DETAILED ACTION
This action is in response to the amendments filed on May 20th, 2026. A summary of this action:
Claims 1-7, 9-13, 15, 17 have been presented for examination.
Claims 1, 9 and 17 are objected to because of informalities
Claim 1-7, 9-13, 15, 17 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite
Claims 1-7, 9-13, 15, 17 rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement
All claim features rejected under § 112(a) are interpreted in view of MPEP § 2143.03(II): “When evaluating claims for obviousness under 35 U.S.C. 103, all the limitations of the claims must be considered and given weight, including limitations which do not find support in the specification as originally filed (i.e., new matter).” – as such, they are given their plain meaning for what is particularly recited in the claims themselves.
Claims 1-7, 9-13, 15, 17 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of both a mathematical concept and mental process without significantly more.
The claims are not rejected under § 102/103, as the art of record does not fairly teach: “interpreting… by compiling the one or more testable hypotheses to a computation graph, wherein the computation graph is a neural network with convolution layers configured to compute differentiation, integration, and (non)linear local operators for constitutive equations, wherein the convolution layers are equipped with repeating stencils that enable increased CPU computations;… validating or invalidating the at least one of the testable hypotheses by (a) fitting the unknown parameters to data relating to the physical system using the computation graph and (b) evaluating a goodness of fit for the fitting; and” as recited in the present ordered combination. To clarify, the closest art of record is the previously relied upon combinations of references (Non-final Act., Jan. 2026, for the primary references as previously relied upon, Examiner further noting Wang 2022 as previously relied upon, in particular note page 4 col. 2 ¶¶ 2-3; and the section on preliminary results for its discussion of applying least squares regression; also see Cao 2019 as previously relied upon, abstract and §§ 2.1 and 2.4), taken in further view of Mogers, Naums, et al. "Automatic generation of specialized direct convolutions for mobile GPUs." Proceedings of the 13th Annual Workshop on General Purpose Processing using Graphics Processing Unit. 2020. Abstract, § 1 ¶ 3, § 1 last two paragraphs, §§ 2.3-2.4, then see § 3.2 and § 4.1, however this does fairly teach what is presently claimed in the particular ordered combination noted above.
This action is Final
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 Arguments/Amendments
Regarding the § 112 Rejection
Withdrawn in view of amendment, new grounds as necessitated by amendment.
Regarding the § 101 Rejection
Maintained, updated as necessitated by amendment.
With respect to the prong 1 remarks, these are mostly directed to newly amended subject matter, so see below on how they are treated.
Furthermore, with respect to the remarks at 8, conservation laws, i.e. mathematical expressions of scientific truisms, no matter how particular they are, are not eligible under § 101. E.g. the law of the conservation of energy is readily expressed in mathematical form, and is also a law of nature – see MPEP § 2106.04(b)(I) incl.: “The law of nature and natural phenomenon exceptions reflect the Supreme Court's view that the basic tools of scientific and technological work are not patentable, because the "manifestations of laws of nature" are "part of the storehouse of knowledge," "free to all men and reserved exclusively to none." Funk Bros. Seed Co. v. Kalo Inoculant Co., 333 U.S. 127, 130, 76 USPQ 280, 281 (1948). Thus, "a new mineral discovered in the earth or a new plant found in the wild is not patentable subject matter" under Section 101. Diamond v. Chakrabarty, 447 U.S. 303, 309, 206 USPQ 193, 197 (1980). "Likewise, Einstein could not patent his celebrated law that E=mc2; nor could Newton have patented the law of gravity." Id. Nor can one patent "a novel and useful mathematical formula," Parker v. Flook, 437 U.S. 584, 585, 198 USPQ 193, 195 (1978);” – to further clarify, ¶ 15: “to express a wide range of mathematically viable physical hypotheses (e.g., candidates for theories/laws) from Kepler's and Newton's laws to elastodynamics in composite materials… Said approach entails: (a) defining a relatively unbiased ontology that is rooted in fundamental abstractions (also referred to as conservation laws) that are common to all known theories of classical and relativistic physics;…” and see MPEP § 2106.04(I): “The Court has held that a claim may not preempt abstract ideas, laws of nature, or natural phenomena, even if the judicial exception is narrow (e.g., a particular mathematical formula such as the Arrhenius equation). See, e.g., Mayo, 566 U.S. at 79-80, 86-87, 101 USPQ2d at 1968-69, 1971 (claims directed to "narrow laws that may have limited applications" held ineligible); Flook, 437 U.S. at 589-90, 198 USPQ at 197 (claims that did not "wholly preempt the mathematical formula" held ineligible). This is because such a patent would "in practical effect [] be a patent on the [abstract idea, law of nature or natural phenomenon] itself." Benson, 409 U.S. at 71- 72, 175 USPQ at 676. The concern over preemption was expressed as early as 1852. See Le Roy v. Tatham, 55 U.S. (14 How.) 156, 175 (1852) ("A principle, in the abstract, is a fundamental truth; an original cause; a motive; these cannot be patented, as no one can claim in either of them an exclusive right.")”
Furthermore, the Examiner notes that the discovery of new scientific hypotheses expressed in mathematical form, e.g. ¶ 47: “Both energy (first-order) and torque (second order) forms of the governing equation were discovered without human intervention” (note ¶ 46 as well, and ¶ 15: “mathematically viable physical hypotheses (e.g., candidates for theories/laws) from Kepler's and Newton's laws to elastodynamics in composite materials, by 25 exploiting common structural invariants across physics.”), is not a technological process, but rather the core of the abstract idea of the scientific method itself as used in all scientific discovery. MPEP § 2106.04(I): “The Supreme Court has explained that the judicial exceptions reflect the Court’s view that abstract ideas, laws of nature, and natural phenomena are "the basic tools of scientific and technological work", and are thus excluded from patentability because "monopolization of those tools through the grant of a patent might tend to impede innovation more than it would tend to promote it." Alice Corp., 573 U.S. at 216, 110 USPQ2d at 1980 (quoting Myriad, 569 U.S. at 589, 106 USPQ2d at 1978 and Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 (2012)).” – and simply adding one abstract idea to another (¶ 16: “At the core of (a) is a powerful mathematical abstraction of physical governing equations rooted in algebraic topology and differential geometry, leading to an ontological commitment to the relationship between physical measurement and basic properties of the embedding spacetime - but nothing more, to leave room for innovation and surprise”) does not provide a practical application. MPEP § 2106.04(II)(A)(2): “See, e.g., RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1327, 122 USPQ2d 1377 (Fed. Cir. 2017) ("Adding one abstract idea (math) to another abstract idea (encoding and decoding) does not render the claim non-abstract"); Genetic Techs. Ltd. v. Merial LLC, 818 F.3d 1369, 1376, 118 USPQ2d 1541, 1546 (Fed. Cir. 2016) (eligibility "cannot be furnished by the unpatentable law of nature (or natural phenomenon or abstract idea) itself.").”
