DETAILED ACTION
1. This office action is in response to the Application No. 18981595 filed on 01/29/2026. Claims 1-7 and 9-18 are presented for examination and are currently pending.
Notice of Pre-AIA or AIA Status
2. 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
3. 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has been withdrawn pursuant to 37 CFR 1.114. Applicant’s submission filed on
01/29/2026 has been entered.
Claim Objections
4. Claim 7 is objected to because of the following informalities:
In claim 7, the limitation recites “... to improve prediction accuracy for time series input sequences with limited historical dat..”. It should be “... to improve prediction accuracy for time series input sequences with limited historical data”.
Appropriate correction is required.
Response to Arguments
5. Upon further review of the claim amendments filed on 01/29/2026 and applicant arguments. It is noted that the arguments are persuasive. As a result, the prior art rejection has been withdrawn.
The claim amendment of 01/29/2026 has overcome some of the 112(b) indefinite rejection. However, new 112(a) and 112(b) has been issued.
On page 10-11 of the remarks, the Applicant argued that “Applicant maintains that the claims as previously presented were not directed to a judicial exception and could not practically be performed in the human mind. As amended, Claim 1 further clarifies this point by expressly reciting specific technical operations that cannot practically be performed mentally, and the Examiner's analysis improperly applies a "could be imagined" standard rather than the controlling "practically performed" standard set forth in the 2019 PEG and subsequent USPTO guidance. First, Claim 1 recites "a variational autoencoder encoder configured to compress the padded input sequence into a latent space vector through dimensional reduction, the latent space vector capturing temporal patterns and dependencies present in the padded input sequence." Variational autoencoders generate continuous latent vector representations through machine-learned probabilistic mappings and numerical optimization. These latent vectors are mathematical constructs that do not exist in the human mind and cannot be generated, represented, or manipulated mentally.
On page 11 of the remarks, the Applicant argued that “Second, Claim 1 recites "a latent transformer configured to process the latent space vector, the latent transformer operating directly on the latent space vector without embedding layers or positional encoding layers." This limitation recites a specific neural network architecture that performs self-attention operations on latent vectors. The attention-weight computation and transformation of high-dimensional latent vectors required by such a transformer cannot practically be performed by a human”.
The above arguments are not persuasive because the use of a variational autoencoder to compress data is a conventional operation used in the technological field for data compression. The “variational autoencoder” and “latent transformer” are additional elements which are mere instructions to apply an exception as analyzed in the detailed 101 rejection.
In addition, the Applicant argued that “Variational autoencoders generate continuous latent vector representations through machine-learned probabilistic mappings and numerical optimization”. This argument is not persuasive because the variational autoencoders generate continuous latent vector representations through machine-learned probabilistic mappings and numerical optimization which is not reflected in the claims. As a result, it appears that the Applicant is arguing what is not claimed.
The Applicant’s argument that “a latent transformer configured to process the latent space vector, the latent transformer operating directly on the latent space vector without embedding layers or positional encoding layers” is a specific architecture is not persuasive because these limitations are additional elements as analyzed in the 101 rejection inn this office action. The Applicant needs to provide detailed argument of how the abstract ideas enumerated in the 101 rejection including the additional elements and how the claim as a whole leads to an improvement in the technological field.
On page 11 of the remarks, the Applicant argued that “Third, Claim 1 recites that "during training the decoder learns to reconstruct the removed terminal data points in positions corresponding to the context-aware padding values by minimizing reconstruction error between the predicted sequence and the original time series input sequence." This training paradigm requires iterative numerical optimization over learned parameters using reconstruction loss. Such optimization operates on latent representations and error gradients that are not cognitively accessible and cannot be mentally executed”.
The above argument is not persuasive because the argued limitation above are analyzed in the 101 rejection in this office action as additional elements. The Applicant needs to provide detailed argument of how the abstract ideas enumerated in the 101 rejection including the additional elements and how the claim as a whole leads to an improvement in the technological field.
On page 11 of the remarks, the Applicant argued that “Fourth, Claim 1 recites "a pattern library configured to store a plurality of historical latent space vectors indexed using locality-sensitive hashing." Locality-sensitive hashing is a specific algorithmic technique for approximate nearest-neighbor indexing in high-dimensional vector spaces. The generation of hash functions and bucket-based similarity retrieval for latent vectors cannot practically be performed in the human mind”.
The above argument is not persuasive because the argued limitation above are analyzed in the 101 rejection as additional elements. The limitation is directed to an insignificant extra solution activity of data gathering (data gathering/storage of latent space vectors indexed using locality-sensitive hashing). The Applicant needs to provide detailed argument of how the abstract ideas enumerated in the 101 rejection including the additional elements and how the claim as a whole leads to an improvement in the technological field.
