DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. 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
2. 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-3 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. (U.S. patent pub. 2021/0012199 A1 will be further addressed as Zhang) and further in view of Schlegal et al.("A comparison of vector symbolic architectures," Artificial Intelligence Review (15 December 2021) Volume 55, Issue 6, pages 4526-4555, will be further referred to as Schlegal).
Regarding claim 1: Zhang et al. discloses a neural network (Zhang; paragraph 0071) comprising:
a fully-connected neural layer (Zhang; paragraph 0052)that implements a generalized bundling function to transform a first set of symbols into a second set of symbols (Zhang; paragraph 0072, i.e. text to code conversion), wherein: the generalized bundling function comprises a bundling operation that uses a weight matrix to influence amounts by which individual values of symbols of the first set of symbols contribute to the second set of symbols (Zhang; paragraphs 0072 and 0098), and
the amounts by which the individual values of the symbols of the first set of symbols contribute to the second set of symbols vary based on the individual values of the symbols of the first set of symbols (Zhang; paragraphs 0072 and 0098). Zhang et al. does not teach the feature of a “generalized bundling function.” Schlegal teaches a “generalized bundling function” (Schlegal; page 4530 second paragraph and page 4544 second paragraph). It would have been obvious to one ordinary skilled in the art to combine the teaching of Schlegal to the disclosure of Zhang because they are analogous in the field of vector symbol processing using neural network. One ordinary skilled in the art would have been motivated to combine the teaching of Schlegal into the disclosure of Zhang in order to increase speed and efficiency.
Regarding claim 2: The neural network of claim 1, wherein: in accordance with the weight matrix being a first size, the fully-connected layer transforms the first set of symbols to a different dimensionality in the second set of symbols (Zhang; paragraphs 0052, 0072, and 0098); and
in accordance with the weight matrix being a second size, the fully-connected layer transforms the first set of symbols to a same dimensionality in the second set of symbols (Zhang; paragraph 0089).
Regarding claim 3: The neural network of claim 1, wherein: the first set of symbols comprises a first set of Fourier holographic reduced representation (FHRR) vector-symbolic architecture (VSA) symbols; and the second set of symbols comprises a second set of FHRR VSA symbols (Schlegal; page 4526, paragraphs 3-4, page 4528, 2nd paragraph, and paragraph 4530, 3rd paragraph).
Allowable Subject Matter
3. Claims 18-20 are allowed.
4. Claims 4-17 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.
Contact Information
5. Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANAND BHATNAGAR whose telephone number is (571)272-7416. The examiner can normally be reached on M-F 7:30am-4:00pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Vu Le can be reached on 571-272-4650. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ANAND P BHATNAGAR/
Primary Examiner, Art Unit 2668
August 8, 2026
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