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 .
This action is in response to communications filed on 01/16/2026.
Claims 11, 14-15, 18, 21-22, 29-30, 32 have been canceled.
Claims 1-10, 12-13, 16-17, 19-20, 23-28, 31, and 33-36 are pending and have been examined.
Claim Objections
Claims 1 and 19 are objected to because of the following informalities:
As per claim 1, it appears that the semicolon before “wherein the conditional execution of the directed graph is less computationally intensive than a non-conditional execution of the directed graph using the input tensor” in the last 2 lines should be replaced with a comma (or the limitation should be placed at the end of the “conditioning the execution…” step). This similarly applies to claim 19.
Appropriate correction is required.
Response to Arguments
Applicant's arguments filed in response to rejections under 35 US 101 have been fully considered but they are not persuasive.
Applicant argues in substance that execution data that determines how a computation is executed allegedly is not directed to a mental process or mathematics, or well-understood, routine, and conventional. However, examiner respectfully disagrees. As noted by applicant and in the claim, execution data is merely instruction for a computation, which is mental process or mathematical calculation. Applicant merely applies this mental process to a computer (e.g. to be performed by a computer using a packet). Note that storing information (e.g. in a packet) is insignificant extra solution activity (e.g. see 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 and note also PTAB Decision Pages 23-24).
Applicant further argues in substance that storing computation data in packet headers allegedly cannot be performed in the human mind. However, as noted above, storing information is insignificant extra solution activity (e.g. see MPEP 2106.05(g)). A human is capable of substituting a value for use in computations. Note also that a “packet” merely refers to a group of data, which a human can memorize.
Applicant further argues in substance that the human mind allegedly cannot bypass execution of computations and supply values derived previously. However, examiner respectfully disagrees. A human could make a decision to use a previous value instead of performing a computation, i.e. a mental process. The claims merely apply the judicial exception to a generic computer component (e.g. a computer or neural network, see MPEP 2106.05(f))).
Applicant further argues in substance that the claimed limitations allegedly would be considered significantly more than the judicial exception or a practical application because it allegedly improves operation of a machine learning model/computer, e.g. including selections of computations in real time. However, examiner respectfully disagrees. Selecting computations for suppression would benefit a human who is using a directed graph (which is merely nodes with edges, which can e.g. be performed in the mind or pen and paper) in real time along with computations (and instructions for those computations)/values in order to determine output tensors from the directed graph (which is calculated data). This would allow a human to perform less computations. As noted in the rejections, the claims merely apply the judicial exception to a generic computer component (e.g. a computer or neural network with data being stored in packets, see MPEP 2106.05(f))). The previously added dependent claims have similar issues as noted above.
As such, applicant’s arguments are not persuasive.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. For example, each of recited “means” are interpreted as “a processor”, “a memory”, and/or “computer-readable non-transitory medium” (e.g. in paragraphs 18 and 46).
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 1-10, 12-13, 16-17, 31, and 34 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1:
Claims 1-10, 12-13, 16-17, 31, and 34 are directed to a method. Therefore, the claims are all directed to one of the four statutory categories of patent eligible subject matter.
Step 2A Prong 1:
Claim 1 recites:
A computer-implemented method for executing a directed graph, wherein the directed graph is a neural network including a set of weights including at least one weight tensor in which each step is conducted by a processor (e.g. “In summary, we construe the claim preamble to mean performing operations using a processor wherein the purpose of the recited steps (processes) is executing a directed graph that represents a neural network that includes a set of weights that further includes a weight tensor”; PTAB Decision Page 10), comprising:
deriving a simplified version of the directed graph, wherein the directed graph is an original directed graph (e.g. a mental step encompassing a human making evaluations and judgments; note also PTAB Decision Page 12);
applying an input tensor to the directed graph, wherein the directed graph is the original directed graph and not the simplified version of the directed graph (e.g. a mental step encompassing a human making evaluations and judgments; note also PTAB Decision Page 12);
conditioning the execution of the directed graph by selecting, in real time and during the application of the input tensor to the directed graph, computations for suppression using the collection of execution data, wherein conditioning the execution of the directed graph comprises using the execution data itself as an instruction that determines how a computation associated with the weight tensor is executed and wherein the conditional execution of the directed graph is less computationally intensive than a non-conditional execution of the directed graph using the input tensor (e.g. a mental step encompassing a human making evaluations and calculations; PTAB Decision Page 12; note a human mind operates in real time);
obtaining an output tensor from the conditional execution of the directed graph (e.g. a mental step encompassing a human making evaluations and calculations; PTAB Decision Page 12)
Step 2A Prong 2:
This judicial exception is not integrated into a practical application because the additional elements are as follows:
“computer-implemented”; “neural network” (e.g. mere instructions to apply the abstract idea using generic computing elements; note PTAB Decision Page 19 and see MPEP 2106.05(f))
“and the set of weights are stored in a set of packets” (e.g. mere instructions to apply the abstract idea using generic computing elements; packets are a generic computing element associated with transferring data; note PTAB Decision Pages 17-18 “using generic computing elements or components … does not integrate the abstract idea into a practical application” and see MPEP 2106.05(f)).