On page 11 of the remarks, the Applicant argued that “Fifth, Claim 1 recites "a pattern matching component configured to calculate similarity between the latent space vector and the plurality of historical latent space vectors using cosine distance metrics." Cosine similarity calculations require vector dot products and magnitude computations across latent dimensions. These operations cannot practically be carried out mentally or with pen and paper, particularly when applied to machine-generated latent vectors”.
On page 11-12 of the remarks, the Applicant argued that “The Examiner's characterization of these limitations as mental processes improperly abstracts away the machine-only representations expressly recited in the claims. Under the 2019 PEG, claim limitations that require operations on representations that do not exist in the human mind, and that cannot practically be performed mentally, do not fall within the mental processes grouping. Here, Claim 1 expressly recites operations on latent space vectors, locality-sensitive hashing indices, and cosine distance calculations-none of which can practically be performed in the human mind”.
The above argument is not persuasive because the arguments are directed to the abstract ideas. The calculation of the similarity between the latent space vector and the plurality of historical latent space vectors using cosine distance metrics are clearly mathematical concepts. Mathematical concepts are classified under abstract ideas. As a result, the limitations are directed to judicial exception.
On pages 12-13 of the remarks, the Applicant argued that “The amended claims impose meaningful limitations that confine the scope of any alleged abstract idea and prevent preemption. First, the claims recite a specific technical architecture, not a result. Claim 1 does not merely recite the goal of "predicting time series values." Instead, it recites a particular arrangement of components, including a variational autoencoder encoder and decoder, a latent transformer operating without embedding or positional encoding layers, a pattern library indexed using locality-sensitive hashing, and a pattern matching component using cosine distance metrics. This is one of many possible technical approaches to time series prediction, and the claims do not preempt alternative approaches. Second, the claims require specific algorithmic implementations. Claim 1 requires locality-sensitive hashing for indexing historical latent vectors and cosine distance metrics for similarity calculation. Systems employing different indexing techniques (e.g., k-d trees, ball trees, brute-force search) or different similarity measures (e.g., Euclidean distance, Manhattan distance, or learned similarity functions) fall outside the scope of the claims. This demonstrates that the claims do not preempt the field. Third, the claims require a specific neural network configuration. The requirement that the latent transformer operates directly on latent vectors without embedding or positional encoding layers distinguishes the claimed system from conventional transformer architectures and from systems using recurrent or convolutional neural networks. Fourth, the claims require a specific training methodology. The decoder is trained to reconstruct withheld terminal data points corresponding to context-aware padding values. This reconstruction-based learning approach is distinct from other training paradigms such as next- token prediction, masked modeling, or direct regression on future values. Fifth, the claims require context-aware padding based on statistical analysis of the input sequence, including seasonality, trend, or volatility measures. This is a technical approach distinct from simple zero-padding or fixed-value padding strategies. Under MPEP 2106.04(d), a claim integrates a judicial exception into a practical application when it imposes meaningful limitations that represent more than a drafting effort designed to monopolize the exception. The specific architectural, algorithmic, and methodological requirements recited in Claim 1 collectively impose such meaningful limitations. Because the amended claims integrate any alleged abstract idea into a practical application, the §101 analysis should end at Step 2A, Prong Two without proceeding to Step 2B”.
The above argument that the claimed invention recites a particular arrangement of components which includes a variational autoencoder encoder and decoder, a latent transformer operating without embedding or positional encoding layers, a pattern library indexed using locality-sensitive hashing, and a pattern matching component using cosine distance metrics is not persuasive. This is because the alleged specific component “variational autoencoder encoder and decoder” argued by the Applicant are mere instructions to apply an exception (i.e., additional element). The limitation “latent transformer operating without embedding or positional encoding layers” are limitations directed to generally linking the use of a judicial exception to a particular technological environment or field of use (i.e., additional element). The limitation “locality-sensitive hashing” and “cosine distance metrics” are abstract ideas as analyzed in the 101 rejection of this office action.
Furthermore, the argument that the claimed invention includes specific architectural, algorithmic, and methodological requirements that imposes meaningful limitations is not persuasive because the arguments are conclusory statement that include no details or steps as to how these limitations integrates the abstract ideas into practical application.
According to MPEP 2106(d)(1), Second, if the specification sets forth an improvement in technology, the claim must be evaluated to ensure that the claim itself reflects the disclosed improvement. That is, the claim includes the components or steps of the invention that provide the improvement described in the specification”.
