DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Style
In this action unitalicized bold is used for claim language, while italicized bold is used for emphasis.
Applicant Reply
“The claims may be amended by canceling particular claims, by presenting new claims, or by rewriting particular claims as indicated in 37 CFR 1.121(c). The requirements of 37 CFR 1.111(b) must be complied with by pointing out the specific distinctions believed to render the claims patentable over the references in presenting arguments in support of new claims and amendments. . . . The prompt development of a clear issue requires that the replies of the applicant meet the objections to and rejections of the claims. Applicant should also specifically point out the support for any amendments made to the disclosure. See MPEP § 2163.06. . . . An amendment which does not comply with the provisions of 37 CFR 1.121(b), (c), (d), and (h) may be held not fully responsive. See MPEP § 714.” MPEP § 714.02. Generic statements or listing of numerous paragraphs do not “specifically point out the support for” claim amendments. “With respect to newly added or amended claims, applicant should show support in the original disclosure for the new or amended claims. See, e.g., Hyatt v. Dudas, 492 F.3d 1365, 1370, n.4, 83 USPQ2d 1373, 1376, n.4 (Fed. Cir. 2007) (citing MPEP § 2163.04 which provides that a ‘simple statement such as ‘applicant has not pointed out where the new (or amended) claim is supported, nor does there appear to be a written description of the claim limitation ‘___’ in the application as filed’ may be sufficient where the claim is a new or amended claim, the support for the limitation is not apparent, and applicant has not pointed out where the limitation is supported.’)” MPEP § 2163(II)(A).
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 1-6, 9-13, and 15-23 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) and the claims as a whole, considering all claim elements both individually and in combination, do not amount to significantly more.
Step 1: Is the claim to a process, machine, manufacture, or composition of matter?
All claims are found to be directed to one of the four statutory categories, unless otherwise indicated in this action.
Step 2A Prongs One and Two (Alice Step 1): According to Office guidance, claims that read on math do not recite an abstract idea at step 2A1, when the claims fail to refer to the math by name.1 The MPEP also equates “recit[ing] a judicial exception” with “state[ing]” or “describ[ing]” an abstract idea in the claims.2 Consistent with this guidance, an abstract idea may be first recited in a dependent claim even though the independent claims read on that abstract idea. Claim limitations which recite any of the abstract idea groupings set forth in the manual are found to be directed, as a whole, to an abstract idea unless otherwise indicated.3 The claims do not recite additional elements that integrate the abstract ideas into a practical application.4 To confer patent eligibility to an otherwise abstract idea, claims may recite a specific means or method of solving a specific problem in a technological field.5
Independent Claims
Claim 1 recites: “1. A method comprising: (The inventive concept as a whole, is directed to the mental process of identifying the type of training data to be added to a generic model, as recited in claims 1 and 6. (“[I]dentifying . . . an area of the information graph in which to increase an inclusion of the information graph” “wherein the area of the information graph in which to increase the inclusion is identified based on a signal from a human user who has reviewed the information graph[.]”) As can be seen from this language, the claims themselves contemplate a mental process. While the claims also recite the application of other mental processes using generic computer components as explained below, the inventive concept is directed to a mental process in the form of expert determining which training data to add for the purpose of improving a model.) constructing, by a processing system including at least one processor, an information graph that organizes a set of training data into a plurality of entities and a plurality of relationships between the plurality of entities; (Constructing an information graph that organizes training data into entities and relationships between entities reads a mental/mathematical process. Using “a processing system including at least one processor” is merely an instruction to apply the exception recited in the claims using generic computer components operating their ordinary capacity. All subsequent claim language directed to implementation of abstract ideas on the recited processing system is found to be merely an instruction to apply an exception using generic computer components in their ordinary capacity. For brevity, this is not repeated each time use of a generic computing component is recited.) identifying, by the processing system, an area of the information graph in which to increase an inclusion of the information graph, wherein the inclusion comprises a consideration of a population that is targeted for greater inclusion in the information graph; (This reads on a mental process. Further, claim 6 is taken as an admission by Applicant that this step can be feasibly performed in the human mind.) collecting, by the processing system from an auxiliary data source, auxiliary data about the population for use in increasing the inclusion of the information graph, (Mere data gathering is extra-solution activity. Limiting the data to “auxiliary data about the population” merely limits application of the abstract idea to a particular field of use. “For instance, a data gathering step that is limited to a particular data source (such as the Internet) or a particular type of data (such as power grid data or XML tags) could be considered to be both insignificant extra-solution activity and a field of use limitation. See, e.g., Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (limiting use of abstract idea to the Internet); Electric Power, 830 F.3d at 1354, 