“obtaining a collection of execution data during an execution of the simplified version of the directed graph” (e.g. insignificant extra solution activity; note PTAB Decision Page 13);
“storing the execution data in a set of headers of the set of packets, wherein the execution data is obtained and stored orthogonally to a main data flow of the directed graph” (e.g. insignificant extra solution activity; note PTAB Decision Page 13);
“obtaining, during the application of the input tensor to the directed graph and from a packet in the set of packets using a single address, both: (i) a subset of execution data from the execution data from a header of the packet; and (ii) a weight tensor of at least one weight tensor from a payload of the packet, whereby the execution data is available for utilization to condition execution of the directed graph in real time as the set of weights are retrieved from memory for computation” (e.g. insignificant extra solution activity; note PTAB Decision Page 13; note a human mind operates in real time);
Step 2B:
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are as follows:
“computer-implemented”; “neural network” (e.g. PTAB Decision Pages 23-24, “the additional elements are well-understood, routine, and conventional computer components and functions”, i.e. generic computer and/or computer component)
“and the set of weights are stored in a set of packets” (e.g. packets are a generic computing element associated with transferring data; PTAB Decision Pages 23-24, “the additional elements are well-understood, routine, and conventional computer components and functions”, i.e. generic computer component).
“obtaining a collection of execution data during an execution of the simplified version of the directed graph” (e.g. PTAB Decision Pages 23-24, “the additional elements are well-understood, routine, and conventional computer components and functions”, i.e. generic computer component);
“storing the execution data in a set of headers of the set of packets, wherein the execution data is obtained and stored orthogonally to a main data flow of the directed graph” (e.g. PTAB Decision Pages 23-24, “the additional elements are well-understood, routine, and conventional computer components and functions” and see e.g. 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);
“obtaining, during the application of the input tensor to the directed graph and from a packet in the set of packets using a single address, both: (i) a subset of execution data from the execution data from a header of the packet; and (ii) the weight tensor from the set of weights from a payload of the packet, whereby the execution data is available for utilization to condition execution of the directed graph in real time as the set of weights are retrieved from memory for computation” (e.g. PTAB Decision Pages 23-24, “the additional elements are well-understood, routine, and conventional computer components and functions”; Regarding the “header of the packet” and “payload of the packet”, notes also that these are well-understood, routine, and conventional computer components used in the transmission of data over a network, e.g. see Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362, buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014), etc.);
Dependent Claims
Dependent claims 2-10, 12-13, 16-17, 31, and 34 are also rejected under 35 USC 101 for the following reasons:
Claim 2 recites: “applying a pilot input tensor to the simplified version of the directed graph, to conduct the execution of the simplified version of the directed graph; wherein the input tensor is a live input tensor; the pilot input tensor and the live input tensor are not identical; and the pilot input tensor and the live input tensor are stochastically dependent” (e.g. a mental step encompassing a human making evaluations and computations; note PTAB Decision Page 27).
Claim 3 recites: “priming the directed graph for the conditional execution, prior to the conditional execution of the directed graph, using the stored execution data” (e.g. a mental step encompassing a human making evaluations and computations; note PTAB Decision Page 29; note also that “priming” is described in Spec [0039] as including “identifying the associated portion of directed graph data, packaging the execution and directed graph data into a data package, and storing the data package at a set location in memory” and storing and retrieving data in memory is insignificant extra solution activity, e.g. see 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).
Claim 4 recites:
- “the directed graph includes a set of vertices and a set of edges interconnecting the set of vertices”; this describes the conditions of the mathematical calculation of executing a directed graph
- “the set of edges of the directed graph are calculations involving a set of weights for the neural network”; this describes the conditions of the mathematical calculation of executing a directed graph
- “at least a subset of the set of vertices are weights for the neural network” ; this describes the conditions of the mathematical calculation of executing a directed graph. A neural network, generically recited, amounts to mere instructions to apply the abstract idea on a computer in Step 2A Prong 2. A neural network, in the field of machine learning, is also WURC under Step 2B.