With respect to the prong 2 remarks, see the rejection below for how it is rejected. Also, the Examiner notes that increasing the amount of CPU computation as claimed is not an improvement to technology, rather it is claiming a worse result (i.e. it takes more CPU computations to use the stencils). Furthermore, several of these remarks allege features which have no express basis in the claim itself – see MPEP § 2111 for In re Prater, for it is impermissible to import limitations into a claim which have no express basis in the claim language itself, and MPEP § 2106.05(a), for the claim must recite the features that provide the alleged improvement. Also, the Examiner notes that ¶ 54 conveys that the use of the stencils is merely replacing one math equation for another in a math calculation – a new abstract idea is still abstract. See MPEP § 2106.04(I).
With respect to “a directed acyclic graph” as alleged in the remarks, this feature is expressly not in the independent claim, and furthermore is, in the context of this specification (see rejection below for clarification), an abstract idea.
With respect to 2B, see the rejection below for how the newly amended claim is rejected under § 101, and see MPEP § 2106.05(I): “An inventive concept "cannot be furnished by the unpatentable law of nature (or natural phenomenon or abstract idea) itself." Genetic Techs. Ltd. v. Merial LLC, 818 F.3d 1369, 1376, 118 USPQ2d 1541, 1546 (Fed. Cir. 2016). See also Alice Corp., 573 U.S. at 21-18, 110 USPQ2d at 1981 (citing Mayo, 566 U.S. at 78, 101 USPQ2d at 1968 (after determining that a claim is directed to a judicial exception, "we then ask, ‘[w]hat else is there in the claims before us?") (emphasis added));… Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1151, 120 USPQ2d 1473, 1483 (Fed. Cir. 2016) ("a claim for a new abstract idea is still an abstract idea”). To clarify, only additional elements are considered at the WURC consideration, not the abstract idea itself.
Also, given the nature of the alleged improvement and specifically what its output is (math equations), see MPEP § 2106.04(I): “The Supreme Court has explained that the judicial exceptions reflect the Court’s view that abstract ideas, laws of nature, and natural phenomena are "the basic tools of scientific and technological work", and are thus excluded from patentability because "monopolization of those tools through the grant of a patent might tend to impede innovation more than it would tend to promote it." Alice Corp., 573 U.S. at 216, 110 USPQ2d at 1980 (quoting Myriad, 569 U.S. at 589, 106 USPQ2d at 1978 and Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 (2012))… The Supreme Court’s decisions make it clear that judicial exceptions need not be old or long-prevalent, and that even newly discovered or novel judicial exceptions are still exceptions. For example, the mathematical formula in Flook, the laws of nature in Mayo, and the isolated DNA in Myriad were all novel or newly discovered, but nonetheless were considered by the Supreme Court to be judicial exceptions because they were "‘basic tools of scientific and technological work’ that lie beyond the domain of patent protection." Myriad, 569 U.S. 576, 589, 106 USPQ2d at 1976, 1978 (noting that Myriad discovered the BRCA1 and BRCA1 genes and quoting Mayo, 566 U.S. 71, 101 USPQ2d at 1965); Flook, 437 U.S. at 591-92, 198 USPQ2d at 198 ("the novelty of the mathematical algorithm is not a determining factor at all"); Mayo, 566 U.S. 73-74, 78, 101 USPQ2d 1966, 1968 (noting that the claims embody the researcher's discoveries of laws of nature). The Supreme Court’s cited rationale for considering even "just discovered" judicial exceptions as exceptions stems from the concern that "without this exception, there would be considerable danger that the grant of patents would ‘tie up’ the use of such tools and thereby ‘inhibit future innovation premised upon them.’" Myriad, 569 U.S. at 589, 106 USPQ2d at 1978-79 (quoting Mayo, 566 U.S. at 86, 101 USPQ2d at 1971). See also Myriad, 569 U.S. at 591, 106 USPQ2d at 1979 ("Groundbreaking, innovative, or even brilliant discovery does not by itself satisfy the §101 inquiry.")….“
Regarding the § 102/103 Rejection
Withdrawn in view of the amendments.
Claim Objections
Claims 1, 9 and 17 are objected to because of the following informalities:
Independent claims recite: (non)linear – the use of parenthesis in this manner in a claim is informal (see MPEP § 608.01(m)). Examiner suggests reciting either “non-linear” or “nonlinear”, wherein the Examiner notes the more common manner to POSITA is “non-linear”
Claim 9 is objected to for antecedent basis, specifically see claim 1 which has two validating/invalidating steps, whereas claim 9 does not expressly convey which one it is further limitation. Examiner interprets claim 9 given the context of the original claims to further limit the one in the independent claim that was substantially in the original claims.
Appropriate correction is required.
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 1-7, 9-13, 15, 17 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. The dependent claims inherit the deficiencies of the claims they depend upon.
MPEP § 2173.05(b)(IV): “A claim term that requires the exercise of subjective judgment without restriction may render the claim indefinite. In re Musgrave, 431 F.2d 882, 893, 167 USPQ 280, 289 (CCPA 1970). Claim scope cannot depend solely on the unrestrained, subjective opinion of a particular individual purported to be practicing the invention. Datamize LLC v. Plumtree Software, Inc., 417 F.3d 1342, 1350, 75 USPQ2d 1801, 1807 (Fed. Cir. 2005));”
Independent claims recite: using the one or more machine learning techniques to perform validation or invalidation of the one or more testable hypotheses by first testing a first set of hypotheses and modifying the first set of hypotheses to form a second set of hypotheses more complex than the first set of hypotheses when the first set of hypotheses do not explain available data according to a condition” - wherein the term “complex” is a subjective term that renders the claim indefinite because there is no standard provided in the instant disclosure (¶¶ 2, 28, 33) for POSITA to ascertain the scope of the present claims without relying on their own unrestrained, subjective opinion when practicing the invention. To clarify, neither the claims nor the specification clearly define an objective standard for what is more complex as compared to what is less complex, i.e. its purely left to the subjective opinion of POSITA for whether something is more complex then something else (in this case hypotheses). E.g. is a hypothesis that adds two variables together more, or less, complex, than one that multiplies two variables, or one that integrates a variable, etc.
