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 .
This final action is in response to the applicant’s communication received on 1/26/2026 (“Amendment”).
Claims 1 and 11, independent claims, have been amended. Claim 20 are withdrawn. Clams 1-20 are pending.
Claim Objection
Per MPEP 714 IIC, “Each amendment document that includes a change to an existing claim, including the deletion of an existing claim, or submission of a new claim, must include a complete listing of all claims ever presented (including previously canceled and non-entered claims) in the application. After each claim number, the status identifier of the claim must be presented in a parenthetical expression, and the text of each claim under examination as well as all withdrawn claims (each with markings if any, to show current changes) must be presented.”
In the instant claim(s), claim 20 which was withdrawn does not include text that were originally presented.
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.
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 limitation(s) is/are:
a Federated Learning Information Server (FLIS) … configured to aggregate, analyze, and disseminate optimized computational strategies across the blockchain network (claim 1);
an incentive mechanism configured to reward nodes that develop and share efficient computational strategies that are adopted by other nodes within the blockchain network (claim 1);
a dynamic strategy adoption module configured within each node to automatically select and apply the most efficient computational strategy shared by the FLIS based on current network conditions, hardware capabilities of the node, and predefined criteria for optimizing block generation and transaction validation processes (claim 1);
an auto-approval mechanism for validators in the POS system, wherein the mechanism is configured to automatically approve transactions using an optimal strategy selected from the strategies published by the FLIS in scenarios where a validator is temporarily unavailable, ensuring uninterrupted transaction validation within the blockchain network (claim 1);
a privacy-preserving mechanism that ensures sensitive transaction data remains within the node and only anonymized performance metrics and strategy parameters are shared with the FLIS for strategy optimization (claim 2);
a continuous learning module configured to adaptively refine the node's computational strategy based on feedback received from the FLIS regarding the performance of shared strategies across the blockchain network (claim 2);
the FLIS utilizes machine learning algorithms to identify patterns in aggregated strategy data from nodes, enabling the identification of universally efficient strategies that contribute to significant improvements in TPS and carbon efficiency across the blockchain network (claim 3);
a gas compensation model that allocates rewards of cryptocurrency or transaction amount discounts to nodes contributing strategies that lead to measurable improvements in network performance and environmental sustainability (claim 4);
the dynamic strategy adoption module is further configured to periodically review and update a selected computational strategy based on real-time analysis of network performance data and emerging computational strategies identified by the FLIS, ensuring that each node consistently operates using the most effective and resource-efficient strategy available (claim 5);
an optimization feedback loop within the dynamic strategy adoption module, configured to automatically report performance outcomes of the adopted computational strategies back to the LFLM, wherein the feedback loop enhances precision of future strategy selections by incorporating real-world performance data into the LFLM's strategy refinement process (claim 6);
the auto-approval mechanism for validators is further enhanced by: a priority transaction identification feature, configured to recognize high-priority transactions based on predefined criteria and ensure their expedited validation by applying the most efficient computational strategy available, thereby optimizing the blockchain network's responsiveness to time-sensitive transactions (claim 7);
a cryptographic strategy validation mechanism, configured to authenticate origin and integrity of shared computational strategies, ensuring that only verified and secure strategies are disseminated and adopted across the blockchain network, thereby maintaining network security posture while facilitating decentralized learning (claim 8);
a network condition monitoring module within the FLIS, configured to continuously assess a current state of the blockchain network, including transaction volume, block generation time, and overall network congestion, and dynamically adjust the dissemination of computational strategies to prioritize those most effective under prevailing network conditions (claim 1);
the incentive mechanism is further configured to: implement a tiered reward structure that variably compensates nodes based on an impact level of their contributed computational strategies on the blockchain network's efficiency and carbon footprint, thereby incentivizing the development and sharing of groundbreaking strategies that offer the highest benefits in terms of TPS improvement and energy consumption reduction (claim 10);
