints, determining why a goal is infeasible, and iteratively proposing modifications to fix the infeasibility.
The claim elements describe a process of receiving inputs (requests, constraints, preferences), analyzing them using an AI algorithm/mathematical optimization (minimal unsatisfied constraints set), and identifying impossible conditions to determine feasibility.
Certain Method of Organizing Human Activity/Economic Activity: The overall goal is "resource allocation," which is often categorized as a business or organizational method. Managing resource requests, constraints, and preferences to determine feasibility.
Mental Processes: The steps of receiving, analyzing, and determining infeasibility can be performed mentally or with basic logical, data-handling tools, characteristic of a mental process. The steps involve identifying, evaluating, analyzing, and judging the feasibility of a system, which are actions that can be performed in the human mind or by a human using "pen and paper".
Mathematical Concept/Algorithm: The steps heavily rely on "mixed-integer optimization" and computing "conditional expressions" to calculate a "minimal unsatisfied constraints set." This aligns with mathematical concepts, which are abstract ideas. The debugging mechanism and iterative revision involve constraint satisfaction and algorithm-based optimization.
Receiving Data (Steps 1, 2, 3): Receiving inputs is a well-known, conventional, non-technical activity. AI/Optimization Algorithm (Step 4 & 5): Determining a "minimal unsatisfied constraints set" via "mixed-integer optimization" is an algorithmic and mathematical process. While AI is used, it is treated as a "black box" to solve a logical problem rather than to improve the computer's internal functioning, it is considered abstract. Determining Infeasibility (Step 6): Identifying a logical outcome (feasibility) based on the input is the analysis part of the mathematical algorithm. Generating an explanation for infeasibility (Step 8): This step is a high-level, data-analysis act. Without being tied to specific technical implementation (like a debugging system), it could be considered a "mental process" (abstract idea). This acts to analyze constraints, which is generally a mental process or a "method of organizing human activity" (e.g., managing a problem). Determining an issue with the request (Step 9): This acts as "analyzing data" or "identifying a problem," which is a form of an abstract idea. This is often considered an abstract idea ("collecting and analyzing data"). Receiving a third input (Adjustment) (Step 10): Receiving input alone is a conventional step, and thus often considered an abstract concept. Performing a debugging mechanism/Iteratively executing (Step 11): This is a certain method of organizing human activity or alternatively a mental process. Displaying allocation information (Step 12): This is generally considered "gathering and outputting data," which is an abstract idea. This is often treated as insignificant post-solution activity. Performing an action that facilitates the fulfillment of the request (Step 13): This is a certain method of organizing human activity via managing personal behavior (including teachings or following rules or instructions) or mental process via judgment or observations.
While Independent Claims 1, 10 and 19 mention "resource allocation," it does not recite specific hardware components (like a particular processor structure) or a specific improvement to computer functionality (like better memory management) that would integrate the mathematical concept into a practical application, as required by Step 2A, Prong 2. The mere recitation of "at least one processor" does not transform an abstract idea into a patent-eligible invention.