- “the conditional execution of the directed graph produces an inference tensor”; executing a directed graph to produce an inference tensor is a mathematical calculation
- “and the inference tensor is a response of the neural network to the input tensor”; producing the inference tensor, as shown above, is a mathematical calculation. A neural network, generically recited, amounts to mere instructions to apply the abstract idea on a computer in Step 2A Prong 2. A neural network, in the field of machine learning, is also WURC under Step 2B.
Claim 5 recites “an edge in the set of edges is a calculation using a four dimensional tensor”; the claim is directed to a mathematical calculation.
Claim 6 recites “the deriving of the simplified version of the directed graph includes down-sampling the directed graph by a sampling factor; the simplified version of the directed graph is thereby a down-sampled version of the directed graph; a first complete set of tensors used for executing the simplified version of the directed graph has a rank; and a second complete set of tensors used for executing the directed graph has the rank”; each of these limitations describes the mathematical calculation.
Claim 7 recites “the down-sampling of the directed graph utilizes polynomial interpolation”; this recites a mathematical calculation.
Claim 8 recites “the deriving of the simplified version of the directed graph includes replacing a set of original values of the set of weights with a set of replacement values; and the simplified version of the directed graph has a same number of layers as the directed graph”; replacing values with replacement values can be performed by a human with pen and paper, and is thus a mental process.
Claim 9 recites “wherein the replacing comprises one of: reducing a number of bits used to represent the set of original values to obtain the set of replacement values; and calculating the set of replacement values using a set of exponents of the set of original values”; this recites a mathematical calculation.
Claim 10 recites “the collection of execution data includes a set of execution data values”; the collection of data is insufficient extra solution activity (mere data gathering) under Step 2A Prong 2 and WURC under Step 2B. It also recites “the set of execution data values and the set of vertices have uniquely corresponding elements; each uniquely corresponding vertex in the set of vertices produces a contribution to the inference tensor in response to a pilot input tensor; and each execution data value in the set of execution data values is proportional in magnitude to the contribution to the inference tensor of each uniquely corresponding vertex in the set of vertices”; these limitations recite a mental process
Claim 12 recites “generating a markup of the directed graph using the collection of execution data; storing the markup in a distributed set of memory locations; and conditioning an update of the set of weights using the markup” (e.g. generating a markup and conditioning the graph with the markup can be performed by a human with pen and paper, and is thus a mental process, and storing data in memory is insignificant extra solution activity, e.g. see 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).
Claim 13 recites “generating a markup of the directed graph using the collection of execution data; wherein the markup identifies a priority value for the weight tensor; and wherein conditioning of the execution of the directed graph uses the markup” (e.g. generating a markup and conditioning the graph with the markup can be performed by a human with pen and paper, and is thus a mental process).
Claim 16 recites “reducing an accuracy of the computation using the weight tensor based on the priority value”; this describes details of the mathematical calculation.
Claim 17 recites “obtaining a first subset of weights from the set of weights from the memory; replacing a set of original values of a second subset of the set of weights with a set of replacement values; and wherein the first subset of weights is selected using the markup”; replacing and selecting weights can be performed by a human with pen and paper, and are thus a mental process. Obtaining data from memory amounts to insufficient extra solution activity (mere data gathering) under Step 2A Prong 2 and WURC under Step 2B.
Claim 31 recites:
“storing a set of fixed values in the set of headers”; insignificant extra solution activity under Step 2A Prong 2; WURC under Step 2B
“suppressing the computations by providing fixed values from the set of fixed values as outputs of the computations”; mental process
Claim 34 recites:
“storing the original directed graph in a memory at a set of addresses”; insignificant extra solution activity under Step 2A Prong 2; WURC under Step 2B
“storing the simplified version of the directed graph in the memory using pointers to a subset of the set of addresses for shared portions of the original directed graph; insignificant extra solution activity under Step 2A Prong 2; WURC under Step 2B
Claims 19-20, 23, and 35 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1:
Claims 19-20, 23, and 35 are directed to a system. Therefore, the claims are all directed to one of the four statutory categories of patent eligible subject matter.
