DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
This office action is in response to applicant’s response received on 06/18/2025.
Response to Arguments
Applicant’s arguments filed on 06/18/2025, with respect to claims 1, 7, and 13 have been fully considered and are persuasive. Therefore, the rejection under 103 of claims 1, 7, and 13 have been withdrawn. However, upon further consideration, claims 1-18 are rejected under 101.
Applicant argues that the lengthy and detailed limitations of the independent claims could not be practically performed in the human mind. In the alternative, Applicant submits that the claims recite “significantly more” than the alleged abstract idea outlined in the Office Action.
Response: Examiner respectfully disagrees.
Each limitation recites in the claim is a process that, under BRI covers performance of the limitation in the mind but for the recitation of a generic “sensor, body part, and measurement” which is a mere indication of the field of use. Nothing in the claim elements precludes the steps from practically being performed in the mind. Thus, the claim recites a mental process.
Further, the claim recites the step of "receive configuration data regarding a computing cluster that is to execute a simulation of the target workload; train a workload artificial intelligence (AI) model based on the telemetry information and the configuration data to create the simulation of the target workload; generate a benchmarking configuration file based on the workload Al model; and deploy the benchmarking configuration file to the computing cluster for execution” which as drafted, under BRI recites a mathematical calculation. The grouping of "mathematical concepts” in the 2019 PED includes "mathematical calculations" as an exemplar of an abstract idea. 2019 PEG Section |, 84 Fed. Reg. at 52. Thus, the recited limitation falls into the "mathematical concept" grouping of abstract ideas. This limitation also falls into the “mental process” group of abstract ideas, because the recited mathematical calculation is simple enough that it can be practically performed in the human mind, e.g., scientists and engineers have been solving the Arrhenius equation in their minds since it was first proposed in 1889.
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. See October Update at Section I(C)(i) and (iii).
Additional Elements:
Step 2A prong two:
”An information handling system comprising: at least one processor; and a memory; wherein the information handling system is configured to” recited in the preamble does not integrate the judicial exception into a practical application. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)).
“receiving telemetry information regarding a target workload” does not integrate the judicial exception into a practical application. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)).
“receiving configuration data regarding a computing cluster that is to execute a simulation of the target workload” does not integrate the judicial exception into a practical application. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)).
“training a workload artificial intelligence (AI) model based on the telemetry information and the configuration data to create the simulation of the target workload” does not integrate the judicial exception into a practical application. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)).
“generating a benchmarking configuration file based on the workload AI model” does not integrate the judicial exception into a practical application. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)); and
“deploying the benchmarking configuration file to the computing cluster for execution” does not integrate the judicial exception into a practical application. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)).
The claim is merely collecting data, manipulating or analyzing the data using math and mental process, and displaying the results.
This is similar to electric power: MPEP 2106.05(h) vi. Limiting the abstract idea of collecting information, analyzing it, and displaying certain results of the collection and analysis to data related to the electric power grid, because limiting application of the abstract idea to power-grid monitoring is simply an attempt to limit the use of the abstract idea to a particular technological environment, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016).
The claim as a whole does not meet any of the following criteria to integrate the judicial exception into a practical application:
An additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
Step 2B: Claim provides an Inventive Concept? No.
”An information handling system comprising: at least one processor; and a memory; wherein the information handling system is configured to” recited in the preamble does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)).
“receiving telemetry information regarding a target workload” does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)).
“receiving configuration data regarding a computing cluster that is to execute a simulation of the target workload” does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)).
“training a workload artificial intelligence (AI) model based on the telemetry information and the configuration data to create the simulation of the target workload” does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)).
“generating a benchmarking configuration file based on the workload AI model” does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)).
“deploying the benchmarking configuration file to the computing cluster for execution” does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)).
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 1-18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Step 1:
According to the first part of the analysis, in the instant case, claims 1-6 is directed using an information handling system to perform a method, claims 7- 12 is directed to a method claim, and claim 13-18 is directed to using an article of manufacture comprising a non-transitory computer-readable medium having computer-executable instructions thereon that are executable by a processor of an information handling system to perform a method. Thus, each of the claims falls within one of the four statutory categories (i.e. process, machine, manufacture, or composition of matter).
Regarding claim 1:
An information handling system comprising: at least one processor; and a memory; wherein the information handling system is configured to:
receive telemetry information regarding a target workload;
receive configuration data regarding a computing cluster that is to execute a simulation of the target workload;
train a workload artificial intelligence (AI) model based on the telemetry information and the configuration data to create the simulation of the target workload;
generate a benchmarking configuration file based on the workload Al model; and
deploy the benchmarking configuration file to the computing cluster for execution.
Step 2A prong one:
“receive telemetry information regarding a target workload” is a mental step of collecting telemetry information regarding a target workload.