119 USPQ2d at 1742 (limiting application of abstract idea to power grid data); Intellectual Ventures I LLC v. Erie Indem. Co., 850 F.3d 1315, 1328-29, 121 USPQ2d 1928, 1939 (Fed. Cir. 2017) (limiting use of abstract idea to use with XML tags).” MPEP § 2106.05(h). Note also that “for use in increasing the inclusion of the information graph” is written as an intended use. Intended use language is explained in MPEP §§ 2103 and 2111.02. “Claim scope is not limited by claim language that suggests or makes optional but does not require steps to be performed, or by claim language that does not limit a claim to a particular structure.” MPEP § 2111.04. See also Elec. Power Grp., LLC v. Alstom, S.A., 830 F.3d 1350, 1353-1354 (Fed. Cir. 2016).) wherein the auxiliary data source is selected from among a plurality of auxiliary data sources, and wherein each auxiliary data source of the plurality of auxiliary data sources comprises a database that contains data about a different, specific population comprising a group of people who share a characteristic; (The operation of selecting a type of data to use for training the model, from various available types of data, is a mental process. Limiting to a type of data is merely an instruction to apply the abstract idea in a data environment associated with the chosen field of use. Storing and accessing the selected type of data is mere extra-solution activity. See also Elec. Power Grp., LLC v. Alstom, S.A., 830 F.3d 1350, 1353-1354 (Fed. Cir. 2016) distinguishing the independent steps of collecting and analyzing data using computers as tools, from claims focused on an improvement in computers as tools.) utilizing, by the processing system, the auxiliary data to increase the inclusion of the information graph, to generate an updated information graph (Utilizing new information to augment existing information an information graph reads on a mental and on a mathematical relationship. Specifically, this language reads on utilizing additional information to increase in information stored in a graphical format.) training, by the processing system, a machine learning model using the updated information graph as training data to generate a trained machine learning model; (This reads one of the operations carried out as part of using a generic machine learning technique (training a generic model) to implement the claimed abstract ideas limited to a particular date environment consistent with the desired field of use.) providing, by the processing system, a test input to the trained machine learning model to generate a test output that incorporates information from the auxiliary data; (Testing a model using additional data, including data input and data output, is mere extra-solution activity.) generating, by the processing system in response to determining that the test output satisfies an inclusion criterion, a runtime output using the trained machine learning model, wherein the runtime output is generated in response to input data obtained from a source other than a source of the training data and a source of the test input,; (Determining the test output based on the new data satisfies an inclusion criteria is a mental process. Generating a runtime output based on a given dataset is part of a mere an instruction to apply an exception using generic computer components.) and wherein an inclusion of the runtime output is increased by the training using the updated information graph relative to training using the information graph prior to the utilizing (As best understood, this language is meant to assert an increased accuracy in the runtime output with respect to the population that is targeted for greater inclusion. This recites an intended use for the mental/mathematical processes above. Intended use language is explained in MPEP §§ 2103 and 2111.02. “Claim scope is not limited by claim language that suggests or makes optional but does not require steps to be performed, or by claim language that does not limit a claim to a particular structure.” MPEP § 2111.04. Further, while selection of the proper training data may improve accuracy of the model, any improvement would result from the collection of data properly identified in the identifying step. Since the identifying step is disclosed as being carried out by asking a “human user”, it would be the result of an undisclosed mental process. “In short, first the specification should be evaluated to determine if the disclosure provides sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. The specification need not explicitly set forth the improvement, but it must describe the invention such that the improvement would be apparent to one of ordinary skill in the art. Conversely, if the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology. Second, if the specification sets forth an improvement in technology, the claim must be evaluated to ensure that the claim itself reflects the disclosed improvement. That is, the claim includes the components or steps of the invention that provide the improvement described in the specification. . . . It should be noted that while this consideration is often referred to in an abbreviated manner as the ‘improvements consideration,’ the word ‘improvements’ in the context of this consideration is limited to improvements to the functioning of a computer or any other technology/technical field, whether in Step 2A Prong Two or in Step 2B.” MPEP 2106.04(d)(1). See also Koninklijke KPN N.V. v. Gemalto M2M GmbH, 942 F.3d 1143, 1150-1152 (Fed. Cir. 2019).) receiving, by the processing system, user feedback regarding the runtime output; (The operation of receiving user feedback, which reads on receiving data, is mere extra-solution activity.) and determining, by the processing system in response to the user feedback, whether to repeat the collecting, the utilizing, the providing, and the generating to further increase the inclusion of the runtime output. (Determining whether to update the model by adding auxiliary data to further train and subsequently test the model in response to user feedback (data) reads on a mental process.)
