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 .
Continued Examination Under 37 CFR 1.114
2. 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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.
Response to Arguments
3. Applicant's arguments received 05/12/2026 with respect to claim subject matter eligibility have been considered but are moot in view of the new ground(s) of rejection. Detailed response is given in sections 4-5 as set forth below in this Office action.
Claim Rejections - 35 USC § 101
4. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 101 that form the basis for the rejections under this section made in this Office action:
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.
5. Claims 1-2, 4-8, and 10-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Under the 2019 PEG (now been incorporated into MPEP 2106), the revised procedure for determining whether a claim is "directed to" a judicial exception requires a two-prong inquiry into whether the claim recites: (1) any judicial exceptions, including certain groupings of abstract ideas (i.e., mathematical concepts, certain methods of organizing human interactions such as a fundamental economic practice, or mental processes); and (2) additional elements that integrate the judicial exception into a practical application (see MPEP § 2106.05(a)-(c), (e)-(h)).
Only if a claim (1) recites a judicial exception and (2) does not integrate that exception into a practical application, do we then look to whether the claim: (3) adds a specific limitation beyond the judicial exception that is not "well-understood, routine, conventional" in the field (see MPEP § 2106.0S(d)); or (4) simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception.
Claims 1-2, 4-8, and 10-20 are directed to an abstract idea of information processing using digital encoder/decoder.
Specifically, representative claim 1 recites:
An information processing apparatus comprising:
(S1) an encoder configured to encode input content including a sequence of data to convert the input content into a latent variable;
(S2) a decoder configured to decode the latent variable to reconfigure output content, wherein the encoder and a decoder are variational auto encoder (VAE)-trained; and
(S3) circuitry configured to
calculate a loss function including a first term based on a difference between a likelihood of the input content and a reference likelihood indicating a desired degree of commonness or eccentricity of the output content, and a second term based on a reality likelihood, the reality likelihood indicating a probability that the input content is content generated by a human,
lower a gradient of the loss function to update the latent variable such that the likelihood approaches the reference likelihood while the reality likelihood is maintained,
control the decoder to decode the updated latent variable to reconfigure output content, and
obtain the reality likelihood using a reality evaluator that is trained based on first content labeled with a real class indicating content generated by a human and second content labeled with a fake class indicating content not generated by a human.
The claim limitations in the abstract idea have been highlighted in bold above; the remaining limitations are “additional elements”.
The highlighted portion of the claim constitutes an abstract idea under the 2019 Revised Patent Subject Matter Eligibility Guidance and the additional elements are NOT sufficient to amount to significantly more than the judicial exceptions, as analyzed below:
Step
Analysis
1. Statutory Category ?
Yes.
System/Apparatus
2A - Prong 1: Judicial Exception Recited?
Yes.
See the bolded portion as listed above.
Under its broadest reasonable interpretation (BRI), each and/or the combination of the limitations S1, S2 and S3 recited in the bolded portion encompasses mathematical concepts and/or calculations, namely a series of calculations leading to one or more numerical results or answers, which also encompasses mental processes, i.e. data manipulation, evaluation and judgment, that can be performed in the human mind or by a human using a pen and paper. Note, the courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. See MPEP 2106.04(a)(2).III
Claim 1 recites the limitation “wherein the encoder and a decoder are variational auto encoder (VAE)-trained” at a high level of generality. Under the BRI, this limitation encompasses a trained machine learning AI model such as a trained neural network model. The claim does not specify how the variational autoencoder is trained. It may involve optimizing the AI models using a series of mathematical calculations to iteratively adjust the algorithms and/or parameter values of the AI models, therefore encompasses mathematical concepts. Further, the combination of the limitations S1/S2/S3 only recites the outcome of the trained VAE which is used like a “Black Box AI” tool whose internal workings are a mystery of math concepts to its users. As such, the limitation “wherein the encoder and a decoder are variational auto encoder (VAE)-trained” is treated as part of the abstract idea identified for claim 1.
Claim 1 recites the new limitation “obtain the reality likelihood using a reality evaluator that is trained based on first content labeled with a real class indicating content generated by a human and second content labeled with a fake class indicating content not generated by a human”. Under its BRI, “obtain the reality likelihood using a reality evaluator” encompasses a mental process of obtaining the “the reality likelihood” via the “reality evaluator” (i.e., a pre-trained AI model) wherein the “reality evaluator” is used like a “Black Box AI” tool whose internal workings are a mystery of math concepts to its users. In light of USPTO’s July 2024 Subject Matter Eligibility Examples (e.g., Examples 47-49), such a recitation of the AI tool does not negate the mental nature of the claim limitation.
Particular evaluation is given to the limitation of representative claim 1about the training of the “reality evaluator” in light of the guidance provided by Ex Parte Desjardins.