Applicant argues that “no court case or example from the MPEP has been cited to establish that the features recited in amended claims 1, 10 and 19 relate to managing of personal behavior” (see Applicant Remarks, 1st ¶ of Page 18, dated 03/26/2026). Under MPEP § 2106.07 (a) regarding Evidentiary Requirements in Making a 35 U.S.C. 101 Rejection, Examiner cites that “The courts consider the determination of whether a claim is eligible (which involves identifying whether an exception such as an abstract idea is being claimed) to be a question of law. Rapid Litig. Mgmt. v. CellzDirect, 827 F.3d 1042, 1047, 119 USPQ2d 1370, 1372 (Fed. Cir. 2016); OIP Techs. v. Amazon.com, 788 F.3d 1359, 1362, 115 USPQ2d 1090, 1092 (Fed. Cir. 2015); DDR Holdings v. Hotels.com, 773 F.3d 1245, 1255, 113 USPQ2d 1097, 1104 (Fed. Cir. 2014); In re Roslin Institute (Edinburgh), 750 F.3d 1333, 1335, 110 USPQ2d 1668, 1670 (Fed. Cir. 2014); In re Bilski, 545 F.3d 943, 951, 88 USPQ2d 1385, 1388 (Fed. Cir. 2008) (en banc), aff’d by Bilski v. Kappos, 561 U.S. 593, 95 USPQ2d 1001 (2010). Thus, the court does not require "evidence" that a claimed concept is a judicial exception, and generally decides the legal conclusion of eligibility without resolving any factual issues. FairWarning IP, LLC v. Iatric Sys., 839 F.3d 1089, 1097, 120 USPQ2d 1293, 1298 (Fed. Cir. 2016) (citing Genetic Techs. Ltd. v. Merial LLC, 818 F.3d 1369, 1373, 118 USPQ2d 1541, 1544 (Fed. Cir. 2016)); OIP Techs., 788 F.3d at 1362, 115 USPQ2d at 1092; Content Extraction & Transmission LLC v. Wells Fargo Bank, N.A., 776 F.3d 1343, 1349, 113 USPQ2d 1354, 1359 (Fed. Cir. 2014).” When performing the analysis at Step 2A Prong One, it is sufficient for the examiner to provide a reasoned rationale that identifies the judicial exception recited in the claim and explains why it is considered a judicial exception (e.g., that the claim limitation(s) falls within one of the abstract idea groupings). Therefore, there is no requirement for the examiner to rely on evidence, such as publications or an affidavit or declaration under 37 CFR 1.104(d)(2), to find that a claim recites a judicial exception.
Applicant argues that this computer-dependent process is incapable of being practically performed in the human mind as required by MPEP 2106.04 (a) (2) III (A) (see Applicant Remarks, 1st ¶ of Page 18, dated 03/26/2026).
For Independent Claims 1, 10 and 19, the claim limitation step of "receiving... a request for a resource allocation" depicts receiving information and making requests are fundamental administrative tasks and communication steps that can be practically performed in the mind. These are abstract idea under Organizing Human Activity / Mental Process. The step of "receiving... a first input [mandatory constraints] and a second input [non-mandatory preferences]" depicts collecting and organizing rules or preferences for an activity is a basic administrative and data entry task. These are abstract idea under Organizing Human Activity / Mental Process. The step of "determining... a minimal unsatisfied constraints set... [using] mixed-integer optimization" depicts a mixed-integer optimization is a specific mathematical formula/algorithm used for solving optimization problems. This explicitly recites a mathematical concept. The step of "determine a least number of possible conditions... and reduce resource requirements" describes the intended mathematical result or calculation of the optimization algorithm. This is a Mathematical Concept. The step of "identifying... at least one condition that is impossible to satisfy... based on the minimal unsatisfied constraints set" depicts evaluating data to identify a conflict or impossibility is a form of judgment or observation performable in the human mind. This is classified as a Mental Process. The step of "determining... that an infeasibility exists" depicts drawing a conclusion (judgment) from an evaluation is a classic mental process. This is classified as a Mental Process. The step of "generating... an explanation for the infeasibility" depicts creating a human-understandable report or explanation involves cognitive communication and analytical steps. This is classified as a Mental Process. The step of "determining whether an issue exists... based on the generated explanation" depicts a final evaluative judgment based on previously processed information, a quintessential mental process.
