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 .
Response to Amendment
Amendment received on 10/23/2025 is acknowledged and entered. Claim 2 has been canceled. Claims 1, 3, 14 and 19 have been amended. Claims 1 and 2-20 are currently pending in the application.
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 and 2-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
In determining whether a claim falls within an excluded category, the Examiner is guided by the Court’s two-part framework, described in Mayo and Alice. Id. at 217-18 (citing Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 75-77 (2012)); Bilski v. Kappos, 561 U.S. 593, 611 (2010); 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50 (Jan. 7, 2019); the October 2019 Update of the 2019 Revised Guidance (Oct. 17, 2019); 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence (July 17, 2024), and the USPTO’s Paten Subject Matter Eligibility Memorandums of August 4, 2025 and December 5, 2025.
Step 1
Claims are eligible for patent protection under § 101 if they are in one of the four statutory categories and not directed to a judicial exception to patentability (i.e., laws of nature, natural phenomena, and abstract ideas). Alice Corp. v. CLS Bank Int'l, 573 U. S. ____ (2014).
The broadest reasonable interpretation of claims 1 and 14 encompasses a computer system (e.g., hardware such as a processor and memory) that implements the recited functions. If assuming that the system comprises a device or set of devices, then the system is directed to a machine, which is a statutory category of invention.
Claim 19 is directed to a statutory category, because a series of steps for predicting an optimum material property value satisfies the requirements of a process (a series of acts). (Step 1: Yes).
Next, the claim is analyzed to determine whether it is directed to a judicial exception.
Step 2A – Prong 1
Claim 19 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more of predicting an optimum material property value and composition. The claim recites:
19. A method for reducing computation time to find a global minimum corresponding to an optimum material property value and a material composition, the method comprising:
selecting a training dataset comprising a plurality of material compositions and
tagged property values of a predefined material property;
mapping the training dataset from an input space to an output space such that the mapped training dataset is convex; and
machine learning a convex function that approximates the mapped training dataset
in the output space using a machine learning module;
machine learning a minimum of the learned convex function and map the minimum of the learned convex function to the input space using the machine learning module; and
providing, based at least in part on the minimum of the learned convex
function mapped to the input space, an optimum material property value and a corresponding material composition.
The limitations of selecting a training dataset; mapping the dataset; learning a convex function; mapping the learned convex function; and providing an optimum material property and composition, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind and/or mathematical concepts, which may be practically performed in the human mind using observation, evaluation, judgment, and opinion (MPEP 2106.04(a)(2), subsection III), and/or certain methods of organizing human activity but for the recitation of generic computer components. (Note: Examiner’s language (e.g. “selecting a training dataset”; “mapping the dataset”; etc.) is an abbreviated reference to the detailed claim steps and is not an oversimplification of the claim language; the Examiner employing such
shortcuts (that refer to more specific steps) when attempting to explain the rejection). That is, other than reciting “by a processor,” nothing in the claim element precludes the step from practically being performed in the mind, and/or performed as organized human activity. Aside from the general technological environment (addressed below), it covers purely mental concepts and/or certain methods of organizing human activity processes, and the mere nominal recitation of a generic network appliance (e.g. an interface for inputting or outputting data, or generic network-based storage devices and displays) does not take the claim limitation out of the mental processes and/or certain methods of organizing human activity grouping.
Specifically, the utilizing mathematical tools to process data and to output the estimated values - said functions could be performed by a human using mental steps or basic critical thinking, which are types of activities that have been found by the courts to represent abstract ideas (e.g., mental comparison regarding a sample or test subject to a control or target data in Ambry, Myriad CAFC, or the diagnosing an abnormal condition by performing clinical tests and thinking about the results in In re Grams, 888 F.2d 835 (Fed. Cir. 1989) (Grams)). In Grams, the recited functions require obtaining data or patient information (from sensors), and analyze that data to ascertain the existence and identity of an abnormality or estimated responses, and possible causes thereof While said functions are performed by a computer, they are in essence a mathematical algorithm, in that they represent "[a] procedure for solving a given type of mathematical problem." Gottschalk v. Benson, 409 U.S. 63, 65, 93 S.Ct. 253, 254, 34 L.Ed.2d 273 (1972). Moreover, the Federal Circuit has held, “without additional limitations, a process that employs mathematical algorithms to manipulate existing information to generate additional information is not patent eligible.” Digitech Image Techs., LLC v. Elecs. for Imaging, Inc., 758 F.3d 1344, 1351 (Fed. Cir. 2014). Further, “analyzing information by steps people go through in their minds, or by
mathematical algorithms, without more, [are] essentially mental processes within the abstract-idea category.” Elec. Power, 830 F.3d at 1354; see also Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1146 (Fed. Cir. 2016). “[T]he fact that the required calculations could be performed more efficiently via a computer does not materially alter the patent eligibility of the claimed subject matter.” Bancorp Servs., L.L.C. v. Sun Life Assurance Co. of Can. (U.S.), 687 F.3d 1266, 1278 (Fed. Cir. 2012).