FLIS is responsible for aggregating, analyzing, and disseminating optimized computational strategies across the blockchain network to reduce computational resource requirements for block generation and transaction validation (claim 11);
an incentive mechanism to reward nodes that develop and disseminate efficient computational strategies adopted by other nodes within the blockchain network (claim 11);
automatically selecting and applying the most efficient computational strategy at each node from those disseminated by the FLIS, based on current network conditions, hardware capabilities of the node, and predefined criteria for optimizing block generation and transaction validation processes, through a dynamic strategy adoption module configured within each node (claim 11);
an auto-approval mechanism for validators in the POS system to automatically approve transactions using an optimal strategy selected from those published by the FLIS in scenarios where a validator is temporarily unavailable, ensuring uninterrupted transaction validation within the blockchain network (claim 11);
a privacy-preserving mechanism to ensure that sensitive transaction data remains within the node, and only anonymized performance metrics and strategy parameters are shared with the FLIS for the purpose of strategy optimization (claim 11);
dynamic strategy adoption module to periodically review and update the selected computational strategy based on real-time analysis of network performance data and emerging computational strategies identified by the FLIS, ensuring that each node consistently operates using the most effective and resource-efficient strategy available (claim 11);
the feedback loop is configured to enhance the precision of future strategy selections by incorporating real-world performance data into a strategy refinement process (claim 12);
recognizing high-priority transactions through a priority transaction identification feature within the auto-approval mechanism, configured to expedite the validation of these transactions by applying the most efficient computational strategy available, optimizing the blockchain network's responsiveness to time-sensitive transactions (claim 13);
authenticating the origin and integrity of shared computational strategies using a cryptographic strategy validation mechanism within the strategy sharing protocol, ensuring that only verified and secure strategies are disseminated and adopted across the blockchain network, thereby maintaining the network's security posture (claim 14);
continuously assessing the current state of the blockchain network, including transaction volume, block generation time, and overall network congestion, through a network condition monitoring module within the FLIS, and dynamically adjusting the dissemination of computational strategies to prioritize those most effective under the prevailing network conditions (claim 15);
a tiered reward structure within the incentive mechanism, designed to variably compensate nodes based on the impact level of their contributed computational strategies on the blockchain network's efficiency and carbon footprint, incentivizing the development and sharing of groundbreaking strategies that offer the highest benefits in terms of TPS improvement and energy consumption reduction (claim 16);
a decentralized strategy update mechanism that allows nodes to directly exchange updates on computational strategies without relying on the FLIS, enhancing network ability to rapidly adapt to changes and innovations in computational strategies and further decentralizing a learning process (claim 17);
nodes work together to identify and mitigate potential security threats or inefficiencies in computational strategies, leveraging collective intelligence of the blockchain network to enhance security and efficiency through Federated Learning (claim 19).
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
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 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.
Claims 1-19 are 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 limitations:
a Federated Learning Information Server (FLIS) … configured to aggregate, analyze, and disseminate optimized computational strategies across the blockchain network (claim 1);
an incentive mechanism configured to reward nodes that develop and share efficient computational strategies that are adopted by other nodes within the blockchain network (claim 1);
a dynamic strategy adoption module configured within each node to automatically select and apply the most efficient computational strategy shared by the FLIS based on current network conditions, hardware capabilities of the node, and predefined criteria for optimizing block generation and transaction validation processes (claim 1);
an auto-approval mechanism for validators in the POS system, wherein the mechanism is configured to automatically approve transactions using an optimal strategy selected from the strategies published by the FLIS in scenarios where a validator is temporarily unavailable, ensuring uninterrupted transaction validation within the blockchain network (claim 1);
a privacy-preserving mechanism that ensures sensitive transaction data remains within the node and only anonymized performance metrics and strategy parameters are shared with the FLIS for strategy optimization (claim 2);
a continuous learning module configured to adaptively refine the node's computational strategy based on feedback received from the FLIS regarding the performance of shared strategies across the blockchain network (claim 2);
