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 .
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.
Response to Amendment
The amendment filed on 19 February, 2026 has been fully considered and entered. In response to the claim amendments, the previously raised rejections under 35 U.S.C. 112(b) are withdrawn.
Response to Arguments
Applicant's arguments filed 19 February, 2026 have been fully considered but they are not persuasive. Applicant argues that Du (US 2020/0327403; hereinafter Du) fails to teach that the neuron component is configured to receive an input signal having a first frequency and to output an output signal having a second frequency, wherein the output signal depends on the input signal and wherein the second frequency is different from the first frequency.
Examiner disagrees. Paragraph 0072 teaches that the nonlinear optical medium, having electromagnetically induced transparency, has three energy states (E1, E2, and E3). It further teaches that the particles are prepared in the E1 state, the coupling laser beam effects a transition from E2 to E3 and the probe laser beam effects a transition from state E1 to E3. Since the coupling laser beam and the probe laser beam operate to effect different energy transitions, they inherently operate at different frequencies by Bohr’s frequency rule (ΔE=hv; the frequency of a photon absorbed or emitted during an electronic transition is related to the energy difference between the two energy levels involved in the transition). Examiner is providing Finkelstein et al. (A practical guide to electromagnetically induced transparency in atomic vapor, New Journal of Physics, 2023) as an evidentiary reference to demonstrate how EIT works using this principle (see Fig. 1(a), having Λ energy level configuration similar to those disclosed by Du). In Fig. 1(a), the transition between states F1 and F’ has an energy difference (E1) that requires frequency (v1) for the transition to occur, whereas the transition between states F2 and F’ has an energy difference (E2) that requires a different frequency (v2) for the transition to occur. Since Du discloses that the probe beam and the coupling beam effect transitions between different energy levels having different energy differences, the probe beam and the coupling beam necessarily/inherently have different frequencies.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-3, 5-9, 14-15, 17-18, and 20 are rejected under 35 U.S.C. 102(a)(1) or 102(a)(2) as being anticipated by Du et al. (US 2020/0327403; hereinafter Du)
Regarding claim 1: Du discloses A device for providing an artificial neural network (Figs. 1A-1C), comprising: at least one optical neuron component (Fig. 1C, nonlinear optical medium is considered to be a neuron component for providing at least one neuron of the network; alternatively, as applied to claim 8, the entire neuron of Fig. 1C is also considered an optical neuron component for providing at least one neuron of the network) for providing at least one neuron of the network; wherein the neuron component is a nonlinear optical component; the neuron component is configured to receive an input signal having a first frequency (see Fig. 4A-B and paragraphs 0071-0072; input signal is signal from coupling laser 402); the neuron component is configured to output an output signal having a second frequency (see Fig. 4A-B and paragraphs 0071-0072; output signal is signal from probe laser 404); the output signal depends on the input signal (see paragraphs 0071-0072; the coupling laser provides the electromagnetically induced transparency, controlling whether the nonlinear optical material is transparent or opaque to the probe beam); and whereinthe second frequency is different from the first frequency (see paragraphs 0071-0072, as the nonlinear optical material has 3 unequal energy states E1, E2, and E3, and since the coupling laser effects a transition between E2 and E3 while the probe laser effects a transition between E1 and E3, the probe laser and the coupling laser inherently have different frequencies by Bohr’s frequency rule ΔE=hv).
Regarding claim 2: Du disclosesThe device of claim 1 (as applied above), comprisingat least one optical weighting component configured to output an output signal of the weighting component based on a weighting of an input signal of the weighting component (SLM of previous layer, see paragraphs 0045, 0048); wherein the neuron component is interconnecting with the weighting component to form the input signal of the neuron component at least partially from the output signal of the weighting component (see paragraphs 0045, 0048).
Regarding claim 3: Du disclosesThe device of claim 2 (as applied above), wherein the weighting component is configured to linearly transform the input signal of the weighting component to generate the output signal of the weighting component (see abstract, SLM performs linear operation).
Regarding claim 5: Du disclosesThe device of claim 1 (as applied above), wherein the neuron component is configured to transform the input signal of the neuron component in a nonlinear manner using at least one nonlinear optical effect to generate the output signal of the neuron component (see Fig. 1C, the neuron component, i.e. the nonlinear optical medium, does this).