Ex Parte Desjardins (Appeal No. 2024-000567) clarified that claims for training machine learning models can be patent-eligible if they integrate an abstract idea into a practical application and demonstrate technological improvements. Specifically, the USPTO Appeals Review Panel (ARP) found that the claims integrated the abstract idea into a practical application by reciting the additional limitation “training the machine learning model on the second machine learning task by training the machine learning model on the second training data to adjust the first values of the plurality of parameters to optimize performance of the machine learning model on the second machine learning task while protecting performance of the machine learning model on the first machine learning task.” The ARP affirmed that at least the above limitation of independent claim 1 reflects improvements in how the machine learning model operates, such as reduced storage, system simplification. In the instant case, however, the claimed strategy of training the “reality evaluator” requires merely “…based on first content labeled with a real class indicating content generated by a human and second content labeled with a fake class indicating content not generated by a human.” Under the BRI, this limitation encompasses processes of binning/clustering/labelling the “first content” and the “second content” selected from the existing training data by a human, and training the “reality evaluator” (AI model) using the labelled training data. This kind of binning/clustering/labelling the selected training data to generate inputs into the AI model may be practically performed in the human mind using observation, evaluation, judgment, and opinion. The current claims of the present application do not specify any particular training algorithm for training the “reality evaluator”. Under the BRI, it may involve optimizing the AI model using a series of mathematical calculations to iteratively adjust the algorithm and/or parameter values of the AI model, therefore encompasses mathematical concepts. Neither the claims nor the Specification specifies and/or demonstrates that the claimed training of the “reality evaluator” reflects a new and useful improvement such as improving the functioning of a machine learning model, which involved memory savings and reduced system complexity, as identified by the Ex Parte Desjardins decision. Accordingly, the instant claims are not analogous to the claims at issue in Ex parte Desjardin which is fact specific.
Nothing in the bolded portion precludes the limitations S1/S2/S3 from practically being performed in the mind and/or with the aid of pen/paper. Furthermore, according to the MPEP 2106.04(a)(2), if a claim limitation, under its broadest reasonable interpretation, covers mental processes except for the mention of generic computer components performing computing activities via basic function of the computer, then the claim is likely considered to be directed to an ineligible abstract idea, as it essentially describes a mental process that could be performed by a human without the computer components adding any significant practical application beyond the abstract concept itself.
Therefore, the bolded portion of instant claim 1, reciting a series of mathematical concepts and mental process, amounts to an abstract idea falling within a combination of the “Mental Process” and “Mathematical Concepts” groupings of Abstract Ideas defined by the 2019 PEG.
2A - Prong 2: Integrated into a Practical Application?
No.
Claim 1 does not recite any additional element that can be considered to be qualified for being “significantly more” to impose any meaningful limits on practicing the abstract idea.
The claim as a whole does not meet any of the following criteria to integrate the abstract idea into a practical application (See MPEP 2106.04(d)(2)):
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.
2B: Claim provides an Inventive Concept?
No.
Focusing on what the inventors have invented exactly, it is deemed that the “core” of the representative claim 1 is directed to an algorithm of mathematically manipulating existing information to generate output. Under its BRI, the claimed algorithm falls within a combination of the “Mental Process” and “Mathematical Concepts” groupings of abstract ideas. The claim does not recite any additional limitation that would reflect an inventive concept or amount to more than mere instructions to apply the judicial exception using generic computer components.
In particular, Variational Autoencoders (VAEs) as a type of generative model that provide a probabilistic approach to describing an observation in latent space are well-known in the art (e.g., Diederik P. Kingma and Max Welling: Auto-Encoding Variational Bayes”, 2013). Processes of preparing training data such as binning/clustering/labelling the contents selected from the existing training data by a human, and training the AI model using the labelled training data are all well-understood, routine, conventional in the art, they do not provide any inventive concepts or reflect a qualified improvement. See MPEP 2106.05.
The claim is therefore ineligible under 35 USC 101.
The dependent claims 2, 4-8, and 10-18 inherit attributes of the independent claim 1, but does not add anything which would render the claimed invention a patent eligible application of the abstract idea. The claim merely extends (or narrows) the abstract idea which does not amount for "significant more" because it merely adds details to the algorithm which forms the abstract idea as discussed above.
Claims 19-20 are rejected under 35 U.S.C. § 101 for the same reason as for claim 1 set forth above.
Contact Information
6. Any inquiry concerning this communication or earlier communications from the examiner should be directed to JIANCHUN QIN whose telephone number is (571)272-5981. The examiner can normally be reached 9AM-5:30PM EST M-F.
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, Dedei Hammond can be reached at (571)270-7938. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JIANCHUN QIN/Primary Examiner, Art Unit 2837
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