As per the use of artificial intelligence and/or machine learning techniques (AI/ML), said recitation does not make the claim patent eligible, because said tools are utilized merely for data gathering and comparing, and are not utilized in express manipulation and control of functional aspects and/or hardware components/equipment of real-world processes and systems using output of AI models (e.g., manufacturing processes and equipment, medical treatments, communications processes and systems, logistics systems and hardware, interactive smart phone apps, etc.).
Also, the recited limitations of selecting a training dataset; mapping the dataset; learning a convex function; mapping the learned convex function; and providing an optimum material property and composition can be characterized as “Certain Methods of Organizing Human Activity” grouping of abstract ideas, such as commercial or legal interactions including agreements, marketing or sales activities and business relations, as well as managing personal behavior or relationships or interactions between people, including following rules or instructions.
It is similar to other abstract ideas held to be non-statutory by the courts. See, also, Recentive Analytics, Inc. v. Fox Corp. (Fed. Cir. 2025), wherein the court noted that "iterative training," a claimed feature, was inherent to all machine learning models and thus did not confer eligibility. Additionally, applying machine learning to assessing material property, an activity predating computers, did not transform the abstract idea into a patent-eligible invention.
See, also, Mayo Collaborative Svcs. v. Prometheus Labs. 566 U.S. __, 132 S. Ct. 1289, 101 U.S.P.Q.2d 1961 (2012), - Optimizing drug therapeutic efficacy for treatment of immune-mediated gastrointestinal disorders; Genetic Tech. Ltd. v. Merial LLC; 818 F.3d 1369, 118 U.S.P.Q.2d 1541 (Fed. Cir. 2016) - Intron sequence analysis method for detection of adjacent and remote locus alleles as haplotypes; In re Karpf; 611 Fed. Appx. 1005 (Fed. Cir. 2015); CAFC Appeal No. 14-1773 - Increasing patient compliance with medical care instructions; Univ. of Utah Research Found. v. Ambry Genetics Corp. Also known as In re BRCA1– and BRCA2–Based Hereditary Cancer Test Patent Litigation; 774 F.3d 755, 113 U.S.P.Q.2d 1241 (Fed. Cir. 2014) - Breast and ovarian cancer susceptibility gene; and PerkinElmer Inc. v Intema Ltd., 96 Fed. Appx. 65, 105 U.S.P.Q.2d 1960 (Fed. Cir. 2012), - Antenatal screening for Down's syndrome.
Also, Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363 (Fed. Cir. 2015)—tailoring sales information presented to a user based on, e.g., user data and time data; TLI Communications LLC v. AV Automotive LLC 823 F.3d 607, 118 U.S.P.Q.2d 1744 (Fed. Cir. 2016) - recording, transmitting and administering digital images; DataTreasury Corp. v. Fidelity National Information Services 669 Fed. Appx. 572 (Fed. Cir. 2016) - remote image capture with centralized processing and storage; RecogniCorp LLC v. Nintendo Co. 855 F.3d 1322, 122 U.S.P.Q.2d 1377 (Fed Cir. 2017) - encoding and decoding image data; Intellectual Ventures I LLC v. Erie Indemnity Co. 850 F.3d 1315, 121 U.S.P.Q.2d 1928 (Fed Cir. 2017) - mobile interface for accessing remotely stored documents, and retrieving data from a database using an index of XML tags and metafiles.
As per receiving, storing and outputting data limitations, it has been held that “As many cases make clear, even if a process of collecting and analyzing information is ‘limited to particular content’ or a particular ‘source,’ that limitation does not make the collection and analysis other than abstract.” SAP Am., Inc. v. InvestPic, LLC, 898 F.3d 1161, 1168 (Fed. Cir. 2018) (citation omitted); see also In re Jobin, 811 F. App’x 633, 637 (Fed. Cir. 2020) (claims to collecting, organizing, grouping, and storing data using techniques such as conducting a survey or crowdsourcing recited a method of organizing human activity, which is a hallmark of abstract ideas).
