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 .
DETAILED ACTION
The action is in response to the application filed on 2/7/24
Claims 1-20 are pending.
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 1-20 are pending are rejected under 35 U.S.C 101 because the claimed invention directed to an abstract idea(s) without significantly more.
Claims 1 and 11 recites:
A system, comprising: a computer that includes a processor and a memory, the memory including instructions executable by the processor to:
receive data corresponding to a plurality of vehicles regarding a specified aspect of vehicle performance;
determine an effectiveness of a software update targeted to the specified aspect of vehicle performance based on the data; and
actuate a change in at least one of the plurality of vehicles when the determined effectiveness is below a specified threshold.
Step 1: Is the claim to a process, machine, manufacture, or composition of matter?
Yes.
Claim 1 is a system
Claim 11 is a method
Step 2A, prong I: does the claim recite an abstract idea, law of nature, or a natural phenomenon?
Yes: (an) abstract idea(s).
The ‘determining’ limitation in #2 above, as claimed and under broadest reasonable interpretation (BRI), is a mental process that covers performance of the limitation in the mind. For example, ‘determining’ in the context of the claim encompasses the person determining based on the data received whether the update is performing better or worse than before.
Step 2A prong II: does the claim recite additional elements that integrate the judicial exception in a practical application?
No.
The ‘receive’ limitation in #1 above, as claimed and under BRI, is an additional element that is insignificant extra-solution activity. For example, ‘receive’ in the context of this claim encompasses mere data gathering. See MPEP 2106.05(g).
The “actuate” limitation in #3 above, as claimed and under BRI, is an additional element that is mere instructions to apply an exception. “Actuate” in the context of the claim is merely an “Apply it” step as mere instructions to implement an abstract idea on a computer or merely uses a computer as a tool to perform an abstract idea. See MPEP 2106.05(f).
One or more of the claims recite the following additional elements:
A system (Claim 1)
A computer (Claim 1)
Processor (Claim 1)
Memory (Claim 1)
These additional elements are recited at a high level of generality (i.e. as generic computer components) such that they amount to no more than components comprising mere instructions to apply the exception. Accordingly, these additional elements do not integrate the abstract idea(s) into a practical application because they do not impose any meaningful limits on practicing the abstract idea(s).
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
No.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of “system”, “computer”, “processor”, and “memory” amount to no more than mere instructions, or generic computer/computer components to carry out the exception. See MPEP 2106.05(f). The recitation of generic computer instruction and computer components to apply the judicial exception, and merely displaying data do not amount to significantly more, thus, cannot provide an inventive concept.
Additionally, with regards to #1 above, the claim does not include additional elements that are sufficient to amount of significantly more than the judicial exception. The limitation “receive data corresponding to a plurality of vehicles regarding a specified aspect of vehicle performance” the courts have identified mere data gathering and transmitting are well-understood, routine, and conventional activity. See MPEP 2106.05(d). Furthermore, the limitation “actuate a change…” does not require any particular application of the recited evaluation and is at best the equivalent of merely adding the words “apply it” to the judicial exception. Mere instructions to apply an exception cannot provide an inventive concept. Accordingly, the claims are not patent eligible under 35 U.S.C. 101.
Claims 2 and 12 recites:
Wherein the instructions to determine the effectiveness of the software update include instructions to apply a causal model to the received data
Step 1: Is the claim to a process, machine, manufacture, or composition of matter?
Yes.
Claim 2 is a system
Claim 12 is a method
Step 2A, Prong II: Does the claim recite additional elements that integrate the judicial exception into a practical application?
No.
The “Apply” limitation in #4 above, as claimed and under BRI, is an additional element that is mere instructions to apply an exception. “Apply” in the context of the claim is merely an “Apply it” step as mere instructions to implement an abstract idea of a computer or merely uses a computer as a tool to perform an abstract idea. See MPEP 2106.05(f).
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
No.
The limitation “Wherein the instructions to determine the effectiveness of the software update include instructions to apply a causal model to the received data” does not require any particular application of the recited evaluation and is at best the equivalent of merely adding the words “apply it” to the judicial exception. Mere instructions to apply an exception cannot provide an inventive concept.
Claims 3 and 13 recite:
Wherein the instructions to apply the causal model include
Instructions to determine a conditional average treatment effect of the software update based on the data
Step 1: Is the claim to a process, machine, manufacture, or composition of matter?
Yes.
Claim 3 is a system
Claim 13 is a method
Step 2A, Prong I: does the claim recite an abstract idea, law of nature, or a natural phenomenon?
Yes: (an) abstract idea(s).
The “determine” limitation in #5 above, as claimed and under broadest reasonable interpretation (BRI), is a mental process that covers performance of the limitation in the mind. For example, “determine” in the context of the claim encompasses the person calculating the average of effectiveness of the update on the groups of features.