the FLIS utilizes machine learning algorithms to identify patterns in aggregated strategy data from nodes, enabling the identification of universally efficient strategies that contribute to significant improvements in TPS and carbon efficiency across the blockchain network (claim 3);
a gas compensation model that allocates rewards of cryptocurrency or transaction amount discounts to nodes contributing strategies that lead to measurable improvements in network performance and environmental sustainability (claim 4);
the dynamic strategy adoption module is further configured to periodically review and update a selected computational strategy based on real-time analysis of network performance data and emerging computational strategies identified by the FLIS, ensuring that each node consistently operates using the most effective and resource-efficient strategy available (claim 5);
an optimization feedback loop within the dynamic strategy adoption module, configured to automatically report performance outcomes of the adopted computational strategies back to the LFLM, wherein the feedback loop enhances precision of future strategy selections by incorporating real-world performance data into the LFLM's strategy refinement process (claim 6);
the auto-approval mechanism for validators is further enhanced by: a priority transaction identification feature, configured to recognize high-priority transactions based on predefined criteria and ensure their expedited validation by applying the most efficient computational strategy available, thereby optimizing the blockchain network's responsiveness to time-sensitive transactions (claim 7);
a cryptographic strategy validation mechanism, configured to authenticate origin and integrity of shared computational strategies, ensuring that only verified and secure strategies are disseminated and adopted across the blockchain network, thereby maintaining network security posture while facilitating decentralized learning (claim 8);
a network condition monitoring module within the FLIS, configured to continuously assess a current state of the blockchain network, including transaction volume, block generation time, and overall network congestion, and dynamically adjust the dissemination of computational strategies to prioritize those most effective under prevailing network conditions (claim 1);
the incentive mechanism is further configured to: implement a tiered reward structure that variably compensates nodes based on an impact level of their contributed computational strategies on the blockchain network's efficiency and carbon footprint, thereby incentivizing the development and sharing of groundbreaking strategies that offer the highest benefits in terms of TPS improvement and energy consumption reduction (claim 10);
FLIS is responsible for aggregating, analyzing, and disseminating optimized computational strategies across the blockchain network to reduce computational resource requirements for block generation and transaction validation (claim 11);
an incentive mechanism to reward nodes that develop and disseminate efficient computational strategies adopted by other nodes within the blockchain network (claim 11);
automatically selecting and applying the most efficient computational strategy at each node from those disseminated by the FLIS, based on current network conditions, hardware capabilities of the node, and predefined criteria for optimizing block generation and transaction validation processes, through a dynamic strategy adoption module configured within each node (claim 11);
an auto-approval mechanism for validators in the POS system to automatically approve transactions using an optimal strategy selected from those published by the FLIS in scenarios where a validator is temporarily unavailable, ensuring uninterrupted transaction validation within the blockchain network (claim 11);
a privacy-preserving mechanism to ensure that sensitive transaction data remains within the node, and only anonymized performance metrics and strategy parameters are shared with the FLIS for the purpose of strategy optimization (claim 11);
dynamic strategy adoption module to periodically review and update the selected computational strategy based on real-time analysis of network performance data and emerging computational strategies identified by the FLIS, ensuring that each node consistently operates using the most effective and resource-efficient strategy available (claim 11);
the feedback loop is configured to enhance the precision of future strategy selections by incorporating real-world performance data into a strategy refinement process (claim 12);
recognizing high-priority transactions through a priority transaction identification feature within the auto-approval mechanism, configured to expedite the validation of these transactions by applying the most efficient computational strategy available, optimizing the blockchain network's responsiveness to time-sensitive transactions (claim 13);
authenticating the origin and integrity of shared computational strategies using a cryptographic strategy validation mechanism within the strategy sharing protocol, ensuring that only verified and secure strategies are disseminated and adopted across the blockchain network, thereby maintaining the network's security posture (claim 14);
