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 § 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 1-18, 22 and 24 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The limitations, under their broadest reasonable interpretation, cover mental process (concept performed in a human mind, including as observation, evaluation, judgment, opinion, organizing human activity and mathematical problem solving and calculations). The claims recite “determining a set of convolutional weights for the dynamic convolutional kernel, each convolutional weight of the set of convolutional weights determined by applying respective spatial attention weights in the spatial attention weight set, input channel attention weights in the input channel attention weight set, and output channel attention weights in the output channel weight set and applying the set of convolutional weights to the input feature map to generate an output feature map”. This judicial exception is not integrated into a practical application because the steps do not add meaningful limitations to be considered specifically applied to a particular technological problem to be solved .The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the steps of the claimed invention can be done mentally using paper/pencil, solving mathematical problem and no additional features in the claims would preclude them from being performed as such except for the generic computer elements and generic convolution neural network recited at high level of generality (i.e., processor, memory, convolution learning) .
According to the USPTO guidelines, a claim is directed to non-statutory subject matter if:
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis:
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Using the two-step inquiry, it is clear that claims 1, 5 and 6 are directed to an abstract idea as shown below:
Regarding claims 1, 9 and 17
STEP 1: Do the claims fall within one of the statutory categories?
YES.
Claim(s) 1, 9 and 17 are directed to a method, a system and a non-transitory readable storage medium storing computer program, i.e. process, system and manufacture.
STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea?
YES.
The claims are directed toward a mental process and solving mathematical problem (i.e. abstract idea).
With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas:
Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations;
Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgment, opinion).
claims 1, 9 and 17 comprise a mental process that can be practicably performed in the human mind and solving mathematical problem (or generic computers or components configured to perform the process and convolution neural network) and, therefore, an abstract idea.
Regarding claims 1, 9 and 17 (representative claim 9):
A system comprising: a processor; and a non-transitory computer-readable storage medium containing computer program code for execution by the processor (generic computer hard/software component) for:
receiving an input feature map for a convolutional layer of a neural network implementing a dynamic convolutional kernel (collecting data which is insignificant extra solution activity for solving the mathematical problem based on mathematical function formulation),
determining a plurality of attention weight sets based on the input feature map, the plurality of attention weight sets including spatial attention weights describing weights for a plurality of spatial positions, input channel attention weights describing attention weights for a plurality of input channels, and output channel attention weights describing attention weights for a plurality of output channels (solving mathematical function problem using the collected data based on human intelligence i.e. mental process using paper/pencil),
determining a set of convolutional weights for the dynamic convolutional kernel, each convolutional weight of the set of convolutional weights determined by applying respective spatial attention weights in the spatial attention weight set, input channel attention weights in the input channel attention weight set, and output channel attention weights in the output channel weight set (solving mathematical function problem using the acquired result using paper/pencil based on human intelligence i.e. mental process), and
applying the set of convolutional weights to the input feature map to generate an output feature map (solving the mathematical function using collected data and acquired result using pap/pencil and post solution actions, which is a form of insignificant extra-solution activity).
The above limitations, as drafted, is a simple process that, under their broadest reasonable interpretation, covers performance of the limitations in the mind or by a human intelligence and solving mathematical problem. Furthermore limitations, “a processor; and a non-transitory computer-readable storage medium containing computer program code for execution by the processor (generic computer hard/software component) for: receiving an input feature map for a convolutional layer of a neural network implementing a dynamic convolutional kernel (collecting data which is insignificant extra solution activity for solving the mathematical problem based on mathematical function formulation), determining a plurality of attention weight sets based on the input feature map, the plurality of attention weight sets including spatial attention weights describing weights for a plurality of spatial positions, input channel attention weights describing attention weights for a plurality of input channels, and output channel attention weights describing attention weights for a plurality of output channels (solving mathematical function problem using the collected data based on human intelligence i.e. mental process using paper/pencil), determining a set of convolutional weights for the dynamic convolutional kernel, each convolutional weight of the set of convolutional weights determined by applying respective spatial attention weights in the spatial attention weight set, input channel attention weights in the input channel attention weight set, and output channel attention weights in the output channel weight set (solving mathematical function problem using the acquired result using paper/pencil based on human intelligence i.e. mental process), and applying the set of convolutional weights to the input feature map to generate an output feature map (solving the mathematical function using collected data and acquired result using pap/pencil and post solution actions, which is a form of insignificant extra-solution activity)” are insignificant.