Claims 4 and 14 merely further describe the claimed instructions to determine a conditional average treatment effect of claims 3 and 13, respectively.
Claims 5 and 15 recite:
Wherein the instructions to apply the causal model include
Instructions to determine an average treatment effect of a vehicle feature based on the determined conditional average treatment effect for the software update
Step 1: Is the claim to a process, machine, manufacture, or composition of matter?
Yes.
Claim 5 is a system
Claim 15 is a method
Step 2A, Prong I: does the claim recite an abstract idea, law of nature, or a natural phenomenon?
Yes: (an) abstract idea(s).
The “determine” limitation in #6 above, as claimed and under broadest reasonable interpretation (BRI), is a mental process that covers performance of the limitation in the mind. For example, “determine” in the context of the claim encompasses the person calculating the average treatment effect of a vehicle feature using the conditional average treatment effect.
Claim 6 and 16 recite:
Wherein the instructions to apply the causal model include
Instructions to sum the effectiveness of the software update and one or more subsequent software updates
Step 1: Is the claim to a process, machine, manufacture, or composition of matter?
Yes.
Claim 6 is a system
Claim 16 is a method
Step 2A, Prong I: does the claim recite an abstract idea, law of nature, or a natural phenomenon?
Yes: (an) abstract idea(s).
The “sum” limitation in #7 above, as claimed and under broadest reasonable interpretation (BRI), is a mental process that covers performance of the limitation in the mind. For example, “sum” in the context of the claim encompasses the person summing the effectiveness of the software update and the subsequent software update(s).
Claims 7 and 17 merely further describe the instructions to apply the causal model of claims 2 and 12, respectively.
Claim 8, 10, 18, and 20 recites:
Wherein the instructions to actuate a change in the at least one of the plurality of vehicles include
Instructions to revert the software update to a previous version and/or disable a component of the at least one of the plurality of vehicles having a specified feature
Step 1: Is the claim to a process, machine, manufacture, or composition of matter?
Yes.
Claim 8 is a system
Claim 18 is a method
Step 2A, Prong I: does the claim recite an abstract idea, law of nature, or a natural phenomenon?
Yes: (an) abstract idea(s).
The ‘revert’ limitation in #8 above, as claimed and under broadest reasonable interpretation (BRI), mental process with the help of a generic computer that covers performance of the limitation in the mind. For example, ‘revert’ in the context of the claim encompasses the person determining based on the data received that the update was ineffective and reverts the update to a component.
Claims 9 and 19 merely further describes the claimed received data of claims 1 and 11, respectively.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1, 8, 10, 11, 18, and 20 is/are rejected under 35 U.S.C 103 as being unpatentable over Skaggs et al (US 20230005304 A1) hereinafter Skaggs in view of Dixit et al (US 20240420293 A1) hereinafter Dixit.
Regarding claim 1, Skaggs discloses
A system, comprising: a computer that includes a processor and a memory, the memory including instructions executable by the processor to: (Skaggs [0008] discloses a computer system including one or more processors with memory coupled and storing executable instructions)
receive data corresponding to a plurality of vehicles regarding a specified aspect of vehicle performance; (Skaggs [0016] and figure 10 discloses obtaining, by one or more processors, vehicle data from a vehicle data repository, the vehicle data comprising a vehicle feature, and the vehicle feature being stored in an original equipment manufacturer (OEM)-agnostic terminology. Step 1002 on figure 10 further discloses obtaining vehicle data comprising a vehicle feature. Further on Skaggs [0005], vehicle data is collected, such data containing new feature, system, software performance and usage).
determine an effectiveness of a software update targeted to the specified aspect of vehicle performance based on the data; and (Skaggs [0151] - [0152] discloses the update effectiveness computing device obtains vehicle data comprising a vehicle feature, in this case a safety feature. Then, [0161] – [0164] discloses the calculation of effectiveness between before the update is implemented and after the update is implemented. [0149] further discloses that this evaluation is determined by comparing target feature values predicted by the model to the actual target feature values by evaluating the performance of the model).
Skaggs lacks explicitly
actuate a change in at least one of the plurality of vehicles when the determined effectiveness is below a specified threshold.
Dixit teaches
actuate a change in at least one of the plurality of vehicles when the determined effectiveness is below a specified threshold. (Dixit [0022] discloses if the confidence value is less than the threshold value, the circuitry may revert to a default setting. Further, figure 5 shows that in 502 the image correction/update occurring and 504 shows the post-processing based on correction image frame which is where the confidence value determination is made).
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to have modified Skaggs to incorporate the teachings of Dixit to “actuate a change in at least one of the plurality of vehicles when the determined effectiveness is below a specified threshold” in order to improve the vehicles’ system health by rolling back a harmful update and making the update process reliable in the event of adverse effects.