Examiner refers Applicant to MPEP § 2106.04 III (B), which states that: “If a claim recites a limitation that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper, the limitation falls within the mental processes grouping, and the claim recites an abstract idea. See, e.g., Benson, 409 U.S. at 67, 65, 175 USPQ at 674-75, 674 (noting that the claimed "conversion of [binary-coded decimal] numerals to pure binary numerals can be done mentally," i.e., "as a person would do it by head and hand."); Synopsys, 839 F.3d at 1139, 120 USPQ2d at 1474 (holding that claims to the mental process of "translating a functional description of a logic circuit into a hardware component description of the logic circuit" are directed to an abstract idea, because the claims "read on an individual performing the claimed steps mentally or with pencil and paper").” Also under MPEP § 2106.04 III (C), Examiner cites that “Claims can recite a mental process even if they are claimed as being performed on a computer. The Supreme Court recognized this in Benson, determining that a mathematical algorithm for converting binary coded decimal to pure binary within a computer’s shift register was an abstract idea. The Court concluded that the algorithm could be performed purely mentally even though the claimed procedures "can be carried out in existing computers long in use, no new machinery being necessary." 409 U.S at 67, 175 USPQ at 675. See also Mortgage Grader, 811 F.3d at 1324, 117 USPQ2d at 1699 (concluding that concept of "anonymous loan shopping" recited in a computer system claim is an abstract idea because it could be "performed by humans without a computer").” In conclusion, Claims 1-5, 7-14 and 16-20 still recite an abstract idea under 35 U.S.C. § 101 step 2a prong one under the “Certain Methods of Organizing Human Activities” or “Mental Processes” or “Mathematical Concepts” Groupings and thus are maintained. Similar reasons and rationale are also applied to Dependent Claims under 35 U.S.C. § 101 as being patent ineligible. Further explanation is shown below in the 35 U.S.C. § 101 section regarding the Dependent Claims analysis. Thus, Claims 1-5, 7-14 and 16-20 are ineligible with respect to the 35 U.S.C. § 101 analysis.
Claim Rejections - 35 USC § 101
4. 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.
5. Claims 1-5, 7-14 and 16-20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Claims 1-5, 7-14 and 16-20 are each focused to a statutory category namely a “method” or a “process” (Claims 1-5 and 7-9), a “apparatus” or a “system” (Claims 10-14 and 16-18) and a “non-transitory computer readable storage medium” or an “article of manufacture” (Claims 19-20).
Step 2A Prong One: Independent Claims 1, 10 and 19 recite limitations that set forth the abstract idea(s), namely (see in bold except via strikethrough):
“” (see Independent Claim 10);
“” (see Independent Claim 10);
“” (see Independent Claim 10);
“” (see Independent Claim 10);
“” (see Independent Claim 19);
“receiving, from a user, a request for a resource allocation that includes first information that relates to at least one resource to be allocated” (see Independent Claim 1);
“receiving, , a first input that includes second information that relates to at least one constraint that is mandatory with respect to the request” (see Independent Claim 1);
“receiving, a second input that includes third information that relates to at least one preference that is not mandatory” (see Independent Claim 1);
“determining, , a minimal unsatisfied constraints set with respect to the request, wherein uses mixed-integer optimization to determine a least number of possible conditions required for satisfying the resource allocation to generate the minimal unsatisfied constraints set and reduce resource requirements, and wherein the mixed-integer optimization further determines whether a respective constraint of the at least one constraint must be altered for the satisfying of the resource allocation, wherein the generating of the minimal unsatisfied constraints set includes computing a series of conditional expressions for identifying a feasibility for the satisfying of the resource allocation” (see Independent Claim 1);
“identifying, at least one condition that is impossible to satisfy with respect to the request, based on the minimal unsatisfied constraints set, wherein the at least one condition includes at least one from among the at least one preference and the at least one constraint” (see Independent Claim 1);
“determining, , that an infeasibility exists with respect to fulfilling the request in a manner that satisfies each of the at least one constraint and the at least one preference, based on the identifying of the at least one condition” (see Independent Claim 1);
“generating, , an explanation for the infeasibility based on a result of the determining that the infeasibility exists” (see Independent Claim 1);
“determining whether an issue exists with the request, based on the generated explanation” (see Independent Claim 1);
“responsive to a determination that at least one issue exists with the request” (see Independent Claim 1);
“receiving, , a third input that relates to an adjustment of at least one from among the first information and the second information” (see Independent Claim 1);
“performing, , a debugging , to revise the request to re-specify the resource allocation, based on the generated explanation” (see Independent Claim 1);
“iteratively executing, the determining that the infeasibility exists and the generating of the explanation for the infeasibility to generate a revised explanation, based on the third input that relates to an adjustment of at least one from among the first information and the second information, and further based on the revised request” (see Independent Claim 1);
“responsive to a determination that an issue does not exist with the request, displaying, by the at least one processor, allocation information that relates to an action that satisfies the at least one constraint” (see Independent Claim 1);
“performing, and based on the generated explanation for the infeasibility, an action that facilitates the fulfillment of the request in a manner that overcomes the infeasibility” (see Independent Claim 1);