Independent claim 19 recites a manufacture implementing the process of claim 1. Therefore, the same analysis applies. In addition, the claim recites “A non-transitory computer-readable medium storing instructions which, when executed by a processing system including at least one processor, cause the processing system to perform operations[.]” (This is a mere instruction to apply the judicial exceptions recited in the body of the claims using generic computer components.)
Independent claim 20 recites a machine implementing the process of claim 1. Therefore, the same analysis applies. In addition, the claim recites “A device comprising: a processing system including at least one processor; and a non-transitory computer-readable medium storing instructions which, when executed by the processing system, cause the processing system to perform operations[.]” (This is a mere instruction to apply the judicial exceptions recited in the body of the claims using generic computer components.)
Step 2B (Alice Step 2): The rejected claims do not recite additional elements that amount to significantly more than the judicial exception.
All additional limitations that do not integrate the claimed judicial exception into a practical application also fail to amount to significantly more, for the reasons given at step 2A2. All limitations found to be extra-solution activity at step 2A2 are found to be WURC, including limitations that read on mere data gathering, data storage, and data input/output/transfer. The language of claim 1 also includes testing of a machine learning model. (“providing, by the processing system, a test input to the trained machine learning model to generate a test output that incorporates information from the auxiliary data”) No section in the MPEP indicates that any case would support a finding that testing a machine learning model is WURC, though generic input/output to/from the model while testing do read on operations found to be WURC as indicated above. However, testing a machine learning model is WURC based on the state of the art as of the effective filing date. See Buduma (Fundamentals of Deep Learning; 2017), PP. 27-34 describing how test and validations datasets are ordinarily used as part of creating and improving machine learning models. Claim 1 also recites “collecting, by the processing system from an auxiliary data source, auxiliary data about the population for use in increasing the inclusion of the information graph” “wherein the auxiliary data source is selected from among a plurality of auxiliary data sources, and wherein each auxiliary data source of the plurality of auxiliary data sources comprises a database that contains data about a different, specific population comprising a group of people who share a characteristic” “receiving, by the processing system, user feedback regarding the runtime output[.]” The collecting, sending, storing, and retrieving aspects found to be extra-solution activity above are WURC. This finding is based on cases which have recognized that generic input-output operations, repetitive processing operations, and storage operations are WURC.6 Other aspects of generic computing have also been found to be WURC.7 Further, the description itself may provide support for a finding that claim elements are WURC. The analysis under § 112(a) as to whether a claim element is “so well-known that it need not be described in detail in the patent specification” is the same as the analysis as to whether the claim element is widely prevalent or in common use.8 Similarly, generic descriptions in the Specification of claimed components and features has been found to support a conclusion that the claimed components were conventional.9 Improvements to the relevant technology may support a finding that the claims include a patent eligible inventive concept. But some mechanism that results in any asserted improvements must be recited in the claim, and the Specification must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing the improvement.10 This applies equally to the dependent claims below.