Claim 7 has a similar recitation rejected under a similar rationale
Claim Rejections - 35 USC § 112(a)
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-7, 9-13, 15, 17 rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. The dependent claims inherit the deficiencies of the claims they depend upon.
Independent claims recite:
wherein the computation graph is a neural network with convolution layers configured to compute differentiation, integration, and (non)linear local operators for constitutive equations, wherein the convolution layers are equipped with repeating stencils that enable increased CPU computations; see ¶ 54: “Further, for Cartesian grids (in space and/or time), the incidence tensor multiplications can be replaced with 20 efficient convolutions with repeating stencils, thereby enabling rapid computations on the GPU via fast Fourier transforms (FFTs) or convolutional neural networks (CNNs). For example, the tensor product [w]cn-1)X1 = [o]cn-l)xn. [0]nx1 can be implemented as [w]cn-1)X1 = [0]nxi * [-1, + 1] which produces the effect of sliding the stencil [-1, + 1] along the time series data and computing a finite difference formula.” – this does not sufficiently convey that this increases the CPU computations (i.e. more CPU computations are required), which is what the claim recites.
Furthermore, it does not convey that the layers are equipped with the stencils, but rather that the math operation of the convolutions themselves have repeating stencils (see ¶ 54, note the equations in particular and the particular terms used), wherein by replacing the math operation of “tensor multiplication” with that of the “convolutions with repeating stencils”, it enables “rapid computations on the GPU via fast Fourier transforms (FFTs) or convolutional neural networks (CNNs).”
Examiner suggests amending to more expressly reflect ¶ 54.
See MPEP 2163(II)(A): "For example, in Hyatt v. Dudas, 492 F.3d 1365, 1371, 83 USPQ2d 1373, 1376-1377 (Fed. Cir. 2007), the examiner made a prima facie case by clearly and specifically explaining why applicant’s specification did not support the particular claimed combination of elements, even though applicant’s specification listed each and every element in the claimed combination. The court found the "examiner was explicit that while each element may be individually described in the specification, the deficiency was lack of adequate description of their combination" and, thus, "[t]he burden was then properly shifted to [inventor] to cite to the examiner where adequate written description could be found or to make an amendment to address the deficiency.""
Also, see MPEP 2163(I) for Lockwood v. Amer. Airlines, Inc., 107 F.3d 1565, 1572, 41 USPQ2d 1961, 1966 (Fed. Cir. 1997).
Independent claims recite:
using the one or more machine learning techniques to perform validation or invalidation of the one or more testable hypotheses by first testing a first set of hypotheses and modifying the first set of hypotheses to form a second set of hypotheses more complex than the first set of hypotheses when the first set of hypotheses do not explain available data according to a condition;
….
validating or invalidating the at least one of the testable hypotheses by (a) fitting the unknown parameters to data relating to the physical system using the computation graph and (b) evaluating a goodness of fit for the fitting;
This particular order of steps is not sufficiently described in this order. See ¶¶ 32-36, 42, 56, 59 – also, see original claims 1 and 8, noting the antecedent basis in the original claims. In particular ¶¶ 32-36: “…Then, the at least one of the testable hypotheses may be validated or invalidated by (a) fitting the unknown parameters to data (e.g., simulation, experiment, or a combination of both) relating to the physical system and (b) evaluating a goodness of fit for the fitting….The interpreting of the at least one of the testable hypotheses may include mapping the physical variables to tensor data and physical relationships to computational operators in a computational framework. To achieve this mapping techniques such as machine learning, optimization platforms, numerical solvers or simulation platforms, or a combination thereof may be used… The fitting during validating or invalidating may be guided by a loss function, an error function, a cost function, an objective function, a utility function, or penalty function that quantifies how well a testable hypothesis explains the data.” and ¶ 66: “wherein the interpreting and the validating or invalidating for the multiple of the plurality of testable hypotheses is performed for simpler testable hypotheses and proceeds to other testable hypotheses that adds complexity incrementally if the simpler hypotheses do not 15 explain the data adequately” (note the antecedent in the specification, also see ¶¶ 32-33 as well and notes its antecedent) – this conveys a singular validating step, not two of them in the presently claimed ordered combination, with the steps in between them as presently claimed.
Independent claims recite:
using one or more machine learning techniques to interpret the one or more testable hypotheses by mapping the physical variables to tensor data and the physical relationships to computational operators in a computational framework;
…
interpreting at least one of the testable hypotheses into analytical and/or computational forms with a combination of known and unknown variables by compiling the one or more testable hypotheses to a computation graph, wherein the computation graph is a neural network with convolution layers configured to compute differentiation, integration, and (non)linear local operators for constitutive equations, wherein the convolution layers are equipped with repeating stencils that enable increased CPU computations;
See ¶ 32-33, then see ¶ 35, in particular note the antecedent in ¶ 35, also see ¶¶ 59 and 74 – also, see the original claims as filed (e.g. claims 1 and 16, noting the antecedent). The claim recites two distinct interpreting steps, however the specification by antecedent basis has it as one interpreting step (i.e. this particular combination requiring two interpreting steps, along with steps in between them, is not sufficiently described as being in this combination).
Examiner suggests amending the claims to more clearly reflect the original claims, with rolled-up/incorporated dependents including their antecedents for what they further limited, and to more expressly reflect ¶ 54, so as to address these rejections.
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 1-7, 9-13, 15, 17 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of both a mathematical concept and mental process without significantly more.
Step 1
Claim 1 is directed towards the statutory category of a process.
Claim 17 is directed towards the statutory category of an apparatus.