Step 2A Prong 1:
Claim 19 recites:
A system for executing a directed graph, wherein the directed graph is a neural network including a set of weights including at least one weight tensor (e.g. “In summary, we construe the claim preamble to mean performing operations using a processor wherein the purpose of the recited steps (processes) is executing a directed graph that represents a neural network that includes a set of weights that further includes a weight tensor”; PTAB Decision Page 10), comprising:
a means for deriving a simplified version of the directed graph, wherein the directed graph is an original directed graph (e.g. a mental step encompassing a human making evaluations and judgments; note also PTAB Decision Page 12);
a means for applying an input tensor to the directed graph, wherein the directed graph is the original directed graph and not the simplified version of the directed graph (e.g. a mental step encompassing a human making evaluations and judgments; note also PTAB Decision Page 12);
a means for conditioning the execution of the directed graph, in real time, during the application of the input tensor to the directed graph, by selecting, during the application of the input tensor to the directed graph, computations for suppression using the collection of execution data, and wherein the means for conditioning the execution of the directed graph substitutes the replacement value from the header as an output of a suppressed computation and wherein the conditional execution of the directed graph is less computationally intensive than a non-conditional execution of the directed graph using the input tensor (e.g. a mental step encompassing a human making evaluations and judgments; note also PTAB Decision Page 12; note a human mind operates in real time);
a means for obtaining an output tensor from the conditional execution of the directed graph (e.g. a mental step encompassing a human making evaluations and judgments; note also PTAB Decision Page 12);
Step 2A Prong 2:
This judicial exception is not integrated into a practical application because the additional elements are as follows:
“system”; “neural network” (e.g. mere instructions to apply the abstract idea using generic computing elements; note PTAB Decision Page 19 and see MPEP 2106.05(f))
“means for” (mere instructions to apply the abstract idea using generic computing elements; PTAB Decision Page 26, “the ‘means plus function’ analysis does not materially alter our claim interpretation and subject atter eligibility analysis. As we explain above, the computing components disclosed in the Specification for performing the process steps (the claimed functionality) are a processor and memory”)
“and the set of weights are stored in a set of packets (e.g. mere instructions to apply the abstract idea using generic computing elements; packets are a generic computing element associated with transferring data; note PTAB Decision Pages 17-18 “using generic computing elements or components … does not integrate the abstract idea into a practical application” and see MPEP 2106.05(f)).
“a means for obtaining a collection of execution data during an execution of the simplified version of the directed graph and orthogonally to the execution of the simplified version of the directed graph” (e.g. insignificant extra solution activity; note PTAB Decision Page 13; see MPEP 2106.05(g));
“a means for storing the execution data in memory, wherein the execution data is stored in a set of headers of the set of packets such that a subset of execution data from the execution data and a weight tensor from the set of weights are addressed using a single address by retrieving a packet from the set of packets, and wherein the execution data stored in a header of the packet includes a replacement value” (e.g. insignificant extra solution activity; note PTAB Decision Page 13; see MPEP 2106.05(g));
“as obtained from the set of headers of the set of packets while the set of weights are obtained from a set of payloads of the set of packets” (e.g. insignificant extra solution activity; note PTAB Decision Page 13; see MPEP 2106.05(g));
Step 2B:
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are as follows:
“system”; “neural network” (e.g. PTAB Decision Pages 23-24, “the additional elements are well-understood, routine, and conventional computer components and functions”, i.e. generic computer and/or computer component)
“means for” (e.g. PTAB Decision Page 26, “the ‘means plus function’ analysis does not materially alter our claim interpretation and subject atter eligibility analysis. As we explain above, the computing components disclosed in the Specification for performing the process steps (the claimed functionality) are a processor and memory”, i.e. generic computer components);
“and the set of weights are stored in a set of packets” (e.g. packets are a generic computing element associated with transferring data; PTAB Decision Pages 23-24, “the additional elements are well-understood, routine, and conventional computer components and functions”, i.e. generic computer component).