Dependent Claims:
2. The method of claim 1, wherein the information graph comprises: a plurality of nodes, each node of the plurality of nodes representing an entity of the plurality of entities; and a plurality of edges connecting the plurality of nodes, each edge of the plurality of edges representing a relationship of the plurality of relationships that exists between a pair of entities of the plurality of entities which are represented by a pair of nodes of the plurality of nodes to which the each edge is connected. (This merely limits the structure of a graph which is part of a mental process, capable of construction and use in the human mind with the aid of a pencil and paper.)
3. The method of claim 2, wherein the each edge is labeled to describe a nature of the relationship. (This merely limits the structure of a graph which is part of a mental process, capable of construction and use in the human mind with the aid of a pencil and paper.)
4. The method of claim 3, wherein the each edge is directed to show a direction of the relationship. (This merely limits the structure of a graph which is part of a mental process, capable of construction and use in the human mind with the aid of a pencil and paper.)
5. The method of claim 2, wherein the utilizing comprises at least one of: adding a new node to the plurality of nodes, wherein the new node represents a new entity that is present in the auxiliary data, adding a weight to a new node or an existing node of the plurality of nodes based on information in the auxiliary data, updating the information graph to reflect a relationship between two nodes of the plurality of nodes, wherein the relationship is newly discovered through the auxiliary data, adding a feature to the information graph, or adding a new category of data to the information graph. (This merely limits the structure of a graph which is part of a mental process, capable of construction and use in the human mind with the aid of a pencil and paper.)
6. The method of claim 1, wherein the area of the information graph in which to increase the inclusion is identified based on a signal from a human user who has reviewed the information graph. (Sending of a signal is mere extra solution activity and WURC. See MPEP § 2106.05(d)(II) cited above.)
7. The method of claim 1, wherein the area of the information graph in which to increase the inclusion is identified based on contextual information about: the machine learning model. (This is part of the mental process.)
8. The method of claim 1, wherein the area of the information graph in which to increase the inclusion is sparse relative to other areas of the information graph. (This merely limits the structure of the graph, which can be implemented in the human mind as part of a mental process with the aid of a pencil and paper.)
9. The method of claim 1, wherein the characteristic is at least one of: a gender of the group, a race of the group, a nationality of the group, a religion of the group, or an age of the group. (This merely limits the particular data environment to a field of use.)
10. The method of claim 1, wherein the characteristic is at least one of: an occupation of the group, an education of the group, or an interest of the group. (This merely limits the particular data environment to a field of use.)
11. The method of claim 1, wherein the characteristic is at least one of: a gender of the group, a race of the group, a nationality of the group, a religion of the group, an age of the group, an occupation of the group, an education of the group, or an interest of the group. (This merely limits the particular data environment to a field of use.)
12. The method of claim 1, further comprising: repeating, by the processing system subsequent to the providing but prior to the generating, the collecting, the utilizing, and the providing in response to determining that the test output does not satisfy the inclusion criterion, until the inclusion criterion is satisfied by the test output. (This reads on iteratively repeating the steps found to be abstract ideas. Repeating steps, without some inventive concept, is mere extra solution activity (and WURC). “The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. . . ii. Performing repetitive calculations, Flook, 437 U.S. at 594, 198 USPQ2d at 199 (recomputing or readjusting alarm limit values); Bancorp Services v. Sun Life, 687 F.3d 1266, 1278, 103 USPQ2d 1425, 1433 (Fed. Cir. 2012) ("The computer required by some of Bancorp’s claims is employed only for its most basic function, the performance of repetitive calculations, and as such does not impose meaningful limits on the scope of those claims.")” MPEP § 2106.05(d)(2).)
13. The method of claim 1, wherein the auxiliary data source is updated based on the runtime output. (Updating the data used based on the output of a model used as part of a mental process is merely extra solution activity (and WURC). For Berkheimer evidence on sending, receiving, storing, and retrieving data, see MPEP § 2106.05(d)(II), cited below.)
15. The method of claim 1, further comprising: retraining, by the processing system, the trained machine learning model using additional auxiliary data when the test output fails to satisfy the inclusion criterion. (This reads on repeating training steps. Merely repeating steps is mere extra solution activity (and WURC). “The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. . . ii. Performing repetitive calculations, Flook, 437 U.S. at 594, 198 USPQ2d at 199 (recomputing or readjusting alarm limit values); Bancorp Services v. Sun Life, 687 F.3d 1266, 1278, 103 USPQ2d 1425, 1433 (Fed. Cir. 2012) ("The computer required by some of Bancorp’s claims is employed only for its most basic function, the performance of repetitive calculations, and as such does not impose meaningful limits on the scope of those claims.")” MPEP § 2106.05(d)(2).)