“receive, from a user , a request for a resource allocation that includes first information that relates to at least one resource to be allocated” (see Independent Claim 10);
“receive, , a first input that includes second information that relates to at least one constraint that is mandatory with respect to the request” (see Independent Claim 10);
“receive a second input that includes third information that relates to at least one preference that is not mandatory” (see Independent Claim 10);
“determine, , a minimal unsatisfied constraints set with respect to the request, wherein uses mixed-integer optimization to determine a least number of possible conditions required for satisfying the resource allocation to generate the minimal unsatisfied constraints set and reduce resource requirements, and wherein the mixed-integer optimization further determines whether a respective constraint of the at least one constraint must be altered for the satisfying of the resource allocation, wherein the generating of the minimal unsatisfied constraints set includes computing a series of conditional expressions for identifying a feasibility for the satisfying of the resource allocation” (see Independent Claim 10);
“identify, at least one condition that is impossible to satisfy with respect to the request, based on the minimal unsatisfied constraints set, wherein the at least one condition includes at least one from among the at least one preference and the at least one constraint” (see Independent Claim 10);
“determine that an infeasibility exists with respect to fulfilling the request in a manner that satisfies each of the at least one constraint and the at least one preference, based on the identifying of the at least one condition” (see Independent Claim 10);
“generate an explanation for the infeasibility based on a result of the determination that the infeasibility exists” (see Independent Claim 10);
“determine whether an issue exists with the request, based on the generated explanation” (see Independent Claim 10);
“responsive to a determination that at least one issue exists with the request” (see Independent Claim 10);
“receive a third input that relates to an adjustment of at least one from among the first information and the second information” (see Independent Claim 10);
“perform a debugging , to revise the request to re-specify the resource allocation, based on the generated explanation” (see Independent Claim 10);
“iteratively execute the determining that the infeasibility exists and the generating of the explanation for the infeasibility to generate a revised explanation, based on the third input that relates to an adjustment of at least one from among the first information and the second information, and further based on the revised request” (see Independent Claim 10);
“responsive to a determination that an issue does not exist with the request, display allocation information that relates to an action that satisfies the at least one constraint” (see Independent Claim 10);
“perform, based on the generated explanation for the infeasibility, an action that facilitates the fulfillment of the request in a manner that overcomes the infeasibility” (see Independent Claim 10);
“receive, from a user, a request for a resource allocation that includes first information that relates to at least one resource to be allocated” (see Independent Claim 19);
“receive a first input that includes second information that relates to at least one constraint that is mandatory with respect to the request” (see Independent Claim 19);
“receive a second input that includes third information that relates to at least one preference that is not mandatory” (see Independent Claim 19);
“determine, , a minimal unsatisfied constraints set with respect to the request, wherein uses mixed-integer optimization to determine a least number of possible conditions required for satisfying the resource allocation to generate the minimal unsatisfied constraints set and reduce resource requirements, and wherein the mixed-integer optimization further determines whether a respective constraint of the at least one constraint must be altered for the satisfying of the resource allocation, wherein the generating of the minimal unsatisfied constraints set includes computing a series of conditional expressions for identifying a feasibility for the satisfying of the resource allocation” (see Independent Claim 19);
“identify, at least one condition that is impossible to satisfy with respect to the request, based on the minimal unsatisfied constraints set, wherein the at least one condition includes at least one from among the at least one preference and the at least one constraint” (see Independent Claim 19);
“determine that an infeasibility exists with respect to fulfilling the request in a manner that satisfies each of the at least one constraint and the at least one preference, based on the identifying of the at least one condition” (see Independent Claim 19);
“generate an explanation for the infeasibility based on a result of the determining that the infeasibility exists” (see Independent Claim 19);
“determine whether an issue exists with the request, based on the generated explanation” (see Independent Claim 19);
“responsive to a determination that at least one issue exists with the request” (see Independent Claim 19);
“receive a third input that relates to an adjustment of at least one from among the first information and the second information” (see Independent Claim 19);
“perform a debugging to revise the request to re-specify the resource allocation, based on the generated explanation” (see Independent Claim 19);
“iteratively execute the determining that the infeasibility exists and the generating of the explanation for the infeasibility to generate a revised explanation, based on the third input that relates to an adjustment of at least one from among the first information and the second information, and further based on the revised request” (see Independent Claim 19);
“responsive to a determination that an issue does not exist with the request, display allocation information that relates to an action that satisfies the at least one constraint” (see Independent Claim 19);
“perform, based on the generated explanation for the infeasibility, an action that facilitates the fulfillment of the request in a manner that overcomes the infeasibility” (see Independent Claim 19).