All these cases describe the significant aspects of the claimed invention, albeit at another level of abstraction. See Apple, Inc. v. Ameranth, Inc., 842 F.3d 1229, 1240-41 (Fed. Cir. 2016) ("An abstract idea can generally be described at different levels of abstraction. As the Board has done, the claimed abstract idea could be described as generating menus on a computer, or generating a second menu from a first menu and sending the second menu to another location. It could be described in other ways, including, as indicated in the specification, taking orders from restaurant customers on a computer.").
Therefore, if a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” and/or “Certain Methods of Organizing Human Activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. (Step 2A – Prong 1: Yes).
Step 2A – Prong 2
In Prong Two, the Examiner determines whether claim 19, as a whole, recites additional elements that integrate the judicial exception into a practical application of the exception, i.e., whether the additional elements apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is no more than a drafting effort designed to monopolize the judicial exception. See Guidance, 84 Fed. Reg. at 54-55. If the additional elements do not integrate the judicial exception into a practical application, then the claim is directed to the judicial exception. See id., 84 Fed. Reg. at 54. “An additional element [that] reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field” is indicative of integrating a judicial exception into a practical application. See Guidance, 84 Fed. Reg. at 55.
The Examiner determined that this judicial exception is not integrated into a practical application, because there are no meaningful limitations that transform the exception into a patent eligible application. In particular, the claim recites additional elements – using a processor to perform the steps of selecting a training dataset; mapping the dataset; learning a convex function; mapping the learned convex function; and providing an optimum material property and composition. However, the processor in each step is recited (or implied) at a high level of generality, i.e., as a generic processor performing a generic computer functions of processing data, including receiving, storing, comparing, and outputting data. This generic processor limitation is no more than mere instructions to apply the exception using a generic computer component. See MPEP 2106.05(f). The processor that performs the recited steps merely automates these steps which can be done mentally or manually. Thus, while the additional elements have and execute instructions to perform the abstract idea itself, this also does not serve to integrate the abstract idea into a practical application as it merely amounts to instructions to "apply it." The claim only manipulates abstract data elements into another form, and does not set forth improvements to another technological field or the functioning of the computer itself and, instead, uses computer elements as tools in a conventional way to improve the functioning of the abstract idea identified above.
Further, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually; there is no indication that the combination of elements improves the functioning of a computer or improves any other technology, - their collective functions merely provide conventional computer implementation. None of the additional elements "offers a meaningful limitation beyond generally linking 'the use of the [method] to a particular technological environment,' that is, implementation via computers." Alice Corp., slip op. at 16 (citing Bilski v. Kappos, 561 U.S. 610, 611 (U.S. 2010)).
The recited steps do not control or improve operation of a machine (MPEP 2106.05(a)), do not effect a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)), and do not apply the judicial exception with, or by use a particular machine (MPEP 2106.05(b)), but, instead, require receiving, storing, comparing and outputting data.
Regarding the use of AI/ML techniques, said steps are nothing more than an attempt to recycle preexisting AI/ML technologies to apply for a particular computing application. There are no improvements in said AI/ML techniques, such as advances in the field of computer science itself, or designing a new neural network, and there is no controlling of a technological process using the outcome of said AI/ML operations.
Thus, the use of a trained machine learning model does not integrate the abstract idea of limitation into a practical application, because, under its broadest reasonable interpretation when read in light of the specification, the “estimating a duration and a probability” encompasses mental processes practically performed in the human mind by observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III. Similar to Recentive Analytics, claim 19 recites conventional machine learning models without specific improvements to the technology itself. The court noted that "iterative training," a claimed feature, was inherent to all machine learning models and thus did not confer eligibility. Claim 19 does not articulate "how" a technological improvement is achieved.