16. The method of claim 15, wherein the retraining is performed at a checkpoint in a training process of the trained machine learning model. (Denoting the retraining as being performed at a “checkpoint” is not limiting because it does not require additional steps to be performed or limit to a particular structure. “Claim scope is not limited by claim language that suggests or makes optional but does not require steps to be performed, or by claim language that does not limit a claim to a particular structure.” MPEP § 2111.04.)
17. The method of claim 1, wherein the trained machine learning model is one of: a deep learning model or a neural network. (This merely limits to a direction to apply the abstract idea on generic computer components, specifically on a deep learning model or a neural network. Note also that deep learning models generally refer to neural networks.)
18. The method of claim 1, wherein the inclusion of the runtime output is further increased utilizing additional auxiliary data. (Intended use language is explained in MPEP §§ 2103 and 2111.02. “Claim scope is not limited by claim language that suggests or makes optional but does not require steps to be performed, or by claim language that does not limit a claim to a particular structure.” MPEP § 2111.04.)
21. The method of claim 1, wherein the auxiliary data includes attributes that were not present in the training data. (This merely changes the scope of the particular data environment associated with the field of use.)
22. The method of claim 1, wherein the trained machine learning model is trained to assist with an operation of a self-driving vehicle. (This is merely an instruction to apply the abstract idea using a data environment consistent with a given field of use.)
23. The method of claim 1, wherein the trained machine learning model is trained to select media for adaptation for an international market. (This is merely an instruction to apply the abstract idea using a data environment consistent with a given field of use.)
All dependent claims are rejected as containing the material of the claims from which they depend.
Response to Arguments
Applicant's arguments filed 10/10/2025 have been fully considered but they are not persuasive.
Rejections under § 101
As best understood, Applicant’s asserts that the claims are patentable based on application of the machine or transform test. See Rem. 8 (citing MPEP § 2106.05(c)). Examiner is unaware of any legal basis for determining that abstract ideas implemented on a computer result in a “transform” under the machine or transform test. Despite the request in the previous office action, the Remarks do not include a citation to any specific language in the MPEP or any case holding that mathematical operations or mental processes carried out on a conventional computer to “transform a machine learning model to increase inclusion of a runtime output” result in a “transform” within the meaning of the machine or transform test. See Rem. 8 and Final Action (FA) 24. Similarly, the Remarks fail to include the requested citation indicating that the machine or transform test would be dispositive of claims otherwise directed to using a generic machine learning model in a particular data environment.11 See Rem. 8 and FA 24.
The Remarks assert the claims integrate the judicial exception into a practical application in the form of increased inclusion in a trained model. Rem. 8-9 (“A claim may also integrate a judicial exception into a practical application if the claim improves the functioning of a computer or other technology or technological field (MPEP 2106.04(d)). In the instant case, examples of the present disclosure improve the technological field of machine learning by mitigating or minimizing algorithmic bias in machine learning outputs.”) As a factual matter, Applicant is correct that additional training data of a given domain may increase model accuracy in that domain. On this point, there is no dispute. But there is a difference in a patent eligible technical solution and a patent ineligible instruction to apply a mental process for identifying a solution, and instruction to apply the mental process using conventional computer components. The claims read on the latter category. Specifically, the claims read on “identifying . . . an area of the information graph in which to increase inclusion” “based on a signal from a human user who has reviewed the information graph” and collecting the corresponding data. See claims 1 and 6. The solution as it were, is getting a person to figure out what data should be added to a generic graph machine model combination, and using ordinary I/O operations to acquire the data from generic computing components. Simply put, getting a person to select the right data for improving the model is not a technical solution.
Rejections under §§ 112a and 112b
All rejections under these sections are withdrawn in response to claim amendments.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PAUL M KNIGHT whose telephone number is (571) 272-8646. The examiner can normally be reached Monday - Friday 9-5 ET.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Michelle Bechtold can be reached on (571) 431-0762. The fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300.