On page 13 of the remarks, the Applicant argued that “Even if the analysis were to proceed to Step 2B, the amended claims recite significantly more than any alleged judicial exception. The Examiner characterizes the additional elements as "generic computer components" or "mere instructions to apply an exception." This characterization is incorrect. Claim 1 recites a non-conventional arrangement of specific technical elements, including a variational autoencoder-based encoding and decoding pipeline, a latent transformer without embedding or positional encoding layers, locality-sensitive hashing for latent pattern indexing, and cosine-distance-based similarity matching. The Examiner has not provided evidence establishing that this particular combination of techniques was well-understood, routine, or conventional at the time of filing. To the contrary, the §103 rejection relies on combining multiple references from different domains to approximate the claimed system, which confirms that the claimed arrangement was not conventional in the art. Accordingly, Claim 1 recites significantly more than any alleged abstract idea”.
The above argument is not persuasive because the specific technical elements in the claim which includes variational autoencoder-based encoding and decoding pipeline are mere instructions to apply an exception (i.e., additional element) and the latent transformer without embedding or positional encoding layers are limitations that are directed to generally linking the use of a judicial exception to a particular technological environment or field of use (i.e., additional element). The locality-sensitive hashing for latent pattern indexing, and cosine-distance-based similarity matching are abstract ideas as analyzed in the 101 rejection. None of the above highlighted limitations are analyzed as well-understood, routine, or conventional in the 101 rejection of this office action.
Furthermore, as regards the argument that “the §103 rejection relies on combining multiple references from different domains to approximate the claimed system, which confirms that the claimed arrangement was not conventional in the art” is not persuasive because the analysis for an obviousness rejection (103 rejection) of a claimed invention is distinct from a subject matter eligibility analysis for a 101 rejection, and the findings in the rejections made under 35 U.S.C. 101 do not influence findings in the rejections made under 35 U.S.C. 103, and vice versa.
In addition, the claimed invention as analyzed in the 101 rejection includes abstract ideas and additional elements. As a result, the applicant needs to include detailed arguments of how the additional elements including the abstract ideas and how the claimed invention as a whole leads to the improvement of the technological field or functioning of the computer.
According to MPEP 2106.05(a): “It is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by
one or more additional elements. See the discussion of Diamond v. Diehr, 450 U.S.
175, 187 and 191-92, 209 USPQ 1, 10 (1981) in subsection II, below. In addition, the
improvement can be provided by the additional element(s) in combination with the
recited judicial exception”.
On page 14, the Applicant argued that “The amended claims recite specific technical operations that cannot practically be performed in the human mind, including variational autoencoder processing, latent transformer computation without embedding or positional encoding layers, locality-sensitive hashing indexing, and cosine distance similarity calculation. Even if viewed as involving an abstract idea, the claims integrate any such idea into a practical application through meaningful limitations that prevent preemption. The claims further recite significantly more than any alleged exception through a non-conventional combination of technical features. Applicant therefore respectfully requests withdrawal of the §101 rejection”.
The argument above is not persuasive because the additional elements needs to demonstrate that the claims as a whole integrate into practical application by arguing the claims as a whole improve the functioning of the computer or technological field.
As a result, the 101 rejection is maintained and adjust to reflect the amendments.
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.
6. Claims 1-7 and 9-18 are rejected under 35 U.S.C 101 because the claimed invention is directed towards an abstract idea without significantly more.
Step 1
Independent claim 1 is directed to a system, and falls into one of the four statutory categories.
Step 2A, Prong 1
Claim 1 recites the following abstract ideas:
truncate the time series input sequence by removing a predetermined number of terminal values to create a truncated sequence (Mental process directed to observing and making a judgement of when to truncate values from a sequence);
analyze statistical properties of the time series input sequence including at least one of seasonality patterns, trend components, or volatility measures (Mental process directed to analyzing seasonality patterns, trend components, or volatility measures by observation); and
generate context-aware padding values based on the analyzed statistical properties (Mental process directed to generating context-aware values which can be done by observation and making a judgement on the padding values) and
append the context-aware padding values to the truncated sequence to create a padded input sequence matching the first length (Mental process directed to observing and making a judgement of adding padding value to the truncated sequence);
reconstruct, from the latent space vector, a predicted sequence matching the first length (Mental process directed to observing and making a judgement of matching values of the sequence and the first length),
each historical latent space vector derived from a previously processed time series input sequence and indexed using locality-sensitive hashing (Mental process directed to using locality-sensitive hashing to derive historical latent space vector by observing previously processed time series input sequence);
calculate similarity between the latent space vector and the plurality of historical latent space vectors using cosine distance metrics (Mathematical concepts directed to using cosine distance metrics to calculate similarity between latent space vector and the plurality of historical latent space vectors); and
identify one or more similar historical latent space vectors based on the calculated similarity (Mental process directed to identifying similar historical latent space vectors based on the calculated similarity by observing and making a judgement on the calculated similarity); and
to adjust the predicted sequence based on historical prediction outcomes associated with the identified similar historical latent space vectors (Mental process directed to observing the predicted sequence and adjusting the predicted sequence based on historical prediction outcomes associated with the identified similar historical latent space vectors).