Further, regarding “A method for reducing computation time” recitation, this appears to be a speculative statement without any evidence of achieving said results in the Specification. The Specification, in the background section, broadly states “finding a global minimum or maximum of a function can be time and cost prohibitive since analytical methods are typically not available and numerical solution strategies often lead to excessive computation time and/or unacceptable error.” However, there is no evidence that the claimed method can achieve the stated results; the computation time may depend on many factors, e.g. computational complexity, real-time constraints, efficiency of utilization of resources (the ratio of the run time on one processor to the run time on N processors in parallel and distributed computing), overheads (e.g. load balancing, communication, synchronization, etc.), time spent for training, volume of data, difficulty of a task, OS performance, bandwidth, etc.,
As per receiving, storing and/or outputting data limitations, these recitations amount to mere data gathering and/or outputting, is insignificant post-solution or extra-solution component and represents nominal recitation of technology. Insignificant "post-solution” or “extra-solution" activity means activity that is not central to the purpose of the method invented by the applicant. However, “(c) Whether its involvement is extra-solution activity or a field-of-use, i.e., the extent to which (or how) the machine or apparatus imposes meaningful limits on the execution of the claimed method steps. Use of a machine or apparatus that contributes only nominally or insignificantly to the execution of the claimed method (e.g., in a data gathering step or in a field-of-use limitation) would weigh against eligibility”. See Bilski, 138 S. Ct. at 3230 (citing Parker v. Flook, 437 U.S. 584, 590, 198 USPQ 193, ___ (1978)). Thus, claim drafting strategies that attempt to circumvent the basic exceptions to § 101 using, for example, highly stylized language, hollow field-of-use limitations, or the recitation of token post-solution activity should not be credited. See Bilski, 130 S. Ct. at 3230.
Thus, claim 19 as a whole, outputs only data structure, - everything remains in the form of a code stored in the computer memory. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Therefore, the claim is directed to an abstract idea. (Step 2A – Prong 2: No).
Step 2B
If a claim has been determined to be directed to a judicial exception under revised Step 2A, examiners should then evaluate the additional elements individually and in combination under Step 2B to determine whether the provide an inventive concept (i.e., whether the additional elements amount to significantly more than the exception itself).
The Examiner determined that the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor to perform the steps of selecting a training dataset; mapping the dataset; learning a convex function; mapping the learned convex function; and providing an optimum material property and composition
amount to no more than mere instructions to apply the exception using a generic computer component.
The method would require a processor and memory in order to perform basic computer functions of receiving information, storing the information in a database, retrieving information from the database, comparing data, and outputting said information. These components are not explicitly recited and therefore must be
construed at the highest level of generality. Based on the Specification, the invention utilizes conventional communication networks and generic processors, which can be found in mobile devices or desktop computers, conventional memory and display devices, and the functions performed by said generic computer elements are basic functions of a computer - performing a mathematical operation, receiving, storing, comparing and outputting data - have recognized by the courts as routine and conventional activity. Specifically, regarding the recited functions, MPEP 2106.05(d)(II) defines said functions as routine and conventional, or as insignificant extra-solution activity:
i. 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); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) (“Unlike the claims in Ultramercial, the claims at issue here specify how interactions with the Internet are manipulated to yield a desired result‐‐a result that overrides the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink.” (emphasis added));
ii. Performing repetitive calculations, Flook, 437 U.S. at 594, 198 USPQ2d at 199 (recomputing or readjusting alarm limit values); Bancorp Services v. Sun Life, 687 F.3d 1266, 1278, 103 USPQ2d 1425, 1433 (Fed. Cir. 2012) (“The computer required by some of Bancorp’s claims is employed only for its most basic function, the performance of repetitive calculations, and as such does not impose meaningful limits on the scope of those claims.”); collecting and comparing known information in Classen 659 F.3d 1057, 100 U.S.P.Q.2d 1492 (Fed. Cir. 2011)
iii. Electronic recordkeeping, Alice Corp., 134 S. Ct. at 2359, 110 USPQ2d at 1984 (creating and maintaining “shadow accounts”); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log);
iv. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93;
v. Electronically scanning or extracting data from a physical document, Content Extraction and Transmission, LLC v. Wells Fargo Bank, 776 F.3d 1343, 1348, 113 USPQ2d 1354, 1358 (Fed. Cir. 2014) (optical character recognition); and
vi. A web browser’s back and forward button functionality, Internet Patent Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1418 (Fed. Cir. 2015).
Below are examples of other types of activity that the courts have found to be well-understood, routine, conventional activity when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity:
iv. Presenting offers and gathering statistics, OIP Techs., 788 F.3d at 1362-63, 115 USPQ2d at 1092-93;
v. Determining an estimated outcome and setting a price, OIP Techs., 788 F.3d at 1362-63, 115 USPQ2d at 1092-93; and
vi. Arranging a hierarchy of groups, sorting information, eliminating less restrictive pricing information and determining the price, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1331, 115 USPQ2d 1681, 1699 (Fed. Cir. 2015).