“receive configuration data regarding a computing cluster that is to execute a simulation of the target workload” is directed to mathematics because at the core of any simulation is a mathematical model that represents the real-world system being simulated. This model will define the variables, equations, and rules that govern the behavior of the workload and the computing cluster. The configuration data received by the information handling system would be used to set parameters for this mathematical model. The execution of the simulation on the computing cluster relies on algorithms that translate the mathematical model into computations. For example, these might include algorithms for simulating physical interactions (e.g., Newtonian physics), network traffic, resource allocation, or process scheduling. The purpose of the simulation is often to analyze the performance of a given workload on a specific cluster configuration and identify areas for improvement. This analysis often involves: Statistical Analysis: Determining the behavior and performance metrics (e.g., execution time, resource utilization) requires statistical analysis of the simulation's output data. Optimization Algorithms: If the goal is to optimize performance, mathematical optimization algorithms could be employed to find the best configuration parameters, based on the simulation results.
“train a workload artificial intelligence (AI) model based on the telemetry information and the configuration data to create the simulation of the target workload” is directed to mathematics because telemetry data (performance metrics over time) and configuration data (parameters defining the workload) need to be represented in a format that AI models can understand. This typically involves using vectors, matrices, and tensors – concepts from linear algebra. Linear algebra provides the tools to store, process, and analyze this data efficiently. Machine learning and deep learning, which are used to build these AI models, rely heavily on mathematical algorithms. These algorithms learn patterns and relationships in the telemetry and configuration data during the training phase. This involves complex mathematical processes and algorithms. Training AI models involves optimizing a cost function to minimize the difference between the model's predicted output and the actual output. Calculus, particularly derivatives and gradients, plays a critical role in this optimization process, enabling the model to adjust its parameters and improve its accuracy. Telemetry data can be noisy and incomplete. Probability and statistics are essential for dealing with this uncertainty and making informed predictions based on the available data. Statistical techniques help analyze data distributions, identify trends, and validate the model's performance. The goal of training the model is to create a simulation of the target workload. This involves mathematical modeling and potentially using techniques like mathematical optimization to ensure the simulation accurately reflects the real-world behavior.
“generate a benchmarking configuration file based on the workload Al model” is directed to mathematics because after the benchmark is run, the collected data needs to be analyzed to understand the AI model's performance.
Statistical methods are used to interpret the results, identify trends, compare different configurations, and assess the significance of the observed performance differences. Techniques like principal component analysis (PCA), which relies on eigenvalues and eigenvectors from linear algebra, can be used to understand feature importance and variability in the benchmark data. Generating a benchmarking configuration file based on an AI model's workload is deeply connected to mathematics. Linear algebra helps represent and manipulate data and parameters, calculus is essential for optimization and understanding changes, and statistics is crucial for analyzing and interpreting the benchmark results.
“deploy the benchmarking configuration file to the computing cluster for execution” is directed to mathematics because benchmarking involves collecting quantitative measures to compare different systems or configurations. These metrics are often analyzed using statistical techniques to understand the performance differences and identify areas for improvement. For example, measuring the execution time (wall-clock time) and the number of operations performed (e.g., gigaflops for HPL) are fundamental aspects of benchmarking that rely on mathematical concepts of rates and calculations. When analyzing the results, statistical methods like regression analysis, correlation analysis, and t-tests can be used to identify trends and relationships between variables, such as customer satisfaction levels and revenue growth. Benchmarking analysis often uses statistical measures like percentiles (e.g., lower quartile, median, upper quartile) to present and interpret results, enabling comparison of a company's performance against industry standards or best practices. Optimizing the deployment of compute clusters to achieve energy savings can be framed as a mathematical problem, specifically using mixed-integer linear programming (MILP) to model power and load relationships across different frequencies.
Each limitation recites in the claim is a process that, under BRI covers performance of the limitation in the mind but for the recitation of a generic “sensor, body part, and measurement” which is a mere indication of the field of use. Nothing in the claim elements precludes the steps from practically being performed in the mind. Thus, the claim recites a mental process.
Further, the claim recites the step of "receive configuration data regarding a computing cluster that is to execute a simulation of the target workload; train a workload artificial intelligence (AI) model based on the telemetry information and the configuration data to create the simulation of the target workload; generate a benchmarking configuration file based on the workload Al model; and deploy the benchmarking configuration file to the computing cluster for execution” which as drafted, under BRI recites a mathematical calculation. The grouping of "mathematical concepts” in the 2019 PED includes "mathematical calculations" as an exemplar of an abstract idea. 2019 PEG Section |, 84 Fed. Reg. at 52. Thus, the recited limitation falls into the "mathematical concept" grouping of abstract ideas. This limitation also falls into the “mental process” group of abstract ideas, because the recited mathematical calculation is simple enough that it can be practically performed in the human mind, e.g., scientists and engineers have been solving the Arrhenius equation in their minds since it was first proposed in 1889.
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. See October Update at Section I(C)(i) and (iii).