Step 2A, Prong 2
a data preprocessor (this limitation is directed to a generic computer component to collect information. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(f)) comprising
a time window manager (this limitation is directed to generally linking the use of a judicial exception to a particular technological environment or field of use. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(h)) and
a padding generator (this limitation is directed to generally linking the use of a judicial exception to a particular technological environment or field of use. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(h)),
the data preprocessor configured (this limitation is directed to a generic computer component to collect information. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(f)) to:
receive a time series input sequence of a first length comprising a plurality of sequential data points (this limitation is directed to insignificant extra solution activity of data gathering. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(g));
an a variational autoencoder configured to (this limitation is directed to mere instruction to apply an exception. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(f))
compress the padded input sequence into a latent space representation through dimensional reduction (this limitation is directed to generally linking the use of a judicial exception to a particular technological environment or field of use. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(h)),
the latent space vector capturing temporal patterns and dependencies present in the padded input sequence (this limitation is directed to insignificant extra solution activity of data transmission. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(g));
a latent transformer configured to process the latent space vector (this limitation is directed to generally linking the use of a judicial exception to a particular technological environment or field of use. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(h)),
the latent transformer operating directly on the latent space vector without embedding layers or positional encoding layers (this limitation is directed to generally linking the use of a judicial exception to a particular technological environment or field of use. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(h));
a variational autoencoder configured (this limitation is directed to mere instruction to apply an exception. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(f)) to
wherein during training the decoder learns to reconstruct the removed terminal data points in positions corresponding to the context-aware padding values by minimizing reconstruction error between the predicted sequence and the original time series input sequence (this limitation is directed to generally linking the use of a judicial exception to a particular technological environment or field of use. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(h));
a pattern library configured to store a plurality of historical latent space vectors (this limitation is directed to storing data latent space vectors in a pattern library. This This limitation is directed to insignificant extra solution activity of data gathering. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(g)),
a pattern matching component configured (this limitation is directed to mere instruction to apply an exception. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(f)) to:
a prediction refinement component (this limitation is directed to mere instruction to apply an exception. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(f)) configured
Step 2B
a data preprocessor (this limitation is directed to a generic computer component to collect information. This limitation does not amount to significantly more than the judicial exception. See MPEP 2106.05(f)) comprising
a time window manager (this limitation is directed to generally linking the use of a judicial exception to a particular technological environment or field of use. This limitation does not amount to significantly more than the judicial exception. See MPEP 2106.05(h)) and
a padding generator (this limitation is directed to generally linking the use of a judicial exception to a particular technological environment or field of use. This limitation does not amount to significantly more than the judicial exception. See MPEP 2106.05(h)),
the data preprocessor configured (this limitation is directed to a generic computer component to collect information. This limitation does not amount to significantly more than the judicial exception. See MPEP 2106.05(f)) to:
receive a time series input sequence of a first length comprising a plurality of sequential data points (this limitation is directed insignificant extra solution activity of data gathering and it is well understood routine and conventional. This does not amount to significantly more than judicial exception. See MPEP 2106.05(d)(II), example i);
an a variational autoencoder configured to (this limitation is directed to mere instruction to apply an exception. This limitation does not amount to significantly more than the judicial exception. See MPEP 2106.05(f))
compress the padded input sequence into a latent space representation through dimensional reduction (this limitation is directed to generally linking the use of a judicial exception to a particular technological environment or field of use. This limitation does not amount to significantly more than the judicial exception. See MPEP 2106.05(h)),
the latent space vector capturing temporal patterns and dependencies present in the padded input sequence (this limitation is directed insignificant extra solution activity of data gathering and it is well understood routine and conventional. This does not amount to significantly more than judicial exception. See MPEP 2106.05(d)(II), example i);
a latent transformer configured to process the latent space vector (this limitation is directed to generally linking the use of a judicial exception to a particular technological environment or field of use. This limitation does not amount to significantly more than the judicial exception. See MPEP 2106.05(h)),
the latent transformer operating directly on the latent space vector without embedding layers or positional encoding layers (this limitation is directed to generally linking the use of a judicial exception to a particular technological environment or field of use. This limitation does not amount to significantly more than the judicial exception. See MPEP 2106.05(h));
a variational autoencoder configured (this limitation is directed to mere instruction to apply an exception. This limitation does not amount to significantly more than the judicial exception. See MPEP 2106.05(f)) to
wherein during training the decoder learns to reconstruct the removed terminal data points in positions corresponding to the context-aware padding values by minimizing reconstruction error between the predicted sequence and the original time series input sequence (this limitation is directed to generally linking the use of a judicial exception to a particular technological environment or field of use. This limitation does not amount to significantly more than the judicial exception. See MPEP 2106.05(h));
a pattern library configured to store a plurality of historical latent space vectors (this limitation is directed to storing data latent space vectors in a pattern library. This limitation is directed to insignificant extra solution activity of data gathering and it is well understood routine and conventional. This does not amount to significantly more than judicial exception. See MPEP 2106.05(d)(II), example i),
a pattern matching component configured (this limitation is directed to mere instruction to apply an exception. This limitation does not amount to significantly more than the judicial exception. See MPEP 2106.05(f)) to:
a prediction refinement component (this limitation is directed to mere instruction to apply an exception. This limitation does not amount to significantly more than the judicial exception. See MPEP 2106.05(f)) configured