Here, the claim limitations of Independent Claims 1, 10 and 19 are directed to the abstract idea of optimal constraint satisfaction and feasibility analysis for resource allocation using mathematical optimization as well as analyzing and troubleshooting data, or a method of managing resource allocation/scheduling. The core concept of the claims pertains to analyzing constraints, determining why a goal is infeasible, and iteratively proposing modifications to fix the infeasibility.
The claim elements describe a process of receiving inputs (requests, constraints, preferences), analyzing them using an AI algorithm/mathematical optimization (minimal unsatisfied constraints set), and identifying impossible conditions to determine feasibility.
Certain Method of Organizing Human Activity/Economic Activity: The overall goal is "resource allocation," which is often categorized as a business or organizational method. Managing resource requests, constraints, and preferences to determine feasibility.
Mental Processes: The steps of receiving, analyzing, and determining infeasibility can be performed mentally or with basic logical, data-handling tools, characteristic of a mental process. The steps involve identifying, evaluating, analyzing, and judging the feasibility of a system, which are actions that can be performed in the human mind or by a human using "pen and paper".
Mathematical Concept/Algorithm: The steps heavily rely on "mixed-integer optimization" and computing "conditional expressions" to calculate a "minimal unsatisfied constraints set." This aligns with mathematical concepts, which are abstract ideas. The debugging mechanism and iterative revision involve constraint satisfaction and algorithm-based optimization.
Receiving Data (Steps 1, 2, 3): Receiving inputs is a well-known, conventional, non-technical activity. AI/Optimization Algorithm (Step 4 & 5): Determining a "minimal unsatisfied constraints set" via "mixed-integer optimization" is an algorithmic and mathematical process. While AI is used, it is treated as a "black box" to solve a logical problem rather than to improve the computer's internal functioning, it is considered abstract. Determining Infeasibility (Step 6): Identifying a logical outcome (feasibility) based on the input is the analysis part of the mathematical algorithm. Generating an explanation for infeasibility (Step 8): This step is a high-level, data-analysis act. Without being tied to specific technical implementation (like a debugging system), it could be considered a "mental process" (abstract idea). This acts to analyze constraints, which is generally a mental process or a "method of organizing human activity" (e.g., managing a problem). Determining an issue with the request (Step 9): This acts as "analyzing data" or "identifying a problem," which is a form of an abstract idea. This is often considered an abstract idea ("collecting and analyzing data"). Receiving a third input (Adjustment) (Step 10): Receiving input alone is a conventional step, and thus often considered an abstract concept. Performing a debugging mechanism/Iteratively executing (Step 11): This is a certain method of organizing human activity or alternatively a mental process. Displaying allocation information (Step 12): This is generally considered "gathering and outputting data," which is an abstract idea. This is often treated as insignificant post-solution activity. Performing an action that facilitates the fulfillment of the request (Step 13): This is a certain method of organizing human activity via managing personal behavior (including teachings or following rules or instructions) or mental process via judgment or observations.
Therefore, these abstract idea limitations (as identified above in bold), under their broadest reasonable interpretation of the claims as a whole, cover performance of their limitations as “Certain Methods of Organizing Human Activities” which pertains to (1) managing personal behavior (including teachings or following rules or instructions) or alternatively as “Mathematical Concepts” which pertains to (2) mathematical calculations or (3) mathematical relationships.
Additionally, or alternatively, these abstract idea limitations (as identified above in bold), under the broadest reasonable interpretation of the claims as a whole, cover performance of their limitations as “Mental Processes” which pertains to (4) concepts performed in the human mind (including observations or evaluations or judgments) or (5) using pen and paper as a physical aid, in order to help perform these mental steps does not negate the mental nature of these limitations. The use of "physical aids" in implementing the abstract mental process, does not preclude these claims from reciting an abstract idea. See MPEP § 2106.04(a) III C.