Regarding the use of a training model, and obtaining data via repetitive operation of said model, said steps are nothing more than an attempt to recycle preexisting AI/ML technologies to apply for a current application. There are no improvements in said AI/ML techniques, such as advances in the field of computer science itself, or designing a new neural network, and there is no controlling of a technological process using the outcome of said AI/ML operations. Claim 19 neither specifies a specific technical purpose for which the method is used, nor the claim defines a specific technical implementation of the method, nor the claimed method is particularly adapted for that implementation in that its design is motivated by technical considerations of the internal functioning of the computer. Said AI/ML algorithms and computations are done inside of a computer, and do not have a real-world impact and are not tied to the functionality of the computer. Further, there is no evidence that the invention lies in the training phase or execution phase or both; said AI/ML recitation represents merely conventionally applying an existing model to an existing data from publicly accessible databases, with the result being not technological, but purely entrepreneurial. Similar to Recentive Analytics, Inc. v. Fox Corp. (Fed. Cir. 2025), the machine learning technology as recited in claim 19 and described in the Specification is conventional, and “the processes and logic flows described in this specification can be performed by one or more programmable processors executing one or more computer programs to perform actions by operating on input data and generating output”.
Thus, the background of the current application does not provide any indication that the processor is anything other than a generic, off-the-shelf computer component, and the Symantec, TLI, and OIP Techs. court decisions cited in MPEP 2106.05(d)(II) indicate that mere collection or receipt of data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here).
Also, the claim does not involve a non-conventional and non-generic arrangement of known, conventional pieces, as asserted, by receiving information from an external source of data. The receiving of data from an external source over a network, such as via the Internet, can fairly be characterized as insignificant extra-solution activity that does not receive patentable weight. See Bilski, 545 F.3d 943, 963 (Fed. Cir. 2008) (en banc), aff’d sub nom Bilski v. Kappos, 561 U.S. 593 (2010) (characterizing data gathering steps as insignificant extra-solution activity). Similar to Content Extraction, 776 F.3d at 1347; Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 715 (Fed. Cir. 2014): “And we have recognized that merely presenting the results of abstract processes of collecting and analyzing information, without more (such as identifying a particular tool for presentation), is abstract as an ancillary part of such collection and analysis.” Here, the claims are clearly focused on the combination of those abstract-idea processes. The advance they purport to make is a process of gathering and analyzing information of a specified content, then displaying the results, and not any particular asserted inventive technology for performing those functions. They are therefore directed to an abstract idea. As such, the additional elements, considered individually and in combination with the other claim elements, do not make the claim as a whole significantly more than the abstract idea itself.
Accordingly, a conclusion that the recited steps are well-understood, routine, conventional activity is supported under Berkheimer Option 2. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
Following to the second step of the Mayo analysis, the Examiner did not find “significantly more” by using a particular machine, through specific limitations that are not well-understood, routine, and conventional, and by going beyond linking the abstract idea to a particular technological environment. The claimed steps do not require a particular machine. The Specification discloses:
[0038] Generally, modules as used herein include routines, programs, objects, components, data structures, and so on that perform particular tasks or implement particular data types. In further aspects, a memory generally stores the noted modules. The memory associated with a module may be a buffer or cache embedded within a processor, a RAM, a ROM, a flash memory, or another suitable electronic storage medium. In still further aspects, a module as envisioned by the present disclosure is implemented as an ASIC, a hardware component of a system on a chip (SoC), as a programmable logic array (PLA), or as another suitable hardware component that is embedded with a defined configuration set (e.g., instructions) for performing the disclosed functions.
[0039] Program code embodied on a computer-readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber, cable, radio frequency (RF), etc., or any suitable combination of the foregoing. Computer program code for carrying out operations for aspects of the present arrangements may be written in any combination of one or more programming languages, including an object-oriented programming language such as Java™, Smalltalk, C++ or the like and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer, or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).
Thus, neither claims nor the Specification identify a particular machine, because the Specification implies a vast array of computer elements that are encompassed by the various embodiments envisioned by the Applicant. The operations of receiving, storing, analyzing, and outputting data are primitive computer operations found in any computer system. See In re Katz Interactive Call Processing Patent Litig., 639 F.3d 1303, 1316 (Fed. Cir. 2011) (“Absent a possible narrower construction of the required hardware, the recited functions can be achieved by any general-purpose computer without special programming.”). Therefore, none of the claimed or implied memory storage, computer processor, or automatic operation provide “significantly more” that transforms the abstract idea into eligible subject matter.