7. Dependent claim 2 is directed to a system, and falls into one of the four statutory categories.
Claim 2 recites the following abstract ideas:
monitor temporal characteristics of the time series input sequence including at least one of sampling rate, periodicity, or trend strength (Mental process directed to monitoring temporal characteristics of the time series input by observation);
calculate an optimal window length based on the monitored temporal characteristics (Mathematical concepts directed to calculating the optimal window length); and
adjust the first length and the predetermined number of terminal data points based on the calculated optimal window length (Mental process directed to observing the first length and the predetermined number of terminal data points and making a judgement on when to adjust).
Claim 2 recites the following additional elements:
wherein the time window manager is further configured to (this limitation is directed to mere instruction to apply an exception. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(f)):
Claim 2 recites the following additional elements:
wherein the time window manager is further configured to (this limitation is directed to mere instruction to apply an exception. This limitation does not amount to significantly more than the judicial exception. See MPEP 2106.05(f)):
8. Dependent claim 3 is directed to a system, and falls into one of the four statutory categories.
Claim 3 do not recite any abstract ideas.
Claim 3 recites the following additional elements:
wherein the variational autodecoder is configured to (this limitation is directed to mere instruction to apply an exception. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(f))
generate predictions at multiple time horizons by reconstructing nested subsets of the removed terminal values (this limitation is directed to mere instructions to apply an exception. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(f)), and
wherein the training system applies different weights to reconstruction errors at different time horizons (this limitation is directed to mere instruction to apply a judicial
exception. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(f)).
Claim 3 recites the following additional elements:
wherein the variational autodecoder is configured to (this limitation is directed to mere instruction to apply an exception. This limitation does not amount to significantly more than the judicial exception. See MPEP 2106.05(f))
generate predictions at multiple time horizons by reconstructing nested subsets of the removed terminal values (this limitation is directed to mere instructions to apply an exception. This limitation does not amount to significantly more than the judicial exception. See MPEP 2106.05(f)), and
wherein the training system applies different weights to reconstruction errors at different time horizons (this limitation is directed to mere instruction to apply a judicial
exception. This limitation does not amount to significantly more than the judicial exception. See MPEP 2106.05(f)).
9. Dependent claim 4 is directed to a system, and falls into one of the four statutory categories.
Claim 4 recite the following abstract ideas:
calculate confidence intervals for the predicted sequence based on statistical analysis of the distribution of prediction variants (Mathematical concepts directed to calculating confidence intervals based on statistical analysis).
Claim 4 recites the following additional elements:
further comprising a confidence estimation component configured to (this limitation is directed to mere instructions to apply an exception. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(f))
execute multiple forward passes through the variational autodecoder with stochastic dropout applied to decoder neurons during each forward pass (this limitation is directed to mere instructions to apply an exception. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(f));
generate a distribution of prediction variants from the multiple forward passes (this limitation is directed to mere instructions to apply an exception. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(f)); and
Claim 4 recites the following additional elements:
further comprising a confidence estimation component configured to (this limitation is directed to mere instructions to apply an exception. This limitation does not amount to significantly more than the judicial exception. See MPEP 2106.05(f))
execute multiple forward passes through the variational autodecoder with stochastic dropout applied to decoder neurons during each forward pass (this limitation is directed to mere instructions to apply an exception. This limitation does not amount to significantly more than the judicial exception. See MPEP 2106.05(f));
generate a distribution of prediction variants from the multiple forward passes (this limitation is directed to mere instructions to apply an exception. This limitation does not amount to significantly more than the judicial exception. See MPEP 2106.05(f)); and
10. Dependent claim 5 is directed to a system, and falls into one of the four statutory categories.
Claim 5 do not recite any abstract ideas.