Claims 17, and the dependents thereof, are rejected under a similar rationale as representative claim 1, and the dependents thereof.
Step 2A – Prong 1
The claims recite an abstract idea of both a mental process and mathematical concept.
As an initial matter, this is focused on an abstract idea. ¶ 14: “The present disclosure relates methods and systems for artificial intelligence (AI)assisted generation of viable hypotheses. More specifically, the present disclosure describes a 'cyber-physicist' (CyPhy), an AI research associate for early-stage scientific process of hypothesis generation and initial validation or invalidation, grounded in the most invariable mathematical foundations of classical and relativistic physics.”
The thrust of the alleged advance in ¶ 14: “The framework distinguishes itself from existing rule-based reasoning, statistical learning, and hybrid AI methods by: (1) an ability to rapidly enumerate and test a diverse set of mathematically sound and parsimonious physical hypotheses, starting from a few basic assumptions on the embedding spacetime topology; (2) a distinction between non-negotiable mathematical truism (e.g., conservation laws or symmetries), that are directly implied by properties of spacetime, and phenomenological relations (e.g., constitutive laws), whose characterization relies indisputably on empirical observation, justifying targeted use of data-driven methods (e.g., machine learning (ML) or polynomial regression); and (3) a "simple-first" strategy (following Occam's razor) to search for new hypotheses by incrementally introducing latent variables that are expected to 20 exist based on topological foundations of physics” is merely the use of generic machine learning, or other commonplace algorithms (MPEP § 2106.05(f)) to seek to claim the process of discovery of math equations itself, but with a computer.
To further clarify, ¶ 15: “Further, the AI research associate may bridge multiple levels of abstraction, using a domain-agnostic representation scheme (referred to herein as an interaction network or I-net) to express a wide range of mathematically viable physical hypotheses (e.g., candidates for theories/laws) from Kepler's and Newton's laws to elastodynamics in composite materials, by exploiting common structural invariants across physics. Said approach entails: (a) defining a relatively unbiased ontology that is rooted in fundamental abstractions (also referred to as conservation laws) that are common to all known theories of classical and relativistic physics; (b) constructing a constrained search space to enumerate viable hypotheses with postulated invariants (e.g., built-in conservation laws that are consistent with the presupposed spacetime 30 topology); and (c) automatically assembling interpretable ML architectures for each hypothesis, to estimate parameters for phenomenological relations (also referred to herein as constitutive laws) from empirical data.” – Examiner noting that laws of nature, e.g. Kepler’s and Newton’s laws, are ineligible under § 101 (MPEP § 2106.04(b)(I)), and that “Mackay Radio & Telegraph Co. v. Radio Corp. of Am., 306 U.S. 86, 94, 40 USPQ 199, 202 (1939) (‘‘[A] scientific truth, or the mathematical expression of it, is not patentable invention[.]’’” (MPEP § 2106.04(a)(2)(I).
This is not a data structure, but rather a mathematical representation/abstraction. ¶ 16: “At the core of (a) is a powerful mathematical abstraction of physical governing equations rooted in algebraic topology and differential geometry, leading to an ontological commitment to the relationship between physical measurement and basic properties of the embedding spacetime - but nothing more, to leave room for innovation and surprise”. See fig. 2C which shows a graphical representation of math equations.
To clarify, ¶ 18: “The interaction networks or I-nets described herein may be based on a
generalization of Tonti diagrams that is expressive and versatile enough to accommodate novel scientific hypotheses, while retaining a basic commitment to philosophical principles such as parsimony (Occam's razor), measurement-driven classification of variables, and separation of non-negotiable mathematical properties of spacetime (homology) from domain-specific empirical knowledge (phenomenology).”
To further clarify, ¶ 22: “An abstract (symbolic) I-net may be defined on a single 'D-space as a finite collection of primary and/or secondary co-chain complexes that are inter-connected by phenomenological links (also referred to herein as constitutive laws), as illustrated in FIG. IA” – note, in § 101, constitutive laws, e.g. Hook’s laws, are generally referred to as Laws of Nature, “e.g., candidates for theories/laws) from Kepler's and Newton's laws to elastodynamics in composite materials,” in ¶ 15.
And ¶ 23: “The cross-sequence links can thus represent both single-physics constitutive relations and multi-physics coupling interactions. Conservation laws, on the other hand, are represented by a balance between the output of a topological operator and an external source/sink, the latter being represented by a loop.”
See ¶ 28 as well, which alleges no new computer data structure, but rather the use of a generic one: “The search space may be defined by a directed acyclic graph (DAG) whose nodes (i.e., states) represent symbolic I-net instances” in its ordinary capacity. See figure 2C which provides a visual depiction of this DAG wherein it is merely a graphical representation of math equations (see ¶¶ 41-42, ¶ 13: “FIG. 2C illustrates I-net representations of generated hypotheses along the search tree of FIG. 2B for the pendulum of FIG. 2A.”)
MPEP § 2106.05(a): “Examples that the courts have indicated may not be sufficient to show an improvement in computer-functionality… vii. Providing historical usage information to users while they are inputting data, in order to improve the quality and organization of information added to a database, because "an improvement to the information stored by a database is not equivalent to an improvement in the database’s functionality," BSG Tech LLC v. Buyseasons, Inc., 899 F.3d 1281, 1287-88, 127 USPQ2d 1688, 1693-94 (Fed. Cir. 2018); and” and MPEP § 2106.04(II)(A)(2): “See, e.g., RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1327, 122 USPQ2d 1377 (Fed. Cir. 2017) ("Adding one abstract idea (math) to another abstract idea (encoding and decoding) does not render the claim non-abstract"); Genetic Techs. Ltd. v. Merial LLC, 818 F.3d 1369, 1376, 118 USPQ2d 1541, 1546 (Fed. Cir. 2016) (eligibility "cannot be furnished by the unpatentable law of nature (or natural phenomenon or abstract idea) itself.").”
See MPEP § 2106.04: “...In other claims, multiple abstract ideas, which may fall in the same or different groupings, or multiple laws of nature may be recited. In these cases, examiners should not parse the claim. For example, in a claim that includes a series of steps that recite mental steps as well as a mathematical calculation, an examiner should identify the claim as reciting both a mental process and a mathematical concept for Step 2A Prong One to make the analysis clear on the record.”