That is, other than reciting the additional elements of (e.g., “a memory” & “communication interface” & “display” & “debugging mechanism” & “non-transitory computer readable storage medium” & “a processor”, etc…), nothing in the claim elements precludes the steps from being performed as “Certain Methods of Organizing Human Activities” which pertains to (1) managing personal behavior (including teachings or following rules or instructions) and additionally or alternatively as “Mathematical Concepts” which pertains to (2) mathematical calculations or (3) mathematical relationships and additionally or alternatively as “Mental Processes” which pertains to (4) concepts performed in the human mind (including observations or evaluations or judgments) or (5) using pen and paper as a physical aid.
Moreover, the mere recitation of generic computer components such as (e.g., “a memory” & “a processor”) does not take the claims out of “Certain Methods of Organizing Human Activities” or “Mental Processes” or “Mathematical Concepts” Groupings.
Therefore, at step 2a prong 1, Yes, Claims 1-5, 7-14 and 16-20 recite an abstract idea. We proceed onto analyzing the claims at step 2a prong 2.
Step 2A Prong Two: With respect to Step 2A Prong Two of the eligibility inquiry (as explained in MPEP § 2106.04(d)), the judicial exception is not integrated into a practical application. Independent Claims 1, 10 and 19 recites additional elements directed to: (e.g., “a memory” & “communication interface” & “display” & “non-transitory computer readable storage medium” & “a processor”). These additional elements have been considered individually and in combination, but fail to integrate the abstract idea into a practical application because they amount to using generic computing elements or instructions (software) to perform the abstract idea, similar to adding the words “apply it” (or an equivalent), which merely serves to link the use of the judicial exception to a particular technological environment. See MPEP § 2106.05(f) and MPEP § 2106.05(h).
Independent Claims 1, 10 and 19: With respect to reliance on (e.g., “debugging mechanism” & “artificial intelligence (AI) algorithm”) as additional elements when considered individually and as a ordered combination (as a whole) for the claim limitations for Independent Claims 1, 10 and 19, these additional elements do not provide limitations that are indicative of integration into a practical application due to: (1) reciting mere instructions to implement an abstract idea on a computer or using a computer as a tool to “apply” the recited judicial exceptions (see MPEP § 2106.05(f)) or (2) limiting to a particular field of use or technological environment pertaining to monitoring and analyzing infeasibility in order to identify at least one from among the at least one constraint that is impossible to satisfy for responding to a request for resource allocation in a business enterprise environment (see MPEP § 2106.05 (h)).
In addition, these limitations fail to provide an improvement to the functioning of a computer or to any other technology or technical field, fail to apply the exception with a particular machine, fail to apply the judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, fail to effect a transformation of a particular article to a different state or thing, and fail to apply/use the abstract idea in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
Accordingly, because the Step 2A Prong One and Prong Two analysis resulted in the conclusion that the claims are directed to an abstract idea, additional analysis under Step 2B of the eligibility inquiry must be conducted in order to determine whether any claim element or combination of elements amount to significantly more than the judicial exception. Therefore, at step 2a prong 2, Claims 1-5, 7-14 and 16-20 are directed to the abstract idea and do not recite additional elements that integrate into a practical application.
Step 2B: (As explained in MPEP § 2106.05), it has been determined that the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Independent Claims 1, 10 and 19 recites additional elements directed to: (e.g., “a memory” & “communication interface” & “display” & “non-transitory computer readable storage medium” & “a processor”). These elements have been considered individually and in combination, but fail to add significantly more to the claims because they amount to using computing elements or instructions (software) to perform the abstract idea, similar to adding the words “apply it” (or an equivalent), which merely serves to link the use of the judicial exception to a particular technological environment (computing environment) and does not amount to significantly more than the abstract idea itself. See MPEP § 2106.05 (h) and See MPEP § 2106.05 (f). Notably, Applicant’s Specification suggests that the claimed invention relies on nothing more than a general-purpose computer executing the instructions to implement the invention (see at least Applicant’s Specification ¶ [0037]: “The processor 104 may be a general-purpose processor or may be part of an application specific integrated circuit (ASIC). The processor 104 may also be a microprocessor, a microcomputer, a processor chip, a controller, a microcontroller, a digital signal processor (DSP), a state machine, or a programmable logic device.”).