Claim 5 recites the following additional elements:
wherein the padding generator is further configured to: apply an attention mechanism to score relevance of the context-aware padding values to prediction accuracy (this limitation is directed to mere instructions to apply an exception. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(f)); and
iteratively refine the context-aware padding values based on the relevance scores during training of the variational autoencoder encoder and the variational autoencoder decoder (this limitation is directed to mere instructions to apply an exception. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(f)).
Claim 5 recites the following additional elements:
wherein the padding generator is further configured to: apply an attention mechanism to score relevance of the context-aware padding values to prediction accuracy (this limitation is directed to mere instructions to apply an exception. This limitation does not amount to significantly more than the judicial exception. See MPEP 2106.05(f)); and
iteratively refine the context-aware padding values based on the relevance scores during training of the variational autoencoder encoder and the variational autoencoder decoder (this limitation is directed to mere instructions to apply an exception. This limitation does not amount to significantly more than the judicial exception. See MPEP 2106.05(f)).
11. Dependent claim 6 is directed to a system, and falls into one of the four statutory categories.
Claim 6 recite the following abstract ideas:
weight adjustments to the predicted sequence based on the success rate metrics of the identified similar historical latent space vectors (Mental process directed to adjusting weight to the predicted sequence based on the success rate metrics of the identified similar historical latent space vectors by observing the predicted sequence and making a judgement on the weight adjustment).
Claim 6 recite the following additional elements:
wherein: the pattern library is further configured to maintain historical prediction outcomes for each stored historical latent space vector (this limitation is directed to storing data latent space vectors in a pattern library. This limitation is directed to insignificant extra solution activity of data gathering. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(g)) ),
each historical prediction outcome comprising a success rate metric indicating accuracy of predictions associated with the corresponding historical latent space vector (this limitation is directed to a particular type or source of data, which is field of use. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(f));
and the prediction refinement component is configured to (this limitation is directed to mere instructions to apply an exception. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(f))
Claim 6 recite the following additional elements:
wherein: the pattern library is further configured to maintain historical prediction outcomes for each stored historical latent space vector (this limitation is directed to storing data latent space vectors in a pattern library and it is well understood routine and conventional. This does not amount to significantly more than judicial exception. See MPEP 2106.05(d)(II)i),
each historical prediction outcome comprising a success rate metric indicating accuracy of predictions associated with the corresponding historical latent space vector (this limitation is directed to a particular type or source of data, which is field of use. This does not amount to significantly more than judicial exception. See MPEP 2106.05(f));
and the prediction refinement component is configured to (this limitation is directed to mere instructions to apply an exception. This does not amount to significantly more than judicial exception. See MPEP 2106.05(f))
12. Dependent claim 7 is directed to a system, and falls into one of the four statutory categories.
Claim 7 recite the following abstract ideas:
detect correlations between the time series input sequence and the plurality of related time series through sliding window analysis (Mental process directed to detect correlations between the time series input sequence and the plurality of related time series through sliding window analysis by observation and making a judgement on the correlations);
Claim 7 recites the following additional elements:
further comprising a cross-series knowledge subsystem including a transfer learning engine configured to: extract shared temporal patterns from a plurality of related time series using convolutional filters (this limitation is directed to insignificant extra solution activity of data gathering. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(g));
store the extracted shared temporal patterns in a knowledge base (this limitation is directed to insignificant extra solution activity of data gathering. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(g));
Claim 7 recites the following additional elements:
further comprising a cross-series knowledge subsystem including a transfer learning engine configured to: extract shared temporal patterns from a plurality of related time series using convolutional filters (this limitation is directed to insignificant extra solution activity of data gathering. This does not amount to significantly more than judicial exception. See MPEP 2106.05(g));
store the extracted shared temporal patterns in a knowledge base (this limitation is directed to insignificant extra solution activity of data gathering. This does not amount to significantly more than judicial exception. See MPEP 2106.05(g));
13. Dependent claim 9 is directed to a system, and falls into one of the four statutory categories.
Claim 9 do not recite any abstract ideas.
Claim 9 recites the following additional elements:
latent transformer comprises: a plurality of stacked encoder layers, each encoder layer comprising a multi-head self- attention mechanism and a feed-forward network; residual connections between the multi-head self-attention mechanism and the feed-forward network within each encoder layer; and layer normalization applied after each residual connection (This limitation is directed to generally linking the use of a judicial exception to a particular technological environment or field of use. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05(h)).