To clarify, see the USPTO 101 training examples, available at https://www.uspto.gov/patents/laws/examination-policy/subject-matter-eligibility.
The mathematical concept recited in claim 1 is:
instantiating, by the processor, an interaction network (I-net) instance representing one or more testable hypotheses as a network or a graph structure comprising physical relationships among the physical variables, wherein the physical relationships are selected from the relationship types, and wherein, within the network or the graph structure, the physical variables are nodes and the physical relationships are edges;
using one or more machine learning techniques to interpret the one or more testable hypotheses by mapping the physical variables to tensor data and the physical relationships to computational operators in a computational framework;…
interpreting at least one of the testable hypotheses into analytical and/or computational forms with a combination of known and unknown variables by compiling the one or more testable hypotheses to a computation graph, wherein the computation graph is a neural network with convolution layers configured to compute differentiation, integration, and (non)linear local operators for constitutive equations, wherein the convolution layers are equipped with repeating stencils that enable increased CPU computations;
validating or invalidating the at least one of the testable hypotheses by (a) fitting the unknown parameters to data relating to the physical system using the computation graph and (b) evaluating a goodness of fit for the fitting;
This is simply in textual form claiming a mathematical graph/network (math relationships/equations in textual form, i.e. the physical relationships are the mathematical relationships between math variables, e.g. laws of nature), and then (note ¶ 32: “The analytical and/or computational forms may be one or more of: a differential equation, an integral equation, an integro-differential equation, a discrete-algebraic equation, and a system model.”; also note ¶ 42, and ¶ 45, etc., the term “hypotheses” is merely a broad term conveying, under the BRI consistent with the disclosure, series of math equations/relationships, i.e. the interpreting limitation is merely combining variables and equations together to discover new math equations, and the validating/invalidating is merely the math concept of discovering new equations/relationships, followed by mathematically testing them by math calculations to ensure they “fit”, e.g. by using another math equation (¶ 42: “A loss function can, for example, be defined as a mean-squared-error (MSE) to penalize violations uniformly over the time series period”.
To further clarify, ¶ 16: “The computation graphs is a tensor-based architecture, akin to a neural net with convolution layers to compute differentiation integration and (non)linear local operators [i.e. mathematical operations] for constitutive equations” and ¶ 54: “The tensor-based computation remains intact, except that incidence tensors will be less sparse. Further, for Cartesian grids (in space and/or time), the incidence tensor multiplications can be replaced with 20 efficient convolutions with repeating stencils, thereby enabling rapid computations on the GPU via fast Fourier transforms (FFTs) or convolutional neural networks (CNNs). For example, the tensor product [w]cn-1)X1 = [o]cn-l)xn. [0]nx1 can be implemented as [w]cn-1)X1 = [0]nxi * [-1, + 1] which produces the effect of sliding the stencil [-1, + 1] along the time series data and computing a finite difference formula.” – i.e. replacing one equation with another equation in mathematical prose for the “stencil” (i.e. the stencil is a math operation, per the equation, for a math calculation).
With respect to the mapping limitation, this is merely mapping variables to “tensor data” (tensors being akin to matrices) and mapping the physical relationships to computational operators (math operations per the specification), i.e. its merely a step of creating mathematical relationships/equations. Note fig. 2C.
To summarize, it is to 1) represent mathematical equations as graphs (e.g. fig 2C), which is “a powerful mathematical abstraction of physical governing equations rooted in algebraic topology and differential geometry” (¶ 16), 2) interpret the equations by mapping mathematical relationships between “physical variables” to data and “relationships” to “computational operators” [i.e. math operations as discussed above”, i.e. generating equations with variables and math operations, 3) perform some of the mathematical calculations with “stencils” (i.e. see ¶ 54 – its merely using a different mathematical operation to do the calculation, per the equations), then 4) ¶ 36: “The fitting during validating or invalidating may be guided by a loss function, an error function, a cost function, an objective function, a utility function, or penalty function that quantifies how well a testable hypothesis explains the data”, e.g. see equation 2 in ¶ 42: “loss function can, for example, be defined as a mean-squared-error (MSE) 30 to penalize violations uniformly over the time series period” – perform more mathematical calculations in textual form.
Under the broadest reasonable interpretation, the claim recites a mathematical concept – the above limitations are steps in a mathematical concept such as mathematical relationships, mathematical formulas or equations, and mathematical calculations. If a claim, under its broadest reasonable interpretation, is directed towards a mathematical concept, then it falls within the Mathematical Concepts grouping of abstract ideas. In addition, as per MPEP § 2106.04(a)(2): “It is important to note that a mathematical concept need not be expressed in mathematical symbols, because "[w]ords used in a claim operating on data to solve a problem can serve the same purpose as a formula." In re Grams, 888 F.2d 835, 837 and n.1, 12 USPQ2d 1824, 1826 and n.1 (Fed. Cir. 1989). See, e.g., SAP America, Inc. v. InvestPic, LLC, 898 F.3d 1161, 1163, 127 USPQ2d 1597, 1599 (Fed. Cir. 2018)”
See MPEP § 2106.04(a)(2).
To clarify, see the USPTO 101 training examples, available at https://www.uspto.gov/patents/laws/examination-policy/subject-matter-eligibility.
The mental process recited in claim 1 is the mental process of the scientific method, with additional mathematical concepts added to it:
A method for identifying, generating, and/or evaluating scientific hypotheses, the method comprising:
defining, by the processor, a plurality of physical variables and relationship types based on the underlying topology and the domain of interest, wherein the relationship types comprise at least topological relations derived from properties of the underlying topology and phenomenological relations whose parameters are derived from empirical data; instantiating, by the processor, an interaction network (I-net) instance representing one or more testable hypotheses as a network or a graph structure comprising physical relationships among the physical variables, wherein the physical relationships are selected from the relationship types, and wherein, within the network or the graph structure, the physical variables are nodes and the physical relationships are edges - these are merely reciting generating a graphical form of equations. See figure 2(c) as discussed in ¶ 50. An engineer or mathematician, or physicist, is readily able to mentally generate such graphs, e.g. they observe a problem to be solved, and develop a series of mathematical equations/mathematical expressions of scientific hypotheses, e.g. Newtown’s Law of Gravity, Kirchoff’s circuit laws, etc., that may explain the problem. See ¶¶ 41-43 as well to clarify.