Regarding claim 8, it’s a system having similar limitations cited in claim 10. Thus claim 8 is also rejected under the same rationale as cited in the rejection of claim 10 below.
Regarding claim 10, Skaggs discloses
The system of claim 1
for a group of the plurality of vehicles having a specified feature (Skaggs [0068] discloses grouping vehicles based on certain features)
Skaggs lacks explicitly
Wherein the instructions to actuate a change in the at least one of the plurality of vehicles include instructions to revert the software update to a previous version and/or disable a component
Dixit discloses
Wherein the instructions to actuate a change in the at least one of the plurality of vehicles include instructions to revert the software update to a previous version and/or disable a component (Dixit [0022] discloses reverting the processing circuitry to default setting, which would be a previous version of the settings).
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to have modified Skaggs to incorporate the teachings of Dixit to “Wherein the instructions to actuate a change in the at least one of the plurality of vehicles include instructions to revert the software update to a previous version and/or disable a component” in order to remove harmful software from the vehicle thus reducing further complications and improving overall update and patching efficiency.
Regarding claim 11, it’s a method having similar limitations cited in claim 1. Thus claim 11 is also
rejected under the same rationale as cited in the rejection of claim 1 above.
Regarding claim 18, it’s a method having similar limitations cited in claim 8. Thus claim 18 is also rejected under the same rationale as cited in the rejection of claim 8 above.
Regarding claim 20, it’s a method having similar limitations cited in claim 10. Thus claim 20 is also rejected under the same rationale as cited in the rejection of claim 10 above.
Claim(s) 2, 3, 5-7, 12, 13, 15-17 is/are rejected under 35 U.S.C 103 as being unpatentable over Skaggs et al (US 20230005304 A1) hereinafter Skaggs in view of Dixit et al (US 20240420293 A1) hereinafter Dixit in further view of Wong et al (US 20210064517 A1) hereinafter Wong.
Regarding claim 2, Skaggs in view of Dixit discloses
The system of claim 1
Skaggs in view of Dixit lacks explicitly
wherein the instructions to determine the effectiveness of the software update include instructions to apply a causal model to the received data
Wong teaches
wherein the instructions to determine the effectiveness of the software update include instructions to apply a causal model to the received data (Wong [0046] and [0047] discloses testing the functionality of a software feature against another type of software functionality, where type A is the baseline and type B is a new feature or an updated feature. Then the system outputs these outcomes, with A, B, or C which indicate that a new feature is either has higher, lower, or the same user interaction which demonstrates the effectiveness of the feature update. To produce the outcomes, the data accessing module accesses data that is to be used with the test implementation. Wong [0065] further discloses using the data to estimate statistical models and then computing causal effects, then analyze different variants of treatment effects, and finally running at scale)
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to have modified Skaggs in view of Dixit to incorporate the teachings of Wong to “wherein the instructions to determine the effectiveness of the software update include instructions to apply a causal model to the received data” in order to determine the cause/effect of the software update on the vehicle, allowing the vehicle to improve and upgrade or revert and avoid errors/inefficiency.
Regarding claim 3, Skaggs in view of Dixit discloses
The system of claim 2
Skaggs in view of Dixit lacks explicitly
Wherein the instructions to apply the causal model include instructions to determine a conditional average treatment effect of the software update based on the data.
Wong teaches
Wherein the instructions to apply the causal model include instructions to determine a conditional average treatment effect of the software update based on the data. (Wong [0064] demonstrates using conditional average treatment effect for measuring the treatment effect for a specific sub-population, where the treatment effect is defined as Wong [0050] – [0051] the software update and its effect on the end users using the A/B tests).
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to have modified Skaggs in view of Dixit to incorporate the teachings of Wong to “Wherein the instructions to apply the causal model include instructions to determine a conditional average treatment effect of the software update based on the data” in order to determine using the data whether the update was, on average, an improvement or not. This determination allows the system to either improve or revert/prevent harmful changes to the system.
Regarding claim 5, Skaggs in view of Dixit discloses
The system of claim 3
Skaggs in view of Dixit lacks explicitly
Wherein the instructions to apply the causal model include instructions to determine an average treatment effect of a vehicle feature based on the conditional average treatment effect for the software update
Wong teaches
Wherein the instructions to apply the causal model include instructions to determine an average treatment effect of a vehicle feature based on the conditional average treatment effect for the software update (Wong [0064] and [0065] discloses an average treatment effect summarizing the treatment overall, and the conditional average treatment effect measuring the treatment effect for a specific sub-population. This function demonstrates the CATE related to outcomes of software update and ATE as the overall outcome of the effect of a feature).