Claim 9 recites the following additional elements:
latent transformer comprises: a plurality of stacked encoder layers, each encoder layer comprising a multi-head self- attention mechanism and a feed-forward network; residual connections between the multi-head self-attention mechanism and the feed-forward network within each encoder layer; and layer normalization applied after each residual connection (This limitation is directed to generally linking the use of a judicial exception to a particular technological environment or field of use. This does not amount to significantly more than judicial exception. See MPEP 2106.05(h)).
14. Independent claim 10 is directed to a method, and falls into one of the four statutory categories.
With regards to claim 10, it is substantially similar to claim 1, and is rejected in the same manner and reasoning applying.
15. Dependent claim 11 is directed to a method, and falls into one of the four statutory categories.
With regards to claim 11, it is substantially similar to claim 2, and is rejected in the same manner and reasoning applying.
16. Dependent claim 12 is directed to a method, and falls into one of the four statutory categories.
With regards to claim 12, it is substantially similar to claim 3, and is rejected in the same manner and reasoning applying.
17. Dependent claim 13 is directed to a method, and falls into one of the four statutory categories.
With regards to claim 13, it is substantially similar to claim 4, and is rejected in the same manner and reasoning applying.
18. Dependent claim 14 is directed to a method, and falls into one of the four statutory categories.
With regards to claim 14, it is substantially similar to claim 5, and is rejected in the same manner and reasoning applying.
19. Dependent claim 15 is directed to a method, and falls into one of the four statutory categories.
With regards to claim 15, it is substantially similar to claim 6, and is rejected in the same manner and reasoning applying.
20. Dependent claim 16 is directed to a method, and falls into one of the four statutory categories.
With regards to claim 16, it is substantially similar to claim 7, and is rejected in the same manner and reasoning applying.
21. Dependent claim 17 is directed to a method, and falls into one of the four statutory categories.
Claim 17 do not recite any abstract ideas.
Claim 17 recites the following additional elements:
wherein optimizing the variational autoencoder and variational autoencoder comprises implementing multiple reconstruction objectives comprising: full sequence reconstruction; statistical property preservation; and trend direction accuracy (this limitation is directed to generally linking the use of a judicial exception to a particular technological environment or field of use. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05 (h));
wherein the multiple reconstruction objectives are weighted according to configurable importance factors (this limitation is directed to generally linking the use of a judicial exception to a particular technological environment or field of use. This limitation does not integrate the abstract idea into a practical application. See MPEP 2106.05 (h)).
Claim 17 recites the following additional elements:
wherein optimizing the variational autoencoder and variational autoencoder comprises implementing multiple reconstruction objectives comprising: full sequence reconstruction; statistical property preservation; and trend direction accuracy (this limitation is directed to generally linking the use of a judicial exception to a particular technological environment or field of use. This does not amount to significantly more than judicial exception. See MPEP 2106.05 (h));
wherein the multiple reconstruction objectives are weighted according to configurable importance factors (this limitation is directed to generally linking the use of a judicial exception to a particular technological environment or field of use. This does not amount to significantly more than judicial exception. See MPEP 2106.05 (h)).
22. Dependent claim 18 is directed to a method, and falls into one of the four statutory categories.
With regards to claim 18, it is substantially similar to claim 9, and is rejected in the same manner and reasoning applying.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
23. This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are: “a data preprocessor”, “time window manager”, “padding generator”, “pattern library”, “pattern matching component” and “prediction refinement component” in claim 1. “Time window manager” in claim 2, “confidence estimation component” in claim 4, “padding generator” in claim 5 and “pattern library”, prediction refinement component” in claim 6, “a cross-series knowledge subsystem”, “transfer learning engine” in claim 7.
Because these claim limitations are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof. Also, these limitations use generic place holders modified by functional language and the area not modified by sufficient structure.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
24. Claims 1-7 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites “pattern matching component” configured to calculate similarity between the latent space vector and the plurality of historical latent space vectors using cosine distance metrics and identify one or more similar historical latent space vectors based on the calculated similarity. The Applicant’s specification fails to disclose an algorithm for performing the claimed specific computer function and structure to perform the means-plus-function limitation. According to MPEP 2181(II)(B), “In cases involving a special purpose computer-implemented means-plus-function limitation, the Federal Circuit has consistently required that the structure be more than simply a general purpose computer or microprocessor and that the specification must disclose an algorithm for performing the claimed function”.
Claim 1 recites “prediction refinement component configured to adjust the predicted sequence based on historical prediction outcomes associated with the identified similar historical latent space vectors”. The Applicant’s specification fails to disclose an algorithm for performing the claimed specific computer function and structure to perform the means-plus-function limitation. According to MPEP 2181(II)(B), “In cases involving a special purpose computer-implemented means-plus-function limitation, the Federal Circuit has consistently required that the structure be more than simply a general purpose computer or microprocessor and that the specification must disclose an algorithm for performing the claimed function”.