using one or more machine learning techniques to interpret the one or more testable hypotheses by mapping the physical variables to tensor data and the physical relationships to computational operators in a computational framework; - a mental step, as this is merely mapping variables in math equations to “tensor data” [tensors being, in this context, akin to a matrix], e.g. see ¶ 50 and note the notation, similarly see ¶¶ 51 and 54, also see ¶¶ 41-43, and the physical relationships to mathematical operations, e.g. multiplication (see cited paragraphs, e.g. ¶ 51: “The co-boundary operators in EQ. 1 [an equation] are defined by” – the term “computational” here is merely a placeholder for calculatable, i.e. to later be calculated such as by a computer.
using the one or more machine learning techniques to perform validation or invalidation of the one or more testable hypotheses by first testing a first set of hypotheses and modifying the first set of hypotheses to form a second set of hypotheses more complex than the first set of hypotheses when the first set of hypotheses do not explain available data according to a condition; - a furthering of the scientific method, i.e. test the most simple hypotheses first, and if they do not explain the data one continues the journey of scientific discovery to find a hypotheses, expressed as mathematical truism, that explains the data. E.g. Newton’s law of gravity does not explain how a person can parachute out of a plane safely and be slowed down, so one adds the associated equations to account for the forces exerted by the parachute.
interpreting at least one of the testable hypotheses into analytical and/or computational forms with a combination of known and unknown variables by compiling the one or more testable hypotheses to a computation graph, wherein the computation graph is a neural network with convolution layers configured to compute differentiation, integration, and (non)linear local operators for constitutive equations, wherein the convolution layers are equipped with repeating stencils that enable increased CPU computations; - merely assembly of the equations for the later calculation, readily done mentally on pen and paper, wherein a person is readily able to perform mathematical operations such as integration and differentiation for equations.
validating or invalidating the at least one of the testable hypotheses by (a) fitting the unknown parameters to data relating to the physical system using the computation graph and (b) evaluating a goodness of fit for the fitting; - validating the equation (the hypotheses) by seeing if it fits the measured data and checking the goodness of the fit is readily a mental process, e.g. the person using physical aids such as a calculator to calculate a series of data points (e.g. calculating using Newton’s law of cooling the time it takes for a warm object to cool down to room temperature), plotting it along with plotting measured data points, and checking to see how well it fit, such as with a simple mathematical calculation to check for the fit using a simple equation, or using a ruler to measure the deviation from the calculated datapoints to the measured ones.
Under the broadest reasonable interpretation, these limitations are process steps that cover mental processes including an observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of physical aids but for the recitation of a generic computer component. If a claim, under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components, then it falls within the "Mental Process" grouping of abstract ideas. A person would readily be able to perform this process either mentally or with the assistance of physical aids. See MPEP § 2106.04(a)(2).
To clarify, see the USPTO 101 training examples, available at https://www.uspto.gov/patents/laws/examination-policy/subject-matter-eligibility. In particular, with respect to the physical aids, see example # 45, analysis of claim 1 under step 2A prong 1, including: “Note that even if most humans would use a physical aid (e.g., pen and paper, a slide rule, or a calculator) to help them complete the recited calculation, the use of such physical aid does not negate the mental nature of this limitation.”; also see example # 49, analysis of claim 1, under step 2A prong 1: “Moreover, the recited mathematical calculation is simple enough that it can be practically performed in the human mind. Even if most humans would use a physical aid, like a pen and paper or a calculator, to make such calculations, the use of a physical aid would not negate the mental nature of this limitation.”
As such, the claims recite an abstract idea of both a mental process and mathematical concept.
Step 2A, prong 2
The claimed invention does not recite any additional elements that integrate the judicial exception into a practical application. Refer to MPEP §2106.04(d).
The following limitations are merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f), including the “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more”:
Preamble of claim 1, the processor of claim 1, and the preamble of claim 17.
Recitations of “using one or more machine learning techniques” as considered as part of the mere instructions to automate the abstract idea using a computer and commonplace generic software (e.g. ¶ 35: “To achieve this mapping techniques such as machine learning,
optimization platforms, numerical solvers or simulation platforms, or a combination thereof
may be used.”)
For the following limitation:
wherein the computation graph is a neural network with convolution layers configured to compute differentiation, integration, and (non)linear local operators for constitutive equations, wherein the convolution layers are equipped with repeating stencils that enable increased CPU computations; - see ¶ 54 as discussed above, i.e. this is merely part of the instructions to automate it using a computer and commonplace software, with the intended functionality/result to use the CNN to perform math calculations such as “integration”, and generally linking to a particular technological environment. Of particular note is that this is to compute/calculate several mathematical operations expressly claimed, e.g. integration, and that the term “stencil” in view of ¶ 54 is merely conveying replacing one equation with another (see the equations in ¶ 54) during the calculation, but do it on a computer. There is no asserted improvement either to using the CNN alone, but rather: “fast Fourier transforms (FFTs) or convolutional neural networks (CNNs)”, and ¶ 54 merely conveys that these stencils are just simply a faster equation to calculate on a computer, i.e.: “For example, the tensor product [w]cn-1)X1 = [o]cn-l)xn. [0]nx1 can be implemented as [w]cn-1)X1 = [0]nxi * [-1, + 1] which produces the effect of sliding the stencil [-1, + 1] along the time series data and computing a finite difference formula” – with the purpose of “computing a finite difference formula” – i.e. a math calculation, and the stencil is a math operation expressed in mathematical prose in ¶ 54 and textual form in this claim, i.e. it’s merely equipping the convolutional layers with a math operation, and using a neural network to do math calculations, wherein by using the stencils it increases the CPU computation needed as required by the claim language itself.
The receiving step is mere data gathering as a token pre-solution activity, and the outputting/displaying step is mere data outputting/displaying as a token post-solution activity.
A claim that integrates a judicial exception into a practical application will 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 more than a drafting effort designed to monopolize the judicial exception. See MPEP § 2106.04(d).
