Detailed Action
The following action is in response to the communication(s) received on 05/11/2026.
As of the claims filed 05/11/2026:
Claims 1, 8, and 15 have been amended.
Claims 1-20 are pending.
Claims 1, 8, and 15 are independent claims.
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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 05/07/2025 has been entered.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 9/18/2025 were filed in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Response to Arguments
Applicant’s arguments filed 05/11/2026 have been fully considered but are not fully persuasive.
With respect to the rejection under 35 USC § 101:
Applicant asserts that the claims recite an improvement towards a technical problem in “configuring execution of a machine learning network for a given hardware resource” (p.8 ¶2) and reflected by reciting “to reduce memory transfer overhead between different levels of a memory hierarchy of the device” (¶3). Examiner respectfully submits that "to reduce memory transfer overhead" is merely an intended effect (and thus a generally linked application) of an abstract idea. The claims merely recite algorithmically grouping layers based on transitions of a machine learning model. Such grouping is an abstract idea as it can be performed in the human mind; thus, the instant claims are an improvement towards a particular grouping algorithm and are directed towards an abstract idea.
Thus, all the pending claims remain directed to an abstract idea without significantly more.
On p.9 of the response, with respect to the rejection under 35 USC § 102:
The arguments have been considered and are persuasive. Thus, the art rejection has been withdrawn.
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 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1 recites a method, thus a process, one of the four statutory categories of patentable subject matter (Step 1). However, Claim 1 further recites:
determining… an amount of memory… to process each layer of multiple layers of the machine learning network; which is an evaluation or judgement that can be performed in the human mind;
determining a size of a moving window based at least in part on a number of layers of the multiple layers, the size of the window encompassing a set of layers adjacent to a layer being processed by the window, which is an evaluation or judgement that can be performed in the human mind;
determining…a smoothed amount of memory… for each of the multiple layers based on a number of layers of the multiple layers and a maximum amount of unsmoothed memory in a single layer within the moving window ; which is an evaluation or judgement that can be performed in the human mind;
identifying… transitions between adjacent layers, including comparing the smoothed amount of memory to a dynamically determined memory change threshold amount that is based on available memory of the device; which is an evaluation or judgement that can be performed in the human mind;
grouping… the multiple layers of the machine learning network into a first layer grouping based on the identified transitions to reduce memory transfer overhead between different levels of a memory hierarchy of the device, which is an evaluation or judgement that can be performed in the human mind;
Thus, the claim recites an abstract idea under Step 2A Prong 1.
Under Step 2A Prong 2, the claim does not include any additional elements which integrate the abstract idea into a practical application, since the additional elements consist of:
for configuring execution of a machine learning network for a device…; by the processing circuitry of the device… ; on the device…, as the performance of an abstract idea on a computer is not more than instructions to "apply it" on a computer, which by MPEP 2106.05(f) cannot integrate an abstract idea into a practical application.
outputting…the first layer grouping configured to cause a respective set of layers of a group of the first layer grouping to complete prior to execution of a subsequent group of the first layer grouping, which is merely an insignificant extra-solution activity of data output, which by MPEP 2106.05(g) cannot integrate an abstract idea into a practical application.
Thus, the claim is directed towards an abstract idea.
Further, the additional elements, alone or in combination, do not provide significantly more than the abstract idea itself, because implementation on a computer (MPEP 2106.05(f)), and the activity of data output (MPEP 2106.05(g)) cannot provide significantly more, as receiving or transmitting data over a network is well understood, routine, and conventional (MPEP 2106.05(d)(II)(i)) and the combination of additional elements does not provide an inventive concept. Thus, the claim is ineligible.
Claim 2, dependent on Claim 1, further recites:
Modeling the machine learning network based on the first layer grouping;
associating a first cost with the first layer grouping (mental process);
generating a second layer grouping by adjusting a group boundary of the first layer grouping (mental process);
and modeling the machine learning network based on the second layer grouping; associating a second cost with the second layer grouping (mental process);
As these all fail the mental process grouping of abstract ideas, Claim 2 thus recites an abstract idea.
The claim does not include any additional elements which integrate the abstract idea into a practical application, since the additional element consists of outputting a lower cost layer grouping based on a comparison between the first cost and the second cost, which is insignificant extra-solution activity of data output, which by MPEP 2106.05(g) cannot integrate an abstract idea into a practical application.
Thus, the claim is directed towards the abstract idea.
Further, the additional element does not provide significantly more than the abstract idea itself, because the activity of data output (MPEP 2106.05(g)) cannot provide significantly more than the abstract idea itself. Thus, the claim is subject matter ineligible.
Claim 3, dependent on claim 2, further recites a mental process of expecting (the first and second costs are based on at least one of expected number of memory accesses or processing cycles). It does not recite any new additional elements which could integrate the abstract idea into a practical application or provide significantly more than the abstract idea itself.
Claim 4, dependent on claim 2, further recites a mental process of adjusting (the group boundary is adjusted within a predefined range of values around the group boundary). It does not recite any new additional elements which could integrate the abstract idea into a practical application or provide significantly more than the abstract idea itself.
Claim 5 and 6, dependent on claim 1, merely recites details on the mental process of the grouping of the first layer (the first layer grouping comprises a first set of layers and a second set of layers; a first number of layers of the first set of layers differs from a second number of layers of the second set of layers). Neither claim recites any new additional elements which could integrate the abstract idea into a practical application or provide significantly more than the abstract idea itself.
Claim 7, dependent on claim 1, further recites:
determining a minimum number of tiles for the layers of the first layer grouping based on the amount of memory used by the layers; (a mental process that can be done on pen and paper)
determining a number of tiles for a last layer of the first layer grouping based on the minimum number of tiles; (a mental process that can be done on pen and paper)
and determining the number of tiles for other layers of the first layer grouping based on the number of tiles for the last layer. (a mental process that can be done on pen and paper).
As it does not recite any additional elements, it recites an abstract idea. Thus, the claim is subject matter ineligible.
Claims 8-14 recite non-transitory computer readable storage medium storing instructions for performing precisely the methods of Claims 1-7, respectively. As performance on a computer cannot integrate an abstract idea into a practical application nor provide significantly more than the abstract idea itself (MPEP 2106.05(f)), Claims 8-14 are rejected as subject-matter ineligible for reasons set forth in the rejections of Claims 1-7, respectively.
Claims 15-20 recite A device, thus an article of manufacture, one of the four statutory categories of patentable subject matter. However, Claims 15-20 further recite comprising: a memory; and one or more processors operatively coupled to the memory, wherein the one or more processors are configured to execute non-transitory instructions causing the one or more processors to configure execution of a machine learning network for a device, wherein the one or more processors are configured to perform precisely the methods of Claims 1-5 and 7, respectively. As performance on a computer cannot integrate an abstract idea into a practical application nor provide significantly more than the abstract idea itself (MPEP 2106.05(f)), Claims 15-20 are rejected as subject-matter ineligible for reasons set forth in the rejections of Claims 1-5 and 7, respectively. (Note: “groups of the first layer grouping to execute in sequence” in claim 15 corresponds to “cause a respective set of layers of a group of the first layer grouping to complete prior to execution of a subsequent group of the first layer grouping” in claim 1.)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure: Rhu et al., " vDNN: Virtualized Deep Neural Networks for Scalable, Memory-Efficient Neural Network Design".
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/J.H./Examiner, Art Unit 2122
/KAKALI CHAKI/Supervisory Patent Examiner, Art Unit 2122
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