“a means for obtaining a collection of execution data during an execution of the simplified version of the directed graph and orthogonally to the execution of the simplified version of the directed graph” (e.g. PTAB Decision Pages 23-24, “the additional elements are well-understood, routine, and conventional computer components and functions”, i.e. generic computer component);
“a means for storing the execution data in memory, wherein the execution data is stored in a set of headers of the set of packets such that a subset of execution data from the execution data and a weight tensor from the set of weights are addressed using a single address by retrieving a packet from the set of packets, and wherein the execution data stored in a header of the packet includes a replacement value” (e.g. PTAB Decision Pages 23-24, “the additional elements are well-understood, routine, and conventional computer components and functions” and see e.g. 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);
“as obtained from the set of headers of the set of packets while the set of weights are obtained from a set of payloads of the set of packets” (e.g. PTAB Decision Pages 23-24, “the additional elements are well-understood, routine, and conventional computer components and functions”; Regarding the “header of the packet” and “payload of the packet”, notes also that these are well-understood, routine, and conventional computer components used in the transmission of data over a network, e.g. see Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362, buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014), etc.);
Dependent Claims
Dependent claims 20, 23, and 35 are also rejected under 35 USC 101 for the following reasons:
Claim 20 recites: “a means for priming the directed graph for the conditional execution, prior to the conditional execution of the directed graph, using the execution data” (e.g. a mental step encompassing a human making evaluations and computations; note PTAB Decision Page 29; note also that “priming” is described in Spec [0039] as including “identifying the associated portion of directed graph data, packaging the execution and directed graph data into a data package, and storing the data package at a set location in memory” and storing and retrieving data in memory is insignificant extra solution activity, e.g. see 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).
Claim 23 recites: “a means for generating a markup of the directed graph using the collection of execution data; a means for storing the markup in a distributed set of memory locations; and a means for conditioning an update of the directed graph using the markup” (e.g. generating a markup and conditioning the graph with the markup can be performed by a human with pen and paper, and is thus a mental process, and storing data in memory is insignificant extra solution activity, e.g. see 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).
Claim 35 recites:
“a memory storing the original directed graph in a memory at a set of addresses” (e.g. storing data in memory is insignificant extra solution activity, e.g. see 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).
“wherein the memory stores the simplified version of the directed graph using pointers to a subset of the set of addresses for shared portions of the original directed graph (e.g. storing data in memory is insignificant extra solution activity, e.g. see 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).
Claims 24-28, 33, and 36 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1:
Claims 24-28, 33, and 36 are directed to a method. Therefore, the claims are all directed to one of the four statutory categories of patent eligible subject matter.
Step 2A Prong 1:
Claim 24 recites:
A computer-implemented method for generating an inference from a neural network including a set of weights including a weight tensor, in which each step is conducted by a processor (e.g. PTAB Decision Page 9, “The intended purpose of the ‘method’ … does not further limit the claim”; here the intended purpose is “for generating an inference from a neural network” ), comprising:
deriving a simplified version of the neural network, wherein the neural network is an original neural network (e.g. a mental step encompassing a human making evaluations and judgments; note also PTAB Decision Page 12);
applying an input tensor to the neural network, wherein the neural network is the original neural network and not the simplified version of the neural network (e.g. a mental step encompassing a human making evaluations and judgments; note also PTAB Decision Page 12);
conditioning the execution of the neural network by selecting, in real time and during the application of the input tensor to the neural network, computations for conditional execution using the collection of execution data (e.g. a mental step encompassing a human making evaluations and judgments; note also PTAB Decision Page 12; note a human mind operates in real time);
obtaining the inference from the execution of the neural network; wherein: the execution of the neural network is conditioned using the execution data; and conditioning the execution of the neural network comprises bypassing execution of a computation associated with the weight tensor and supplying, as an output of the bypassed computation, a value stored as execution data; the conditional computation of the neural network is less computationally intensive than a non-conditional computation of the neural network using the input tensor” (e.g. a mental step encompassing a human making evaluations and judgments; note also PTAB Decision Page 12; note also that “less computationally intensive” refers merely to an intended purpose);
Step 2A Prong 2:
This judicial exception is not integrated into a practical application because the additional elements are as follows:
“computer-implemented”; “neural network” (e.g. mere instructions to apply the abstract idea using generic computing elements; note PTAB Decision Page 19 and see MPEP 2106.05(f))
“and the set of weights are stored in a set of packets” (e.g. mere instructions to apply the abstract idea using generic computing elements; packets are a generic computing element associated with transferring data; note PTAB Decision Pages 17-18 “using generic computing elements or components … does not integrate the abstract idea into a practical application” and see MPEP 2106.05(f)).