MPEP 2106.04(II)(A)(2) “…Instead, under Prong Two, a claim that recites a judicial exception is not directed to that judicial exception, if the claim as a whole integrates the recited judicial exception into a practical application of that exception. Prong Two thus distinguishes claims that are "directed to" the recited judicial exception from claims that are not "directed to" the recited judicial exception…Because a judicial exception is not eligible subject matter, Bilski, 561 U.S. at 601, 95 USPQ2d at 1005-06 (quoting Chakrabarty, 447 U.S. at 309, 206 USPQ at 197 (1980)), if there are no additional claim elements besides the judicial exception, or if the additional claim elements merely recite another judicial exception, that is insufficient to integrate the judicial exception into a practical application. See, e.g., RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1327, 122 USPQ2d 1377 (Fed. Cir. 2017) ("Adding one abstract idea (math) to another abstract idea (encoding and decoding) does not render the claim non-abstract"); Genetic Techs. Ltd. v. Merial LLC, 818 F.3d 1369, 1376, 118 USPQ2d 1541, 1546 (Fed. Cir. 2016) (eligibility "cannot be furnished by the unpatentable law of nature (or natural phenomenon or abstract idea) itself."). For a claim reciting a judicial exception to be eligible, the additional elements (if any) in the claim must "transform the nature of the claim" into a patent-eligible application of the judicial exception, Alice Corp., 573 U.S. at 217, 110 USPQ2d at 1981, either at Prong Two or in Step 2B” and MPEP § 2106(I): “Mayo, 566 U.S. at 80, 84, 101 USPQ2dat 1969, 1971 (noting that the Court in Diamond v. Diehr found “the overall process patent eligible because of the way the additional steps of the process integrated the equation into the process as a whole,”” – and see MPEP § 2106.05(e).
To further clarify, MPEP § 2106.04(II)(A)(1): “Alice Corp., 573 U.S. at 216, 110 USPQ2d at 1980 (citing Mayo, 566 US at 71, 101 USPQ2d at 1965). Yet, the Court has explained that ‘‘[a]t some level, all inventions embody, use, reflect, rest upon, or apply laws of nature, natural phenomena, or abstract ideas,’’ and has cautioned ‘‘to tread carefully in construing this exclusionary principle lest it swallow all of patent law” See also Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335, 118 USPQ2d 1684, 1688 (Fed. Cir. 2016) ("The ‘directed to’ inquiry, therefore, cannot simply ask whether the claims involve a patent-ineligible concept, because essentially every routinely patent-eligible claim involving physical products and actions involves a law of nature and/or natural phenomenon").”
As a point of clarity, RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1327, 122 USPQ2d 1377 (Fed. Cir. 2017) ("Adding one abstract idea (math) to another abstract idea (encoding and decoding) does not render the claim non-abstract"); Genetic Techs. Ltd. v. Merial LLC, 818 F.3d 1369, 1376, 118 USPQ2d 1541, 1546 (Fed. Cir. 2016) (eligibility "cannot be furnished by the unpatentable law of nature (or natural phenomenon or abstract idea) itself." discussed in MPEP § 2106.04(II)(A)(2) as well as MPEP § 2106.04(I): “Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1151, 120 USPQ2d 1473, 1483 (Fed. Cir. 2016) ("a new abstract idea is still an abstract idea") (emphasis in original).
The claimed invention does not recite any additional elements that integrate the judicial exception into a practical application. Refer to MPEP §2106.04(d).
Step 2B
The claimed invention does not recite any additional elements/limitations that amount to significantly more.
The following limitations are merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f), including the “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more”:
Preamble of claim 1, the processor of claim 1, and the preamble of claim 17.
Recitations of “using one or more machine learning techniques” as considered as part of the mere instructions to automate the abstract idea using a computer and commonplace generic software (e.g. ¶ 35: “To achieve this mapping techniques such as machine learning,
optimization platforms, numerical solvers or simulation platforms, or a combination thereof
may be used.”)
For the following limitation:
wherein the computation graph is a neural network with convolution layers configured to compute differentiation, integration, and (non)linear local operators for constitutive equations, wherein the convolution layers are equipped with repeating stencils that enable increased CPU computations; - see ¶ 54 as discussed above, i.e. this is merely part of the instructions to automate it using a computer and commonplace software, with the intended functionality/result to use the CNN to perform math calculations such as “integration”, and generally linking to a particular technological environment. Of particular note is that this is to compute/calculate several mathematical operations expressly claimed, e.g. integration, and that the term “stencil” in view of ¶ 54 is merely conveying replacing one equation with another (see the equations in ¶ 54) during the calculation, but do it on a computer. There is no asserted improvement either to using the CNN alone, but rather: “fast Fourier transforms (FFTs) or convolutional neural networks (CNNs)”, and ¶ 54 merely conveys that these stencils are just simply a faster equation to calculate on a computer, i.e.: “For example, the tensor product [w]cn-1)X1 = [o]cn-l)xn. [0]nx1 can be implemented as [w]cn-1)X1 = [0]nxi * [-1, + 1] which produces the effect of sliding the stencil [-1, + 1] along the time series data and computing a finite difference formula” – with the purpose of “computing a finite difference formula” – i.e. a math calculation, and the stencil is a math operation expressed in mathematical prose in ¶ 54 and textual form in this claim, i.e. it’s merely equipping the convolutional layers with a math operation, and using a neural network to do math calculations, wherein by using the stencils it increases the CPU computation needed as required by the claim language itself.
The receiving step is mere data gathering as a token pre-solution activity, and the outputting/displaying step is mere data outputting/displaying as a token post-solution activity. Receiving data is WURC in view of MPEP § 2106.05(d)(II), as is outputting/displaying data WURC in view MPEP § 2106.05(d)(II), to clarify on the displaying also see example 46, claim 1, at step 2B for its WURC discussion of its displaying step.
The claimed invention is directed towards an abstract idea of both a mathematical concept and a mental process without significantly more.