Independent Claims 1, 10 and 19: With respect to reliance on (e.g., “debugging mechanism” & “artificial intelligence (AI) algorithm”) as additional elements when considered individually and as an ordered combination (as a whole) in view of the claim limitations for Independent Claims 1, 10 and 19, these additional elements do not amount to significantly more than the judicial exceptions under step 2B due to: (1) reciting mere instructions to implement an abstract idea on a computer or using a computer as a tool to “apply” the recited judicial exceptions (see MPEP § 2106.05(f)) or (2) limiting to a particular field of use or technological environment pertaining to monitoring and analyzing infeasibility in order to identify at least one from among the at least one constraint that is impossible to satisfy for responding to a request for resource allocation in a business enterprise environment (see MPEP § 2106.05 (h)).
Additionally, certain/particular claim limitations in Independent Claims 1, 10 and 19 recite steps of “receiving data” when evaluated as additional elements, these activities at most amount to insignificant extra-solution activities (see MPEP § 2106.05 (g)), which have been recognized as Well-Understood, Routine and Conventional (WURC), and thus insufficient to add significantly more to the abstract idea. See MPEP § 2106.05(d) ii - 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 (utilizing an intermediary computer to forward information); 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).
The additional element of “artificial intelligence (AI) algorithm” in Independent Claims 1, 10 and 19 does not amount to significantly more than the judicial exceptions under step 2B due being expressly recognized as Well-Understood, Routine and Conventional (WURC) in the art.
See for example; US PG Pub (US 2021/0117873 A1) hereinafter Vakhutinsky, et. al. Vakhutinsky at ¶ [0002]: “One embodiment is directed generally to a computer system, and in particular to a computer system that provides artificial intelligence-based room assignment optimization.” Vakhutinsky at ¶ [0027]: “Most hotel operators generally perform the room assignment manually by assigning the rooms to the individual reservations through an intuitive domain understanding, which is labor-intensive and, in many cases, results in assignments that are far from optimal. Some known solutions solve the problem using Mixed Integer Linear Programming (“MILP”).”
See for example; US PG Pub (US 2022/0366360 A1) hereinafter Terrazas-Moreno, et. al. Terrazas-Moreno at ¶ [0043]: “The math model constructor 222 implements a data-driven algorithm that creates an equation-oriented model 223a-n out of a black-box, input-output model 221a-n, using statistics, machine learning, and/or Artificial Intelligence techniques.” Terrazas-Moreno at ¶ [0050]: “If the problem (solving the equation-oriented models 223a-n) is feasible the algorithm converges; if the problem is infeasible, a new constraint is written exclusively in terms of Category 1 and Category 2 variables and added to the master problem 225, e.g., as another equation in the master problem 225. This constraint is referred to as a “cut” and it can be generated in several ways. For instance, the constraint can be generated through: (i) an integer cut, (ii) a Benders cut, (iii) a logic-based cut, and (iv) a cut generated through data-driven and/or artificial intelligence means.”
See for example; US PG Pub (US 2010/0318207 A1) hereinafter Yee, et. al. Yee at ¶ [0044] notes: “FIG. 22 illustrates a high-level overview of database federation and "Extract, Transform, and Load" ("ETL") database management to query, search, and selectively extract data, present the data, analyze and present the data using complex optimization, for example, integer programming, mixed integer programming, heuristics, and artificial intelligence, among other techniques, human intervention and requesting additional data, as carried out by a sourcing agent.” See for example; US PG Pub (US 2004/0193473 A1) hereinafter Robertson, et. al. Robertson notes at ¶ [0060]: “An effective schedule is formed in step 820 using the worker data from steps 811, 812, and 813. In the field of employee staffing and scheduling, several techniques are known to create an optimized schedule using the worker data, such as the information described above in steps 811, 812, and 813. For instance, an optimized schedule for a security checkpoint may be formed using linear programming, quadratic or mixed-integer programming, nonlinear optimization, global optimization, non-smooth optimization using genetic and evolutionary algorithms, and constraint programming methods from artificial intelligence.”