Regarding claim 6: Du disclosesThe device of claim 1 (as applied above), wherein the neuron component is configured to provide an activation function with the input signal of the neuron component as the input by means of at least one nonlinear optical effect (see paragraph 0008).
Regarding claim 7: Du disclosesThe device of claim 5 (as applied above), wherein the at least one nonlinear effect involves at least one of the following effects: frequency multiplication, sum frequency generation, difference frequency generationan optical parametric process, optical parametric amplification (OPA), and a Kerr effect (all materials exhibit a Kerr effect; therefore, the nonlinear optical material inherently exhibits a Kerr effect, which is a nonlinear effect).
Regarding claim 8: Du disclosesThe device of claim 5, wherein the neuron component comprises at least one of the following materials in order to provide the at least one nonlinear optical effect: beta-barium borate (BBO), potassium dihydrogen phosphate (KDP), ammonium dihydrogen phosphate (ADP), lithium niobate, lithium iodate, silver thiogallate, silicon, Si-N, KTP, glass, quartz, sapphire, MgF, CaF, Yb:YAG, NeYAG, TiSa, and a laser medium (the SLMs include glass, see paragraph 0055, which is involved in transmitting coupling light to control the nonlinear optical effect).
Regarding claim 9: Du disclosesThe device of claim 1 (as applied above), wherein the neuron component is configured to output, depending on the input signal of the neuron component having a first amplitude and/or phase, an output signal of the neuron component having a second amplitude and/or phase, wherein the second amplitude and/or phase is different from the first amplitude and/or phase (see paragraph 0054, due to the electromagnetically induced transparency, depending on the input signal of the neuron component having a first amplitude and/or phase, an output signal of the neuron component will have a second amplitude and/or phase different from the first).
Regarding claim 14: Du disclosesA method for providing an artificial neural network (see paragraph 0018), comprising: providing at least one neuron of the network using at least one optical neuron component, wherein the neuron component is in the form of a nonlinear optical component (see paragraph 0018);receiving an input signal having a first frequency (see Fig. 4A-B and paragraphs 0071-0072; input signal is signal from coupling laser 402); and outputting an output signal of the neuron component having a second frequency (see Fig. 4A-B and paragraphs 0071-0072; output signal is signal from probe laser 404); wherein the output signal depends on the input signal (see paragraphs 0071-0072; the coupling laser provides the electromagnetically induced transparency, controlling whether the nonlinear optical material is transparent or opaque to the probe beam); and wherein the second frequency is different from the first frequency (see paragraphs 0071-0072, as the nonlinear optical material has 3 unequal energy states E1, E2, and E3, and since the coupling laser effects a transition between E2 and E3 while the probe laser effects a transition between E1 and E3, the probe laser and the coupling laser inherently have different frequencies by Bohr’s frequency rule ΔE=hv).
Regarding claim 15: Du disclosesThe method of claim 14 (as applied above), wherein the method is provided by a device for providing an artificial neural network (see Figs. 1A-1C and paragraph 0018), the device comprising at least one optical neuron component for providing at least one neuron of the network (Fig. 1C, nonlinear optical medium is an optical neuron component for providing at least one neuron of the network).
Regarding claim 17: Du disclosesThe device of claim 2 (as applied above), wherein the neuron component is configured to transform the input signal of the neuron component in a nonlinear manner using at least one nonlinear optical effect to generate the output signal of the neuron component (see Fig. 1C, the neuron component, i.e. the nonlinear optical medium, does this).
Regarding claim 18: Du disclosesThe device of claim 3 (as applied above), wherein the neuron component is configured to transform the input signal of the neuron component in a nonlinear manner using at least one nonlinear optical effect to generate the output signal of the neuron component (see Fig. 1C, the neuron component, i.e. the nonlinear optical medium, does this).
Regarding claim 20: Du disclosesThe device of claim 2 (as applied above), wherein the neuron component is configured to provide an activation function with the input signal of the neuron component as the input by means of at least one nonlinear optical effect (see paragraph 0008).
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.
Claims 10-13 are rejected under 35 U.S.C. 103 as being unpatentable over Du et al. (US 2020/0327403; hereinafter Du) in view of Rodrigues et al. (US 2021/0097378; hereinafter Rodrigues).