Regarding the dependent claims
Claim 2 is further limiting the abstract idea itself
Claim 3 – further limiting the abstract idea itself, also should it be found its not its merely generally linking to a variety of fields of use
Claim 4 - further limiting the abstract idea itself, e.g. mentally evaluating data from a physical system, or just mental observations, e.g. observing the system is an electrical circuit, so therefore variables such as voltage and current are judged to be in the system
Claim 5 – further limiting the abstract idea itself, including explicit recitations of math operators for use in math equations/relationships/calculations
Claim 6 – further limiting the abstract idea itself to using mathematical expressions of laws of nature, readily mentally judged
Claim 7 – part of the abstract idea of arranging the equations into a graphical form (e.g. see figures 2B-2C) readily done mentally and also considered as a math concept as mathematical relationships between math equations, wherein the adding is merely adding more math relationships (e.g. fig. 2C as discussed in ¶ 41, e.g. ¶ 44: “Every time such a branch is turned into one or more closed cycles by adding enough new variables and/or relations”), the defining is merely adding math relationships between variables – i.e. its directed to a mental process of graphically depicting mathematical equations and relationships between them, and is also, for similar reasons directed to a math concept as it is a “mathematical abstraction of physical governing equations rooted in algebraic topology and differential geometry,” (¶ 16) – see ¶ 22 for more clarification, also see ¶ 42, e.g.: “Further down the search DAG, H-08 defines a new variable typed as a 0-pseudo-form L(f0 ) = ff2 (w(* f 0 )), where *To= (f0 _ Eh,i0 + Eh)-“
Claim 9 is further limiting the abstract idea by adding equations expressly to the graph (both mental and math), and people are readily able to fit math equations to data, e.g. graphing
Claim 10 – further limiting the abstract idea
Claim 11 – adding in a litany of math equations/relationships to the abstract idea, recited with such generality that people may readily mentally evaluate them such as with physical aids
Claim 12 – mere data gathering, which is WURC in view of MPEP § 2106.05(d)(II): “iii. Electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225, 110 USPQ2d 1984 (2014) (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”, e.g. this is so broad it literally encompasses: “Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 67, 101 USPQ2d 1961, 1964 (2010) provides an example of additional elements that were not an inventive concept because they were merely well-understood, routine, conventional activity previously known to the industry, which were not by themselves sufficient to transform a judicial exception into a patent eligible invention. Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 79-80, 101 USPQ2d 1969 (2012) (citing Parker v. Flook, 437 U.S. 584, 590, 198 USPQ 193, 199 (1978) (the additional elements were "well known" and, thus, did not amount to a patentable application of the mathematical formula)). In Mayo, the claims at issue recited naturally occurring correlations (the relationships between the concentration in the blood of certain thiopurine metabolites and the likelihood that a drug dosage will be ineffective or induce harmful side effects) along with additional elements including telling a doctor to measure thiopurine metabolite levels in the blood using any known process. 566 U.S. at 77-79, 101 USPQ2d at 1967-68. The Court found this additional step of measuring metabolite levels to be well-understood, routine, conventional activity already engaged in by the scientific community because scientists "routinely measured metabolites as part of their investigations into the relationships between metabolite levels and efficacy and toxicity of thiopurine compounds." 566 U.S. at 79, 101 USPQ2d at 1968. Even when considered in combination with the other additional elements, the step of measuring metabolite levels did not amount to an inventive concept, and thus the claims in Mayo were not eligible. 566 U.S. at 79-80, 101 USPQ2d at 1968-69” as discussed in MPEP § 2106.05(d), - for additional WURC evidence see ¶¶ 32 and 35, for the specification goes into no details but as is preferable omits what is WURC, as per MPEP § 2106.07(a)(III): “(A) A citation to an express statement in the specification or to a statement made by an applicant during prosecution that demonstrates the well-understood, routine, conventional nature of the additional element(s). A specification demonstrates the well-understood, routine, conventional nature of additional elements when it describes the additional elements as well-understood or routine or conventional (or an equivalent term), as a commercially available product, or in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. 112(a).” and To clarify, see MPEP § 2164.01: “A patent need not teach, and preferably omits, what is well known in the art. In re Buchner, 929 F.2d 660, 661, 18 USPQ2d 1331, 1332 (Fed. Cir. 1991); Hybritech, Inc. v. Monoclonal Antibodies, Inc., 802 F.2d 1367, 1384, 231 USPQ 81, 94 (Fed. Cir. 1986), cert. denied, 480 U.S. 947 (1987); and Lindemann Maschinenfabrik GMBH v. American Hoist & Derrick Co., 730 F.2d 1452, 1463, 221 USPQ 481, 489 (Fed. Cir. 1984).” Also see MPEP § 2163(II)(A)(3)(a): “What is conventional or well known to one of ordinary skill in the art need not be disclosed in detail. See Hybritech Inc. v. Monoclonal Antibodies, Inc., 802 F.2d at 1384, 231 USPQ at 94. See also Capon v. Eshhar, 418 F.3d 1349, 1357, 76 USPQ2d 1078, 1085 (Fed. Cir. 2005) ("The ‘written description’ requirement must be applied in the context of the particular invention and the state of the knowledge…. As each field evolves, the balance also evolves between what is known and what is added by each inventive contribution."). If a skilled artisan would have understood the inventor to be in possession of the claimed invention at the time of filing, even if every nuance of the claims is not explicitly described in the specification, then the adequate description requirement is met.”
Claim 13 – further limiting the abstract idea
Claim 15 – mere data gathering, followed by repeating the abstract idea step of the validating/invalidating with new data. WURC evidence: see MPEP § 2106.05(d)(II): “iii. Electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225, 110 USPQ2d 1984 (2014) (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
The claimed invention is directed towards an abstract idea of both a mathematical concept and a mental process without significantly more.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Ahmad, Afzal, and Muhammad Adeel Pasha. "Optimizing hardware accelerated general matrix-matrix multiplication for CNNs on FPGAs." IEEE Transactions on Circuits and Systems II: Express Briefs 67.11 (2020): 2692-2696. Abstract, §§ III-IV
Hadjis, Stefan, and Kunle Olukotun. "Tensorflow to cloud FPGAs: Tradeoffs for accelerating deep neural networks." 2019 29th International Conference on Field Programmable Logic and Applications (FPL). IEEE, 2019. Abstract, § II and cf. 1.
Ren, Mengye, et al. "Sbnet: Sparse blocks network for fast inference." 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. IEEE, 2018. § 2 last paragraph.
Goris et al., US 2021/0209764. ¶¶ 101-103
Stevens et al., US 2022/0066776. ¶ 57
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.
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/David A Hopkins/Primary Examiner, Art Unit 2188
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