The Examiner notes that under MPEP 2106.04(A) (2) (III), the courts consider a mental process (thinking, human intelligence) that can be performed in the mind/intelligence using a paper and pencil to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[Mental processes and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978).
Furthermore the Examiner also notes that even if you combined the math with the mental process, a combination of abstract ideas don't make a claim eligible. See MPEP 2106.04(II)(A)(2): Because a judicial exception is not eligible subject matter, Bilski, 561 U.S. at 601, 95 USPQ2d at 1005-06 (quoting Chakrabarty, 447 U.S. at 309, 206 USPQ at 197 (1980)), if there are no additional claim elements besides the judicial exception, or if the additional claim elements merely recite another judicial exception, that is insufficient to integrate the judicial exception into a practical application. See, e.g., RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1327, 122 USPQ2d 1377 (Fed. Cir. 2017) ("Adding one abstract idea (math) to another abstract idea (encoding and decoding) does not render the claim non-abstract").
Other than generic and well-known computer hardware/software and generic convolution neural network recited in the independent claims 1, 9 and 17 disclosed in the specification, nothing in the claims 1, 9 and 17 elements preclude the processing from being performed as mental process, or merely based on the observations, evaluation, judgement, thought process using paper/pencil and solving mathematical function. Limitations determining a set of convolutional weights for the dynamic convolutional kernel, each convolutional weight of the set of convolutional weights determined by applying respective spatial attention weights in the spatial attention weight set, input channel attention weights in the input channel attention weight set, and output channel attention weights in the output channel weight set and applying the set of convolutional weights to the input feature map to generate an output feature map recited in independent claims 1, 9 and 17 is a mere idea of a solution without details per MPEP 2106.05( f ) or the idea of a technological environment without detail per MPEP 2106.05 ( h ). The generic computing hardware/software and convolution neural network are recited as just to automate the mental process of mathematical problem solving(Step 2A, prong 1 Test Abstract idea = Yes).
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
[YES/NO].
The claims do not recite additional elements that integrate the judicial exception into a practical application.
With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application:
an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to affect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application:
an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea;
an additional element adds insignificant extra-solution activity to the judicial exception; and
an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.
Claim(s) 1, 8 and 15 do not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application.
Claim(s) 1, 9 and 17 recite: (representative claim 9):
A system comprising: a processor; and a non-transitory computer-readable storage medium containing computer program code for execution by the processor (generic computer hard/software component) for:
receiving an input feature map for a convolutional layer of a neural network implementing a dynamic convolutional kernel (collecting data which is insignificant extra solution activity for solving the mathematical problem based on mathematical function formulation),
determining a plurality of attention weight sets based on the input feature map, the plurality of attention weight sets including spatial attention weights describing weights for a plurality of spatial positions, input channel attention weights describing attention weights for a plurality of input channels, and output channel attention weights describing attention weights for a plurality of output channels (solving mathematical function problem using the collected data based on human intelligence i.e. mental process using paper/pencil),
determining a set of convolutional weights for the dynamic convolutional kernel, each convolutional weight of the set of convolutional weights determined by applying respective spatial attention weights in the spatial attention weight set, input channel attention weights in the input channel attention weight set, and output channel attention weights in the output channel weight set (solving mathematical function problem using the acquired result using paper/pencil based on human intelligence i.e. mental process), and
applying the set of convolutional weights to the input feature map to generate an output feature map (solving the mathematical function using collected data and acquired result using pap/pencil and post solution actions, which is a form of insignificant extra-solution activity).