Additional Elements:
Step 2A prong two:
”An information handling system comprising: at least one processor; and a memory; wherein the information handling system is configured to” recited in the preamble does not integrate the judicial exception into a practical application. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)).
“receiving telemetry information regarding a target workload” does not integrate the judicial exception into a practical application. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)).
“receiving configuration data regarding a computing cluster that is to execute a simulation of the target workload” does not integrate the judicial exception into a practical application. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)).
“training a workload artificial intelligence (AI) model based on the telemetry information and the configuration data to create the simulation of the target workload” does not integrate the judicial exception into a practical application. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)).
“generating a benchmarking configuration file based on the workload AI model” does not integrate the judicial exception into a practical application. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)); and
“deploying the benchmarking configuration file to the computing cluster for execution” does not integrate the judicial exception into a practical application. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)).
The claim is merely collecting data, manipulating or analyzing the data using math and mental process, and displaying the results.
This is similar to electric power: MPEP 2106.05(h) vi. Limiting the abstract idea of collecting information, analyzing it, and displaying certain results of the collection and analysis to data related to the electric power grid, because limiting application of the abstract idea to power-grid monitoring is simply an attempt to limit the use of the abstract idea to a particular technological environment, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016).
The claim as a whole does not meet any of the following criteria to integrate the judicial exception into a practical application:
An additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
Step 2B: Claim provides an Inventive Concept? No.
”An information handling system comprising: at least one processor; and a memory; wherein the information handling system is configured to” recited in the preamble does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)).
“receiving telemetry information regarding a target workload” does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)).
“receiving configuration data regarding a computing cluster that is to execute a simulation of the target workload” does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)).
“training a workload artificial intelligence (AI) model based on the telemetry information and the configuration data to create the simulation of the target workload” does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)).
“generating a benchmarking configuration file based on the workload AI model” does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)).
“deploying the benchmarking configuration file to the computing cluster for execution” does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)).
The claim is therefore ineligible under 35 USC 101.
Claim 7 is similar to claim 1 but recites a method and the method include the information handling system is configured the steps as in claim 1. These additional elements fail to integrate the abstract idea into a practical application. These limitations are recited at a high level of generality and do not add significantly more to the judicial exception. These elements are generic computing devices that perform generic functions. Using generic computer elements to perform an abstract idea does not integrate an abstract idea into a practical application. See 2019 Guidance, 84 Fed. Reg. at 55. Moreover, “the mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention.” Alice, 573 U.S. at 223; see also FairWarninglP, LLCv. latric SysInc., 839 F.3d 1089, 1096 (Fed. Cir. 2016) (citation omitted) (“[T]he use of generic computer elements like a microprocessor or user interface do not alone transform an otherwise abstract idea into patent-eligible subject matter”). On the record before us, we are not persuaded that the hardware processors of claim 7 integrates the abstract idea into a practical application. Nor are we persuaded that the additional elements are anything more than well-understood, routine, and conventional so as to impart subject matter eligibility to claim 7.
Claim 13 is similar to claim 1 but recites an article of manufacture comprising a non-transitory, computer-readable medium having computer-executable instructions thereon that are executable by a processor of an information handling system for to perform the steps similar as in claim 1. This amounts to nothing more than instructions to implement the abstract idea on a computer, which fails to integrate the abstract idea into a practical application. See 2019 Guidance, 84 Fed. Reg. at 55. Additionally, using instructions to implement an abstract idea on a generic computer “is not ‘enough’ to transform an abstract idea into a patent-eligible invention.” Alice, 573 U.S. at 226. Therefore, the rejection of claim 13 for the same reason discussed above with regard to the rejection of claim 1.
Regarding claims 2, 8, and 14, “wherein the computing cluster is a hyper- converged infrastructure (HCI) cluster” is directed to math because the design, implementation, and management of an HCI cluster involve various aspects that draw upon mathematical concepts and tools, including optimization, statistics, graph theory, and algorithms based on machine learning.
Regarding claims 3, 9, and 15, “wherein the AI model is a long short-term memory (LSTM) model” does not integrate the judicial exception into a practical application. It does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)).
Regarding claims 4, 10, and 16, “wherein the workload AI model is implemented via a microservice architecture” does not integrate the judicial exception into a practical application. It does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)).
Regarding claims 5, 11, and 17, “wherein the telemetry information is received from a cloud intelligence system” does not integrate the judicial exception into a practical application. It does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)).
Regarding claims 6, 12, and 18, “wherein the telemetry information further includes information regarding a target information handling system configured to execute the target workload” does not integrate the judicial exception into a practical application. It does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)).
Hence the claims 1-18 are treated as ineligible subject matter under 35 U.S.C. § 101.
Conclusion
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.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHN H LE whose telephone number is (571)272-2275. The examiner can normally be reached on Monday-Friday from 7:00am – 3:30pm ET.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Shelby A. Turner can be reached on (571) 272-6334. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JOHN H LE/Primary Examiner, Art Unit 2857
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