In addition, as was noted earlier, except for the generic computer elements, there is nothing recited in the claim that goes beyond the abstract idea itself. Therefore, there is nothing recited that fails to be well-understood, routine, and conventional, and the claims are not linked to any particular technological environment, because so many computer options are articulated.
Further, similar to Electric Power Group v Alstom S.A. (Fed Cir, 2015-1778, 8/1/2016) (Power Group), claim’ invocation of computers, networks, and displays does not transform the claimed subject matter into patent-eligible applications. Claim 19 does not require any nonconventional computer, network, or display components, or even a “non-conventional and non-generic arrangement of known, conventional pieces,” but merely call for performance of the claimed information collection, analysis, and display functions on a set of generic computer components and display devices. Nothing in the claim, understood in light of the specification, requires anything other than off-the-shelf, conventional computer, network, and display technology for gathering, sending, and presenting the desired information. Analogous to Power Group, claim 19 does not even require a new source or type of information, or new techniques for analyzing it. As a result, the claim does not require an arguably inventive set of components or methods, such as measurement devices or techniques that would generate new data. The claim does not invoke any assertedly inventive programming. Merely requiring the selection and manipulation of information - to provide a “humanly comprehensible” amount of information useful for users - by itself does not transform the otherwise-abstract processes of information collection and analysis into patent eligible subject matter. Merely obtaining and selecting information, by content or source, for collection, analysis, and display does nothing significant to differentiate a process from ordinary mental processes, whose implicit exclusion from § 101 undergirds the information-based category of abstract ideas. Therefore, the recited steps represent implementing the abstract idea on a generic computer, or “reciting a commonplace business method aimed at processing business information despite being applied on a general purpose computer” Versata, p. 53; Ultramerical, pp. 11-12.
Furthermore, there is no technological improvement provided by the claim. The recited functions do not improve the functioning of computers itself, including of the processor(s) or the network elements, and there are no physical improvements in the claim, like a faster processor or more efficient memory, and there is no operational improvement, like mathematical computation that improve the functioning of the computer. Applicant did not invent a new type of computer; Applicant like everyone else programs their computer to perform functions. The Supreme Court in Alice indicated that an abstract claim might be statutory if it improved another technology or the computer processing itself. Using a (programmed) computer to implement a common business practice does neither. The Federal Circuit has recognized that "an invocation of already-available computers that are not themselves plausibly asserted to be an advance, for use in carrying out improved mathematical calculations, amounts to a recitation of what is 'well-understood, routine, [and] conventional.'" SAP Am., Inc. v. InvestPic, LLC, 890 F.3d 1016, 1023 (Fed. Cir. 2018) (alteration in original) (citing Mayo v. Prometheus, 566 U.S. 66, 73 (2012)). Apart from the instructions to implement the abstract idea, they only serve to perform well-understood functions (e.g., receiving, storing, comparing and transmitting data—see the Specification as well as Alice Corp.; Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307 (Fed. Cir. 2016); and Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334 (Fed. Cir. 2015) covering the well-known nature of these computer functions). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually; there is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. “However, it is not apparent how appellant’s programmed digital computer can produce any synergistic result. Instead, the computer will simply do the job it is instructed to do. Where is there any surprising or unexpected result? The unlikelihood of any such result is merely one more reason why patents should not be granted in situations where the only novelty is in the programming of general purpose digital computers”. See Sakraida v. Ag. Pro, Inc., 425 U.S. 273 [ 96 S.Ct. 1532, 47 L.Ed.2d 784], 189 USPQ 449 (1976) and A P Tea Co. V. Supermarket Corp., 340 U.S. 147 [ 71 S.Ct. 127, 95 L.Ed. 162], 87 USPQ 303 (1950).
Also, there are no improvements in said machine learning techniques, such as advances in the field of computer science itself, or designing a new neural network, and there is no controlling of a technological process using the outcome of said techniques. Said machine learning algorithms and computations are done inside of a computer, and do not have a real-world impact and are not tied to the functionality of the computer. Further, there is no evidence that the invention lies in the training phase or execution phase or both. However, machine learning subject matter becomes patent-eligible only when it achieves a technical purpose and, at minimum, offers a technical effect that does more than performing the solution more quickly or efficiently. The general application of machine learning techniques to solve a problem predictably is not eligible for patentability.