These limitations are recited at a high level of generality (i.e. as a general action or calculation being taken based on the results of the acquiring step) and amounts to mere post solution actions, which is a form of insignificant extra-solution activity without further detail. Further, the claims 1, 9 and 17 are claimed generically and are operating in their ordinary capacity such that they do not use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
As stated above other than generic and well-known computer hardware/software and generic convolution neural network recited in the independent claims 1, 9 and 17 disclosed in the specification, nothing in the claims 1, 9 and 17 elements preclude the processing from being performed as mental process, or merely based on the observations, evaluation, judgement, thought process using paper/pencil and solving mathematical function. Limitations determining a set of convolutional weights for the dynamic convolutional kernel, each convolutional weight of the set of convolutional weights determined by applying respective spatial attention weights in the spatial attention weight set, input channel attention weights in the input channel attention weight set, and output channel attention weights in the output channel weight set and applying the set of convolutional weights to the input feature map to generate an output feature map recited in independent claims 1, 9 and 17 is a mere idea of a solution without details per MPEP 2106.05( f ) or the idea of a technological environment without detail per MPEP 2106.05 ( h ). The generic computing hardware/software and generic convolution neural network are recited as just to automate the mental process of mathematical problem solving (Step 2A, prong 2 Test Abstract idea = Yes).
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
NO.
The claims do not recite additional elements that amount to significantly more than the judicial exception.
With regard to STEP 2B, whether the claims recite additional elements that provide significantly more than the recited judicial exception, the guidelines specify that the pre-guideline procedure is still in effect. Specifically, that examiners should continue to consider whether an additional element or combination of elements:
adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
As stated above, other than generic and well-known computer hardware/software and generic convolution neural network recited in the independent claims 1, 9 and 17 disclosed in the specification, nothing in the claims 1, 9 and 17 elements preclude the processing from being performed as mental process, or merely based on the observations, evaluation, judgement, thought process using paper/pencil and solving mathematical function. Limitations determining a set of convolutional weights for the dynamic convolutional kernel, each convolutional weight of the set of convolutional weights determined by applying respective spatial attention weights in the spatial attention weight set, input channel attention weights in the input channel attention weight set, and output channel attention weights in the output channel weight set and applying the set of convolutional weights to the input feature map to generate an output feature map recited in independent claims 1, 9 and 17 is a mere idea of a solution without details per MPEP 2106.05( f ) or the idea of a technological environment without detail per MPEP 2106.05 ( h ). The generic computing hardware/software and convolution neural network are recited as just to automate the mental process of mathematical problem solving
Thus, since Claim(s) 1, 9 and 17 are: (a) directed toward an abstract idea and mathematical function problem solving using human intelligence, (b) do not recite additional elements that integrate the judicial exception into a practical application, and (c) do not recite additional elements that amount to significantly more than the judicial exception, it is clear that Claim(s) 1, 9 and 17 are not eligible subject matter under 35 U.S.C 101 (Step 2B, Test Abstract idea = Yes).
Regarding dependent claims: 2-8, 10-16, 18, 22 and 24 the limitations further limit the abstract idea of independent claims 1, 9 and 17 of solving mathematical problem using human intelligence i.e. mental process , the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. The limitations of dependent claims 2-8, 10-16, 18, 22 and 24 fall under (mental process including observation and evaluation, and judgement and mathematical problem solving which can be done mentally in the human mind) OR (insignificant pre/post-solution extra activity of generating/gathering data, performing mathematical calculation) OR (generic computers or components configured to perform the process), the generic convolution neural network model recited in the dependent claims 2-8, 10-16, 18, 22 and 24 and as disclosed in the specification is a mere idea of a solution without details per MPEP 2106.05( f ) or the idea of a technological environment without detail per MPEP 2106.05 ( h ).
Communication
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ISHRAT I SHERALI whose telephone number is (571)272-7398. The examiner can normally be reached Monday-Friday 8:00AM -5:00 PM.
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ISHRAT I. SHERALI
Examiner
Art Unit 2667
/ISHRAT I SHERALI/Primary Examiner, Art Unit 2667
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