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to have modified Skaggs in view of Dixit to incorporate the teachings of Wong to “Wherein the instructions to apply the causal model include instructions to determine an average treatment effect of a vehicle feature based on the conditional average treatment effect for the software update” in order to compute causal effects and respond to live queries to analyze different subpopulations or variants of treatment effects before running at scale, as disclosed in Wong [0065]. This improves updating efficiency and reduces risk of an adverse update compromising the vehicles.
Regarding claim 6, Skaggs in view of Dixit in further view of Wong discloses
The system of claim 2, wherein the instructions to apply the causal model include instructions to sum the effectiveness of the software update and one or more subsequent software updates. (Skaggs [0083] discloses combining the effectiveness scores for multiple safety features, i.e., the blind spot detection feature and an adaptive cruise control feature. As previously mentioned, Skaggs [0160] – [0164] then updates the system).
Regarding claim 7, Skaggs in view of Dixit in further view of Wong discloses
The system of claim 2, wherein the instructions to apply the causal model include instructions to group the plurality of vehicles by features (Skaggs [0068] discloses grouping vehicles based on certain features to analyze the effectiveness and/or performance of various vehicle features)
Regarding claim 12, it’s a method having similar limitations cited in claim 2. Thus claim 12 is also rejected under the same rationale as cited in the rejection of claim 2 above.
Regarding claim 13, it’s a method having similar limitations cited in claim 3. Thus claim 13 is also rejected under the same rationale as cited in the rejection of claim 3 above.
Regarding claim 15, it’s a method having similar limitations cited in claim 5. Thus claim 15 is also rejected under the same rationale as cited in the rejection of claim 5 above.
Regarding claim 16, it’s a method having similar limitations cited in claim 6. Thus claim 16 is also rejected under the same rationale as cited in the rejection of claim 6 above.
Regarding claim 17, it’s a method having similar limitations cited in claim 7. Thus claim 17 is also rejected under the same rationale as cited in the rejection of claim 7 above.
Claim(s) 4 and 14 is/are rejected under 35 U.S.C 103 as being unpatentable over Skaggs et al (US 20230005304 A1) hereinafter Skaggs in view of Dixit et al (US 20240420293 A1) hereinafter Dixit in further view of Wong et al (US 20210064517 A1) hereinafter Wong in further view of Tu et al (US 20200311745 A1) hereinafter Tu.
Regarding claim 4, Skaggs in view of Dixit in further view of Wong discloses
The system of claim 3,
Wherein the instructions to determine a conditional average treatment effect of the software update based on the data
Skaggs in view of Dixit in further view of Wong explicitly lack
Include instructions to use an S-learner, an X-learner, or a causal tree algorithm
Tu teaches
Include instructions to use an S-learner, an X-learner, or a causal tree algorithm (Tu [0026] discloses a treatment model generation service implementing a causal tree algorithm to estimate heterogeneity in causal effects of applying different treatments).
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to have modified Skaggs in view of Dixit in further view of Wong to incorporate the teachings of Tu to “Include instructions to use an S-learner, an X-learner, or a causal tree algorithm” in order to observe the results of software update and how they compare to estimated effects, improving system efficiency by either continuing with the update and improving the vehicle or reverting the update and preventing failures in the system.
Regarding claim 14, it’s a method having similar limitations cited in claim 4. Thus claim 14 is also rejected under the same rationale as cited in the rejection of claim 4 above.
Claim(s) 9 and 19 is/are rejected under 35 U.S.C 103 as being unpatentable over Skaggs et al (US 20230005304 A1) hereinafter Skaggs in view of Dixit et al (US 20240420293 A1) hereinafter Dixit in further view of Bohl et al (US 20200051347 A1) hereinafter Bohl.
Regarding claim 9, Skaggs in view of Dixit discloses
The system of claim 1
Skaggs in view of Dixit lack explicitly
Wherein the received data includes warranty claim information and/or vehicle diagnostic trouble codes.
Bohl teaches
Wherein the received data includes warranty claim information and/or vehicle diagnostic trouble codes. (Bohl [0009] discloses receiving a diagnostic trouble code from the vehicle subsystem).
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to have modified Skaggs in view of Dixit to incorporate the teachings of Bohl to “Wherein the received data includes warranty claim information and/or vehicle diagnostic trouble codes” in order to have a metric in determining performance of the vehicle for the update, thus allowing outcomes of the update to be seen easier.
Regarding claim 9, it’s a method having similar limitations cited in claim 19. Thus claim 19 is also rejected under the same rationale as cited in the rejection of claim 9 above.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHRISTOPHER J SALLEY whose telephone number is (571)272-6355. The examiner can normally be reached Mon-Fri, 7:30am-5pm.
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/CHRISTOPHER J SALLEY/
Examiner, Art Unit 2193
/Chat C Do/Supervisory Patent Examiner, Art Unit 2193