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PAUL M. KNIGHTExaminerArt Unit 2148
/PAUL M KNIGHT/Examiner, Art Unit 2148
1 This distinction between claims which read on math and claims which recite an abstract idea is based on official USPTO Guidance. The 2019 Subject Matter Eligibility (SME) Examples instructs examiners that a claim reciting “training the neural network” where the background describes training as “using stochastic learning with backpropagation which is a type of machine learning algorithm that uses the gradient of a mathematical loss function to adjust the weights of the network” “does not recite any mathematical relationships, formulas, or calculations.” See 2019 SME Example 39, PP. 8-9 (emphasis added). In this example, the plain meaning of “training the neural network” read in light of the disclosure reads on backpropagation using the gradient of a mathematical loss function. See MPEP § 2111.01. In contrast, the 2024 SME Examples instructs examiners that a claim reciting “training, by the computer, the ANN . . . wherein the selected training algorithm includes a backpropagation algorithm and a gradient descent algorithm” does recite an abstract idea because “[t]he plain meaning of [backpropagation algorithm and gradient descent algorithm] are optimization algorithms, which compute neural network parameters using a series of mathematical calculations.” 2024 PEG Example 47, PP. 4-6. The Memorandum of August 4, 2025; Reminders on evaluating subject matter eligibility of claims under 35 U.S.C. 101, P. 3 also directs examiners that “training the neural network” recited in Example 39 merely “involve[s] . . . mathematical concepts” and contrasts claim 2 of example 47 as “referring to [specific] mathematical calculations by name[.]” (Emphasis added.)
2 “For instance, the claims in Diehr . . . clearly stated a mathematical equation . . . and the claims in Mayo . . . clearly stated laws of nature . . . such that the claims ‘set forth’ an identifiable judicial exception. Alternatively, the claims in Alice Corp. . . . described the concept of intermediated settlement without ever explicitly using the words ‘intermediated’ or ‘settlement.’” MPEP § 2106.04(II)(A).
3 “By grouping the abstract ideas, the examiners’ focus has been shifted from relying on individual cases to generally applying the wide body of case law spanning all technologies and claim types. . . . If the identified limitation(s) falls within at least one of the groupings of abstract ideas, it is reasonable to conclude that the claim recites an abstract idea in Step 2A Prong One.” MPEP § 2106.04(a). See also MPEP 2104(a)(2).
4 Step 2A prongs one and two are evaluated individually, consistent with the framework in the MPEP. Evaluation of relationships between abstract ideas and additional elements in one location promotes clarity of the record.
5 “In short, first the specification should be evaluated to determine if the disclosure provides sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. The specification need not explicitly set forth the improvement, but it must describe the invention such that the improvement would be apparent to one of ordinary skill in the art. Conversely, if the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology. Second, if the specification sets forth an improvement in technology, the claim must be evaluated to ensure that the claim itself reflects the disclosed improvement. That is, the claim includes the components or steps of the invention that provide the improvement described in the specification. . . . It should be noted that while this consideration is often referred to in an abbreviated manner as the ‘improvements consideration,’ the word ‘improvements’ in the context of this consideration is limited to improvements to the functioning of a computer or any other technology/technical field, whether in Step 2A Prong Two or in Step 2B.” MPEP 2106.04(d)(1). See also Koninklijke KPN N.V. v. Gemalto M2M GmbH, 942 F.3d 1143, 1150-1152 (Fed. Cir. 2019).
6 See MPEP § 2106.05(d)(II) listing operations including “receiving or transmitting data,” “storing and retrieving data in memory,” and “performing repetitive calculations” as WURC.