Moreover, there is no transformation recited in the claim as understood in view of 35 USC 101. The recited steps merely represent abstract ideas which cannot meet the transformation test because they are not physical objects or substances. Bilski, 545 F.3d at 963. Said steps are nothing more than mere manipulation or reorganization of data, which does not satisfy the transformation prong. It is further noted that the underlying idea of the recited steps could be performed via pen and paper or in a person's mind. Moreover, “We agree with the district court that the claimed process manipulates data to organize it in a logical way such that additional fraud tests may be performed. The mere manipulation or reorganization of data, however, does not satisfy the transformation prong.” and “Abele made clear that the basic character of a process claim drawn to an abstract idea is not changed by claiming only its performance by computers, or by claiming the process embodied in program instructions on a computer readable medium. Thus, merely claiming a software implementation of a purely mental process that could otherwise be performed without the use of a computer does not satisfy the machine prong of the machine-or-transformation test”. CyberSource, 659 F.3d 1057, 100 U.S.P.Q.2d 1492 (Fed. Cir. 2011)
Therefore, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception, because, when considered separately and in combination, the claim elements do not add significantly more to the exception. Considered separately and as an ordered combination, the claim elements do not provide an improvement to another technology or technical field; do not provide an improvement to the functioning of the computer itself; do not apply the judicial exception by use of a particular machine; do not effect a transformation or reduce a particular article to a different state or thing; and do not add a specific limitation other than what is well-understood, routine and conventional in the operation of a generic computer. None of the hardware recited "offers a meaningful limitation beyond generally linking 'the use of the [method] to a particular technological environment,' that is, implementation via computers." Id., slip op. at 16 (citing Bilski v. Kappos, 561 U.S. 610, 611 (U.S. 2010)). As per “selecting a training dataset” and “using a machine learning module” recitations, these limitations do not add significantly more because they are simply an attempt to limit the abstract idea to a particular technological environment, that is, implementation via computers." Id., slip op. at 16 (citing Bilski v. Kappos, 561 U.S. 610, 611 (U.S. 2010)). Limiting the claims to the particular technological environment is, without more, insufficient to transform the claim into patent-eligible applications of the abstract idea at their core.
Accordingly, claim 19 is not directed to significantly more than the exception itself, and is not eligible subject matter under § 101. (Step 2B: No).
Further, although the Examiner takes the steps recited in the independent claim as exemplary, the Examiner points out that limitations recited in dependent claim 20 further narrow the abstract idea but do not make the claims any less abstract. Dependent claim 20 merely add further details of the abstract steps recited in claim 19 without including an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. These claims "add nothing of practical significance to the underlying idea," and thus do not transform the claimed abstract idea into patentable subject matter. Ultramercial, 772 F.3d at 716. Therefore, dependent claim 20 is also directed to non-statutory subject matter.
Because Applicant’s apparatus claims 1 and 3-18 add nothing of substance to the underlying abstract idea, they too are patent ineligi-ble under §101.
Response to Arguments
Applicant's arguments filed 10/23/2025 have been fully considered but they are not persuasive.
Applicant argues that claim 1 recites elements that cannot be practically performed in the human mind using observation, evaluation, judgment, and opinion and/or certain methods of organizing human activity but for the recitation of generic computer components, because the recited steps utilize machine-learning technology.
The Examiner respectfully disagrees, and maintains that the recited steps is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind, which may be practically performed in the human mind using observation, evaluation, judgment, and opinion (MPEP 2106.04(a)(2), subsection III), and/or certain methods of organizing human activity but for the recitation of generic computer components. Said mental processes, as recited in the claims, remain
unpatentable even when automated to reduce the burden on the user of what once could have been done with pen and paper. CyberSource Corp. at 1375 (“That purely mental processes can be unpatentable, even when performed by a computer, was precisely the holding of the Supreme Court in Gottschalkv. Benson, [409 U.S. 63 (1972)].”). In Content Extraction & Transmission LLC v. Wells Fargo Bank, National Ass’n, Nos. 13-1588,-1589, 14-1112, -1687 (Fed. Cir. Dec. 23, 2014) the Federal Circuit affirmed that such limitations (parsing and extracting data) were generally directed to “the abstract idea of 1) collecting data, 2) recognizing certain data within the collected data set, and 3) storing that recognized data in a memory.” The Court explained that ”[t]he concept of data collection, recognition, and storage is undisputedly well-known,” and noted that “humans have always performed these functions.” Id. The Court then rejected CET’s argument that the claims were patent eligible because they required hardware to perform functions that humans cannot, such as processing and recognizing the stream of bits output by the scanner. Comparing the asserted claims to “the computer-implemented claims in Alice,” the Court concluded that the claims were “drawn to the basic concept of data recognition and storage,” even though they recited a scanner. Id. at 8. Mental processes, as recited in the claims, remain unpatentable even when automated to reduce the burden on the user of what once could have been done with pen and paper. CyberSource Corp. at 1375 (“That purely mental processes can be unpatentable, even when performed by a computer, was precisely the holding of the Supreme Court in Gottschalkv. Benson, [409 U.S. 63 (1972)].”).
