Prosecution Insights
Last updated: April 19, 2026
Application No. 18/500,672

Quantization at Different Levels for Data Used in Artificial Neural Network Computations

Non-Final OA §103
Filed
Nov 02, 2023
Examiner
PATEL, JITESH
Art Unit
2612
Tech Center
2600 — Communications
Assignee
Micron Technology, Inc.
OA Round
1 (Non-Final)
78%
Grant Probability
Favorable
1-2
OA Rounds
2y 2m
To Grant
91%
With Interview

Examiner Intelligence

Grants 78% — above average
78%
Career Allow Rate
312 granted / 398 resolved
+16.4% vs TC avg
Moderate +12% lift
Without
With
+12.4%
Interview Lift
resolved cases with interview
Typical timeline
2y 2m
Avg Prosecution
14 currently pending
Career history
412
Total Applications
across all art units

Statute-Specific Performance

§101
6.2%
-33.8% vs TC avg
§103
61.3%
+21.3% vs TC avg
§102
3.8%
-36.2% vs TC avg
§112
16.6%
-23.4% vs TC avg
Black line = Tech Center average estimate • Based on career data from 398 resolved cases

Office Action

§103
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 . Claim Rejections - 35 USC § 103 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. 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. Claims 1 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Naccari et al (US 20230078190 A1). Regarding claim 1, Naccari discloses a method (Naccari [0005], “method”), comprising: storing weight data configured to weigh on image data (Naccari [0052], “Encoding is carried out using the weights stored in the model”; [0053], “A normalised weight W.sub.N for each image area is determined”); receiving first data representative of a first portion of an image (Naccari [0053], “for each image area (a first data representing a first received area/portion of an image)”); determining, based on a location of the first portion within the image, a first quantization level (Naccari [0056], “determining the weight W.sub.current for each area (area is interpreted as comprising a portion at a given location in an image) of a current image”; [0070], “a discrete quantisation level Δ.sub.area used for compression (comprising a first quantization level)”); and quantizing the first data according to the first quantization level (Naccari [0070], “a discrete quantisation level Δ.sub.area used for compression (compression/quantizing)”); Naccari does not explicitly disclose a location of the first portion within the image. However, Naccari suggests a location of the first portion within the image (Naccari [0056], “determining the weight W.sub.current for each area (area is interpreted as comprising a portion at a given location in an image) of a current image”). It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to utilize area information as location data for portions of an image. This would have been done to generate a high quality compressed image. See, for example, Naccari [0025], “a photograph or a video, different areas of the image may be compressed at different levels. For example, a larger area of similar, or identical color, such as sky, may be compressed at a higher level, without losing quality perceived by a viewer of the display device 20, than an area with sharp boundaries between different colors providing high detail.”). Regarding claim 15, Naccari discloses an apparatus (Naccari fig. 2), comprising: a pair of augmented reality glasses (Naccari [0020], “enhanced reality wearable glasses or other head-mounted display system”), having: a digital camera configured to capture an image of a field of view (Naccari [0020], “video cameras”); and a processing device configured to perform an analysis of the image using an artificial neural network having weight data (Naccari [0052], “Encoding is carried out using the weights stored in the model”; [0053], “A normalised weight W.sub.N for each image area is determined”); wherein the processing device is further configured to apply different quantization levels to data from different regions of the image (Naccari [0056], “determining the weight W.sub.current for each area (areas interpreted as comprising different regions in an image) of a current image”; [0070], “a discrete quantisation level Δ.sub.area used for compression (comprising a first quantization level)”), and apply the different quantization levels to the weight data in weighing on the data from the different regions respectively (Naccari [0070], “a discrete quantisation level Δ.sub.area used for compression (compression/quantizing levels for each area respectively)”). Naccari does not explicitly disclose a digital camera. However, Naccari suggests a digital camera (Naccari [0020], “video cameras”; [0021], “the sources may be … video streams (interpreted as reading on digital image data)”). It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to utilize a digital camera, as suggested by Naccari, to capture image data for processing. This would have been done to optimize processing by eliminating the need for processing by eliminating analog to digital processing from a non-digital camera. Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Naccari in view of Kim et al (US 20240104912 A1). Regarding claim 8, Naccari discloses a device (Naccari fig. 1), comprising: receive first data representative of a first portion of the image (Naccari [0053], “for each image area (a first data representing a first received area/portion of an image)”);; and determine, based on a location of the first portion within the image, a first quantization level (Naccari [0056], “determining the weight W.sub.current for each area (area is interpreted as comprising a portion at a given location in an image) of a current image”; [0070], “a discrete quantisation level Δ.sub.area used for compression (comprising a first quantization level)”); voltage drivers (Naccari [0019], “circuits” (comprising voltage drivers to drive the circuits)); and a logic circuit (Naccari [0019], “circuits, and processes”) configured to: Naccari does not disclose an array of memory cells programmable in a first mode to support multiplication and accumulation program, using the voltage drivers and in the first mode, first memory cells in the array to store weight data of an artificial neural network trained to analyze an image However, Kim discloses an array of memory cells programmable in a first mode to support multiplication and accumulation (Kim [0148], “the processing element array 100 is configured to include a plurality of processing elements (PE1 . . . ) 110 configured to calculate node data of an artificial neural network and weight data of a connection network. Each processing element may include a multiply and accumulate (MAC) operator”); program, using the voltage drivers and in the first mode, first memory cells in the array to store weight data of an artificial neural network trained to analyze an image (Kim [0143], “the algorithms applied to the first and second models based on the artificial neural network, and the operating characteristics of the NPU 1000, … the weight values loaded into the internal memory (store weight data of an artificial neural network trained to analyze an image)”; [0168], “The NPU controller 300 may control (program) to induce at least one processing element to classify the object in the image (analyzing an image) using the first model”); It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Naccari with Kim to utilize an NPU to perform MAC operations to analyze image objects. This would have been done to improve image quality. See, for example, Kim [0221], “provide an image having an optimal quality according to characteristics of an object by using a plurality of independent neural network-based models” Allowable Subject Matter Claims 2-7, 9-14 and 16-20 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. The following is a statement of reasons for the indication of allowable subject matter: Regarding claim 2, none of the prior art of record, alone or in combination, disclose the claim as recited as a whole. Claims 3-7 are allowed for depending from claim 2. Regarding claim 9, none of the prior art of record, alone or in combination, disclose the claim as recited as a whole. Claims 10-14 are allowed for depending from claim 9. Regarding claim 15, none of the prior art of record, alone or in combination, disclose the claim as recited as a whole. Claims 16-20 are allowed for depending from claim 15. Conclusion See the notice of references cited (PTO-892) for prior art made of record, including art that is not relied upon but considered pertinent to applicant's disclosure. Any inquiry concerning this communication or earlier communications from the examiner should be directed to JITESH PATEL whose telephone number is (571)270-3313. The examiner can normally be reached 8am - 5pm. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Said A. Broome can be reached at (571) 272-2931. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /JITESH PATEL/ Primary Examiner, Art Unit 2612
Read full office action

Prosecution Timeline

Nov 02, 2023
Application Filed
Mar 16, 2026
Request for Continued Examination
Mar 18, 2026
Response after Non-Final Action
Mar 21, 2026
Non-Final Rejection — §103 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
78%
Grant Probability
91%
With Interview (+12.4%)
2y 2m
Median Time to Grant
Low
PTA Risk
Based on 398 resolved cases by this examiner. Grant probability derived from career allow rate.

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