7 “But ‘[f]or the role of a computer in a computer-implemented invention to be deemed meaningful in the context of this analysis, it must involve more than performance of 'well-understood, routine, [and] conventional activities previously known to the industry.’ Content Extraction, 776 F.3d at 1347-48 (quoting Alice, 134 S. Ct at 2359). Here, the server simply receives data, ‘extract[s] classification information . . . from the received data,’ and ‘stor[es] the digital images . . . taking into consideration the classification information.’ See ‘295 patent, col. 10 ll. 1-17 (Claim 17). . . . These steps fall squarely within our precedent finding generic computer components insufficient to add an inventive concept to an otherwise abstract idea. Alice, 134 S. Ct. at 2360 (‘Nearly every computer will include a 'communications controller' and a 'data storage unit' capable of performing the basic calculation, storage, and transmission functions required by the method claims.’); Content Extraction, 776 F.3d at 1345, 1348 (‘storing information’ into memory, and using a computer to ‘translate the shapes on a physical page into typeface characters,’ insufficient confer patent eligibility); Mortg. Grader, 811 F.3d at 1324-25 (generic computer components such as an ‘interface,’ ‘network,’ and ‘database,’ fail to satisfy the inventive concept requirement); Intellectual Ventures I, 792 F.3d at 1368 (a ‘database’ and ‘a communication medium’ ‘are all generic computer elements’); BuySAFE v. Google, Inc., 765 F.3d 1350, 1355 (Fed. Cir. 2014) (‘That a computer receives and sends the information over a network—with no further specification—is not even arguably inventive.’).” TLI Commc'ns LLC v. AV Auto., LLC, 823 F.3d 607, 614 (Fed. Cir. 2016), Emphasis Added.
8 “The analysis as to whether an element (or combination of elements) is widely prevalent or in common use is the same as the analysis under 35 U.S.C. 112(a) as to whether an element is so well-known that it need not be described in detail in the patent specification. See Genetic Techs. Ltd. v. Merial LLC, 818 F.3d 1369, 1377, 118 USPQ2d 1541, 1546 (Fed. Cir. 2016) (supporting the position that amplification was well-understood, routine, conventional for purposes of subject matter eligibility by observing that the patentee expressly argued during prosecution of the application that amplification was a technique readily practiced by those skilled in the art to overcome the rejection of the claim under 35 U.S.C. 112, first paragraph)[.]” MPEP § 2106.05(d)(I).
9 “Similarly, claim elements or combinations of claim elements that are routine, conventional or well-understood cannot transform the claims. (Citing BSG Tech LLC v. BuySeasons, Inc., 899 F.3d 1281, 1290-1291 (Fed. Cir. 2018)). When the patent's specification ‘describes the components and features listed in the claims generically,’ it ‘support[s] the conclusion that these components and features are conventional.’ Weisner v. Google LLC, 51 F.4th 1073, 1083-84 (Fed. Cir. 2022); see also Beteiro, LLC v. DraftKings Inc., 104 F.4th 1350, 1357-58 (Fed. Cir. 2024).” Broadband iTV, Inc. v. Amazon.com, Inc., 113 F.4th 1359 (Fed. Cir. 2024)
10 “If it is asserted that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes, a technical explanation as to how to implement the invention should be present in the specification. That is, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. The specification need not explicitly set forth the improvement, but it must describe the invention such that the improvement would be apparent to one of ordinary skill in the art. Conversely, if the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology.” MPEP § 2106.05(a).
11 “[I]f a claim fails the Alice/Mayo test . . . then the claim is ineligible even if it passes the M-or-T test.” MPEP § 2106.05(c), Citing DDR Holdings, LLC v. Hotels.com LP, 773 F.3d 1245, 1256 (Fed. Cir. 2014). See also DDR Holdings at 1256. “For example, in Mayo, the Supreme Court emphasized that satisfying the machine-or-transformation test, by itself, is not sufficient to render a claim patent-eligible, as not all transformations or machine implementations infuse an otherwise ineligible claim with an "inventive concept." See 132 S. Ct. at 1301 ("[S]imply implementing a mathematical principle on a physical machine, namely a computer, [i]s not a patentable application of that principle.") (describing Gottschalk v. Benson, 409 U.S. 63, 64, 93 S. Ct. 253, 34 L. Ed. 2d 273 (1972)). And after Alice, there can remain no doubt: recitation of generic computer limitations does not make an otherwise ineligible claim patent-eligible. 134 S. Ct. at 2358. The bare fact that a computer exists in the physical rather than purely conceptual realm "is beside the point." Id.”