Even accepting Applicant’s argument regarding the hardware used, it also is insufficient, without more, to establish patent eligibility that “[t]he human mind is not equipped to execute the claimed method”. Although “a method that can be performed by human thought alone is merely an abstract idea and is not patent-eligible under § 101,” CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1373 (Fed. Cir. 2011), it does not automatically follow, that methods requiring physical components, i.e., methods that arguably cannot be performed entirely in the human mind, are, therefore, not directed to abstract ideas. See, e.g., In re TLI Commc'ns LLC Patent Litig., 823 F.3d 607, 611 (Fed. Cir. 2016) (“[N]ot every claim that recites concrete, tangible components escapes the reach of the abstract-idea inquiry.”); FairWarning IP, LLC v. Latric Sys., Inc., 839 F.3d 1089, 1098 (Fed. Cir. 2016) (“[T]he inability for the human mind to perform each claim step does not alone confer patentability.”).
Applicant further argues that claim 1 provides a system that reduces computation time for predicting a new material composition with optimized properties, and as such provides an improvement to the field of materials exploration.
The Examiner respectfully disagrees, and points out that said “A method for reducing computation time” recitation appears to be a speculative statement without any evidence of achieving said results in the Specification. The Specification, in the background section, broadly states “finding a global minimum or maximum of a function can be time and cost prohibitive since analytical methods are typically not available and numerical solution strategies often lead to excessive computation time and/or unacceptable error.” However, there is no evidence that the claimed method can achieve the stated results; the computation time may depend on many factors, e.g. computational complexity, real-time constraints, efficiency of utilization of resources (the ratio of the run time on one processor to the run time on N processors in parallel and distributed computing), overheads (e.g. load balancing, communication, synchronization, etc.), time spent for training, volume of data, difficulty of a task, OS performance, bandwidth, etc. Thus, said Applicant’s argument is not convincing.
Also, the Examiner maintains that there is no technological improvement provided by the claim. The recited functions do not improve the functioning of computers itself, including of the processor(s) or the network elements, and there are no physical improvements in the claim, like a faster processor or more efficient memory, and there is no operational improvement, like mathematical computation that improve the functioning of the computer. Applicant programs their computer to perform functions. The Supreme Court in Alice indicated that an abstract claim might be statutory if it improved another technology or the computer processing itself. Using a (programmed) computer to implement a common business practice does neither. The Federal Circuit has recognized that "an invocation of already-available computers that are not themselves plausibly asserted to be an advance, for use in carrying out improved mathematical calculations, amounts to a recitation of what is 'well-understood, routine, [and] conventional.'" SAP Am., Inc. v. InvestPic, LLC, 890 F.3d 1016, 1023 (Fed. Cir. 2018) (alteration in original) (citing Mayo v. Prometheus, 566 U.S. 66, 73 (2012)). Apart from the instructions to implement the abstract idea, they only serve to perform well-understood functions (e.g., receiving, storing, comparing and transmitting data—see the Specification as well as Alice Corp.; Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307 (Fed. Cir. 2016); and Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334 (Fed. Cir. 2015) covering the well-known nature of these computer functions).
Also, there are no improvements in said machine learning techniques, such as advances in the field of computer science itself, or designing a new neural network, and there is no controlling of a technological process using the outcome of said techniques. Said machine learning algorithms and computations are done inside of a computer, and do not have a real-world impact and are not tied to the functionality of the computer. Further, there is no evidence that the invention lies in the training phase or execution phase or both. However, machine learning subject matter becomes patent-eligible only when it achieves a technical purpose and, at minimum, offers a technical effect that does more than performing the solution more quickly or efficiently. The general application of machine learning techniques to solve a problem predictably is not eligible for patentability.
Conclusion
The prior art search has been conducted, with no significant prior art found.
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 extension fee 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.
/IGOR N BORISSOV/Primary Examiner, Art Unit 3685
3/19/2026