Regarding claim 10: Du discloses the device of claim 1, as applied above. Du fails to disclose an electronic and/or electro-optical interface assembly to at least one electronic vehicle component is arranged to provide the artificial neural network in a vehicle. However, Du does teach that optical artificial neural networks have a variety of applications including image recognition (see paragraph 0003). Rodrigues, also related to optical artificial neural networks (see title and abstract), teaches that optical neural networks can be configured for image recognition, to identify vehicles, pedestrians, traffic signs, etc. when used in transportation, and can interface with a processor, an electronic vehicle component, to provide the artificial neural network in a vehicle and support autonomous control of a vehicle (see paragraphs 0038, 0046, and 0070). Since it was taught by Rodrigues, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to use the device disclosed by Du to provide the artificial neural network in a vehicle, by modifying the Du device to include an electronic and/or electro-optic interface assembly to at least one electronic vehicle component, based on the teachings of Rodrigues, in order to enable autonomous control of a vehicle, a known use of artificial neural networks configured for image recognition.
Regarding claim 11: Du discloses the device of claim 1, as applied above. Du fails to disclose the device of claim 1 being part of a system including at least one vehicle component. However, Du does teach that optical artificial neural networks have a variety of applications including image recognition (see paragraph 0003). Rodrigues, also related to optical artificial neural networks (see title and abstract), teaches that optical neural networks can be configured for image recognition, to identify vehicles, pedestrians, traffic signs, etc. when used in transportation, and can interface with a processor, an electronic vehicle component, to provide the artificial neural network in a vehicle and support autonomous control of a vehicle (see paragraphs 0038, 0046, and 0070). Since it was taught by Rodrigues, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to use the device disclosed by Du in a system that also includes at least one vehicle component, by modifying the Du device to include an electronic and/or electro-optic interface assembly to at least one electronic vehicle component, based on the teachings of Rodrigues, in order to enable autonomous control of a vehicle, a known use of artificial neural networks configured for image recognition.
Regarding claim 12: Modified Du teachesThe system of claim 11 (as applied above), wherein the device comprises an electronic and/or electro-optical interface assembly (as described above; the electronic and/or electro-optical interface assembly would further include a controller, based on the disclosure of Du, to provide electrical signals to control the optical neuron components; see Du paragraph 0060), configured to: receive electrical input information from the vehicle component (see Rodrigues paragraphs 0038-0040); provide an optical input signal for the neural network based on the received input information (see paragraph 0060); and to provide electrical output information for the vehicle component based on the optical output signal of the neuron component (see Du paragraph 0080 and Rodrigues paragraphs 0038, 0046, and 0070).
Regarding claim 13: Modified Du teachesThe system of claim 12 (as applied above), wherein the at least one vehicle component comprises a detection device to generate the input information in the form of image information (see Du paragraph 0060), and wherein the at least one vehicle component comprises a driver assistance system for providing an automatic driving function to evaluate the output information by means of the driver assistance system, and to use the output information here as a classification of an environment of the vehicle (see Rodrigues paragraph 0046).
Claims 4, 16, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Du et al. (US 2020/0327403; hereinafter Du) in view of Haney et al. (US 2007/0147842; hereinafter Haney).
Regarding claims 4 and 16, respectively: Du discloses the device of claim 2 and claim 3, respectively, as applied above. Du fails to disclose that the weighting component is configured as a waveguide and/or exclusively comprises a waveguide to carry out the weighting of the input signal of the weighting component. However, the weighting component directs coupling light to the nonlinear optical medium. Waveguides are well known components for directing light from one location to another with low loss. Furthermore, before the effective filing date of the claimed invention, Haney taught integrating spatial light modulators with waveguides (see paragraph 0010). In order to better direct light to the nonlinear optical medium, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to configure the weighting component as a waveguide by integrating the disclosed spatial light modulators with them, since waveguides are well known in the art and since integrating the two components was previously taught by Haney.
Regarding claim 19: Modified Du teachesThe device of claim 4 (as applied above), wherein the neuron component is configured to transform the input signal of the neuron component in a nonlinear manner using at least one nonlinear optical effect to generate the output signal of the neuron component (see Fig. 1C, the neuron component, i.e. the nonlinear optical medium, does this).
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Kirsten D Endresen whose telephone number is (703)756-1533. The examiner can normally be reached Monday to Thursday.
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/KIRSTEN D. ENDRESEN/Examiner, Art Unit 2874
/THOMAS A HOLLWEG/Supervisory Patent Examiner, Art Unit 2874
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