“obtaining a collection of execution data during an execution of the neural network, wherein the collection of execution data is obtained and stored: (i) orthogonally to a main data flow of the neural network; and (ii) in a set of headers of the set of packets” (e.g. insignificant extra solution activity; note PTAB Decision Page 13);
“storing the execution data in a set of headers of the set of packets, wherein the execution data is obtained and stored orthogonally to a main data flow of the directed graph”; insignificant extra solution activity (“these features are extra-solution activity to the central idea of claim 1”; PTAB Decision Page 13)
“obtaining, during the application of the input tensor to the neural network and from a packet in the set of packets using a single address, both: (i) a subset of execution data from the execution data from a header of the packet; and (ii) the weight tensor from the set of weights from a payload of the packet, whereby the execution data is available for utilization to condition execution of the directed graph in real time as the set of weights are retrieved from memory for computation” (e.g. insignificant extra solution activity; note PTAB Decision Page 13);
Step 2B:
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are as follows:
“computer-implemented”; “neural network” (e.g. PTAB Decision Pages 23-24, “the additional elements are well-understood, routine, and conventional computer components and functions”, i.e. generic computer and/or computer component)
“and the set of weights are stored in a set of packets, comprising” (e.g. packets are a generic computing element associated with transferring data; PTAB Decision Pages 23-24, “the additional elements are well-understood, routine, and conventional computer components and functions”, i.e. generic computer component).
“obtaining a collection of execution data during an execution of the neural network, wherein the collection of execution data is obtained and stored: (i) orthogonally to a main data flow of the neural network; and (ii) in a set of headers of the set of packets” (e.g. PTAB Decision Pages 23-24, “the additional elements are well-understood, routine, and conventional computer components and functions”, i.e. generic computer component);
“storing the execution data in a set of headers of the set of packets, wherein the execution data is obtained and stored orthogonally to a main data flow of the directed graph” (e.g. PTAB Decision Pages 23-24, “the additional elements are well-understood, routine, and conventional computer components and functions” and see e.g. 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);
“obtaining, during the application of the input tensor to the neural network and from a packet in the set of packets using a single address, both: (i) a subset of execution data from the execution data from a header of the packet; and (ii) the weight tensor from the set of weights from a payload of the packet, whereby the execution data is available for utilization to condition execution of the directed graph in real time as the set of weights are retrieved from memory for computation” (e.g. PTAB Decision Pages 23-24, “the additional elements are well-understood, routine, and conventional computer components and functions”; Regarding the “header of the packet” and “payload of the packet”, notes also that these are well-understood, routine, and conventional computer components used in the transmission of data over a network, e.g. see Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362, buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014), etc.);
Dependent Claims
Dependent claims 25-28, 33, and 36 are also rejected under 35 USC 101 for the following reasons:
Claim 25 recites: “applying a first input tensor to the simplified version of the neural network, to conduct the execution of the simplified version of the neural network; wherein the input tensor is a second input tensor; wherein the first input tensor and the second input tensor are not identical; and the first input tensor and the second input tensor are stochastically dependent” (e.g. a mental step encompassing a human making evaluations and computations; note PTAB Decision Page 27).
Claim 26 recites: “priming the directed graph for the conditional execution, prior to the conditional execution of the directed graph, using the stored execution data” (e.g. a mental step encompassing a human making evaluations and computations; note PTAB Decision Page 29; note also that “priming” is described in Spec [0039] as including “identifying the associated portion of directed graph data, packaging the execution and directed graph data into a data package, and storing the data package at a set location in memory” and storing and retrieving data in memory is insignificant extra solution activity, e.g. see 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).
Claim 27 recites “the deriving of the simplified version of the neural network includes down-sampling a set of weights of the neural network by a sampling factor” (e.g. each of these limitations describes a mathematical calculation, which can be performed by a human).
Claim 28 recites “the deriving of the simplified version of the neural network includes replacing a set of weight values of the set of weights of the neural network with a set of replacement values (e.g. replacing values with replacement values can be performed by a human with pen and paper and is thus a mental process).
Claim 33 recites:
“storing a set of fixed values in the set of headers” (e.g. storing data is insignificant extra solution activity, e.g. see 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).
“suppressing the computations by providing fixed values from the set of fixed values as outputs of the computations” (e.g. encompasses a human performing evaluations)
Claim 36 recites:
“storing the original neural network in the memory at a set of addresses (e.g. storing data in memory is insignificant extra solution activity, e.g. see 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).
“storing the simplified version of the neural network in the memory using pointers to a subset of the set of addresses for shared portions of the original direct neural network (e.g. storing data in memory is insignificant extra solution activity, e.g. see 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).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/W.W/Examiner, Art Unit 2144 07/29/2026
/TAMARA T KYLE/Supervisory Patent Examiner, Art Unit 2144
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