Claim 2 recites “time window manager is configured to monitor temporal characteristics of the time series input sequence including at least one of sampling rate, periodicity, or trend strength”. The Applicant’s specification fails to disclose an algorithm for performing the claimed specific computer function and structure to perform the means-plus-function limitation. According to MPEP 2181(II)(B), “In cases involving a special purpose computer-implemented means-plus-function limitation, the Federal Circuit has consistently required that the structure be more than simply a general purpose computer or microprocessor and that the specification must disclose an algorithm for performing the claimed function”.
Claim 4 recites “confidence estimation component configured to execute multiple forward passes through the variational autodecoder with stochastic dropout applied to decoder neurons during each forward pass”. The Applicant’s specification fails to disclose algorithms for performing these claimed specific computer functions and structures to perform the means-plus-function limitation. According to MPEP 2181(II)(B), “In cases involving a special purpose computer-implemented means-plus-function limitation, the Federal Circuit has consistently required that the structure be more than simply a general purpose computer or microprocessor and that the specification must disclose an algorithm for performing the claimed function”.
Claim 5 recites “padding generator configured to apply an attention mechanism to score relevance of the context-aware padding values to prediction accuracy”. The Applicant’s specification fails to disclose algorithms for performing these claimed specific computer functions and structures to perform the means-plus-function limitation. According to MPEP 2181(II)(B), “In cases involving a special purpose computer-implemented means-plus-function limitation, the Federal Circuit has consistently required that the structure be more than simply a general purpose computer or microprocessor and that the specification must disclose an algorithm for performing the claimed function”.
Claim 6 recites “pattern library configured to maintain historical prediction outcomes for each stored historical latent space vector”. The Applicant’s specification fails to disclose algorithms for performing these claimed specific computer functions and structures to perform the means-plus-function limitation. According to MPEP 2181(II)(B), “In cases involving a special purpose computer-implemented means-plus-function limitation, the Federal Circuit has consistently required that the structure be more than simply a general purpose computer or microprocessor and that the specification must disclose an algorithm for performing the claimed function”.
Claim 6 recites “prediction refinement component configured to weight adjustments to the predicted sequence based on the success rate metrics of the identified similar historical latent space vectors”. The Applicant’s specification fails to disclose algorithms for performing these claimed specific computer functions and structures to perform the means-plus-function limitation. According to MPEP 2181(II)(B), “In cases involving a special purpose computer-implemented means-plus-function limitation, the Federal Circuit has consistently required that the structure be more than simply a general purpose computer or microprocessor and that the specification must disclose an algorithm for performing the claimed function”.
Claim 7 recites “cross-series knowledge subsystem including a transfer learning engine configured to: extract shared temporal patterns from a plurality of related time series using convolutional filters; store the extracted shared temporal patterns in a knowledge base; detect correlations between the time series input sequence and the plurality of related time series through sliding window analysis; and apply the extracted shared temporal patterns to the predicted sequence based on the detected correlations ...”. The Applicant’s specification fails to disclose algorithms for performing these claimed specific computer functions and structures to perform the means-plus-function limitation. According to MPEP 2181(II)(B), “In cases involving a special purpose computer-implemented means-plus-function limitation, the Federal Circuit has consistently required that the structure be more than simply a general purpose computer or microprocessor and that the specification must disclose an algorithm for performing the claimed function”.
Claim 3 that is not specifically mentioned are rejected due to dependency.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
25. Claims 4 is rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 4 recites “confidence estimation subsystem configured to execute multiple forward passes through the variational autodecoder with stochastic dropout applied to decoder neurons during each forward pass”.
The specific limitation of “stochastic dropout applied to decoder neurons during each forward pass” does not have basis in the original disclosure. This is because the instant specification stated using an optimization algorithm such as “stochastic gradient descent” in [0197] and [0319] during model training. Applicant’s specification [0197] and [0319] also mentions that during training that the loss function which the model might use could be dropout rate in the neural network. The claimed limitation “confidence estimation subsystem configured to execute multiple forward passes through the variational autodecoder with stochastic dropout applied to decoder neurons during each forward pass” is different from what is described in [0197] and [0319] of the instant specification.
As a result, the specification does not provide written description support for “confidence estimation subsystem configured to execute multiple forward passes through the variational autodecoder with stochastic dropout applied to decoder neurons during each forward pass”.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MORIAM MOSUNMOLA GODO whose telephone number is (571)272-8670. The examiner can normally be reached Monday-Friday 8:00am-5:00pm EST.
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/M.G./Examiner, Art Unit 2148
/MOHAMED ABOU EL SEOUD/ Primary Examiner, Art Unit 2148
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