In addition, when taken as an ordered combination, the ordered combination adds nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements integrates the abstract idea into a practical application. Therefore, when viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a practical application of the abstract idea or that, as an ordered combination, amount to significantly more than the abstract idea itself.
Dependent Claims 2-5, 7-9, 11-14, 16-18 and 20 recite additional elements directed to: (e.g., “first algorithm” & “SME knowledge database” & “graphical user interface (GUI)”), and when considered individually and as an ordered combination (as a whole) with the limitations recite the same abstract idea(s) as shown in Independent Claims 1, 10 and 19 along with further steps/details that could be performed as “Mental Processes” which pertains to (1) concepts performed in the human mind (including observations or evaluations or judgments) or (2) using pen and paper as a physical aid and additionally or alternatively as “Certain Methods of Organizing Human Activities” which pertains to (3) managing personal behavior (including teachings or following rules or instructions) and additionally or alternatively as “Mathematical Concepts” which pertains to (4) mathematical calculations or (5) mathematical relationships.
Dependent Claims 7-9 and 16-18 further narrow the abstract ideas, and are therefore still ineligible for the reasons previously provided in Steps 2A Prong 2 and 2B for Independent Claims 1, 10 and 19. Dependent Claims 2-5, 11-14 and 20: With respect to reliance on (e.g., “first algorithm” (see Dependent Claims 2, 11 and 20) & “mixed-integer optimization technique” (see Dependent Claims 2, 11 and 20) & “subject matter expertise (SME) database” (see Dependent Claims 3 and 12) & “graphical user interface (GUI)” (see Dependent Claims 4-5 & 13-14)) as additional elements shown in Dependent Claims 2-5, 11-14 and 20 when considered individually and as an ordered combination (as a whole) in view of these claim limitations, these additional elements do not provide limitations that are indicative of integration into a practical application under step 2a prong 2 and also do not recite additional elements that amount to significantly more than the recited judicial exceptions under step 2B due to: (1) recites mere instructions to implement an abstract idea on a computer or using a computer as a tool to “apply” the recited judicial exceptions by providing the results to the user on a computer (see MPEP § 2106.05 (f)) or (2) the claims as a whole are limited to a particular field of use or technological environment pertaining to monitoring and analyzing infeasibility in order to identify at least one from among the at least one constraint that is impossible to satisfy for responding to a request for resource allocation in a business enterprise environment (see MPEP § 2106.05 (h)).
Furthermore, certain/particular limitations in Dependent Claims 4-5 & 13-14 even if the steps of “mere data outputting/data displaying” (e.g., “further comprising displaying, via & graphical user interface (GUI), a result of the generating of the explanation” & “displaying via a GUI, a prompt that facilitates a reception of the third input”) are evaluated as additional elements, these activities at most amount to insignificant extra-solution activities, which has been recognized as Well-Understood, Routine and Conventional (WURC), and thus insufficient to add significantly more to the abstract idea. See MPEP § 2106.05(d) ii - 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 (utilizing an intermediary computer to forward information); 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).
The ordered combination of elements in the Dependent Claims (including the limitations inherited from the parent claim(s)) add nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Accordingly, the subject matter encompassed by the dependent claims fails to amount to a practical application or significantly more than the abstract idea itself. Therefore, under Step 2B, Claims 1-5, 7-14 and 16-20 do not include additional elements that are sufficient to amount to significantly more than the recited judicial exceptions. Thus, Claims 1-5, 7-14 and 16-20 are ineligible with respect to the 35 U.S.C. § 101 analysis.
Conclusion
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 DERICK HOLZMACHER whose telephone number is (571) 270-7853. The examiner can normally be reached on Monday-Friday 9:00 AM – 6:30 PM EST.
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/DERICK J HOLZMACHER/Patent Examiner, Art Unit 3625A
/BRIAN M EPSTEIN/Supervisory Patent Examiner, Art Unit 3625
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