continuously assessing the current state of the blockchain network, including transaction volume, block generation time, and overall network congestion, through a network condition monitoring module within the FLIS, and dynamically adjusting the dissemination of computational strategies to prioritize those most effective under the prevailing network conditions (claim 15);
a tiered reward structure within the incentive mechanism, designed to variably compensate nodes based on the impact level of their contributed computational strategies on the blockchain network's efficiency and carbon footprint, incentivizing the development and sharing of groundbreaking strategies that offer the highest benefits in terms of TPS improvement and energy consumption reduction (claim 16);
a decentralized strategy update mechanism that allows nodes to directly exchange updates on computational strategies without relying on the FLIS, enhancing network ability to rapidly adapt to changes and innovations in computational strategies and further decentralizing a learning process (claim 17);
nodes work together to identify and mitigate potential security threats or inefficiencies in computational strategies, leveraging collective intelligence of the blockchain network to enhance security and efficiency through Federated Learning (claim 19);
invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The claims are rejected as the claims are found to be indefinite under 35 U.S.C. 112(b) for failure to disclose sufficient corresponding structure (e.g. the computer and the algorithm) in the specification that performs the claimed functions. See January 2019 Federal Register notice on Examining Computer-Implemented Functional Claim Limitations for Compliance with 35 U.S.C. 112 that states, "When a claim containing a computer-implemented 35 U.S.C. 112(f) claim limitation is found to be indefinite under 35 U.S.C. 112(b) for failure to disclose sufficient corresponding structure (e.g., the computer and the algorithm) in the specification that performs the entire claimed function, it will also lack written description under 35 U.S.C. 112(a). See also MPEP § 2163.03, subsection VI.
The dependent claims are rejected as they depend on claim(s) above.
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.
Claims 1-19 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 limitations:
a Federated Learning Information Server (FLIS) … configured to aggregate, analyze, and disseminate optimized computational strategies across the blockchain network (claim 1);
an incentive mechanism configured to reward nodes that develop and share efficient computational strategies that are adopted by other nodes within the blockchain network (claim 1);
a dynamic strategy adoption module configured within each node to automatically select and apply the most efficient computational strategy shared by the FLIS based on current network conditions, hardware capabilities of the node, and predefined criteria for optimizing block generation and transaction validation processes (claim 1);
an auto-approval mechanism for validators in the POS system, wherein the mechanism is configured to automatically approve transactions using an optimal strategy selected from the strategies published by the FLIS in scenarios where a validator is temporarily unavailable, ensuring uninterrupted transaction validation within the blockchain network (claim 1);
a privacy-preserving mechanism that ensures sensitive transaction data remains within the node and only anonymized performance metrics and strategy parameters are shared with the FLIS for strategy optimization (claim 2);
a continuous learning module configured to adaptively refine the node's computational strategy based on feedback received from the FLIS regarding the performance of shared strategies across the blockchain network (claim 2);
the FLIS utilizes machine learning algorithms to identify patterns in aggregated strategy data from nodes, enabling the identification of universally efficient strategies that contribute to significant improvements in TPS and carbon efficiency across the blockchain network (claim 3);
a gas compensation model that allocates rewards of cryptocurrency or transaction amount discounts to nodes contributing strategies that lead to measurable improvements in network performance and environmental sustainability (claim 4);
the dynamic strategy adoption module is further configured to periodically review and update a selected computational strategy based on real-time analysis of network performance data and emerging computational strategies identified by the FLIS, ensuring that each node consistently operates using the most effective and resource-efficient strategy available (claim 5);
an optimization feedback loop within the dynamic strategy adoption module, configured to automatically report performance outcomes of the adopted computational strategies back to the LFLM, wherein the feedback loop enhances precision of future strategy selections by incorporating real-world performance data into the LFLM's strategy refinement process (claim 6);
the auto-approval mechanism for validators is further enhanced by: a priority transaction identification feature, configured to recognize high-priority transactions based on predefined criteria and ensure their expedited validation by applying the most efficient computational strategy available, thereby optimizing the blockchain network's responsiveness to time-sensitive transactions (claim 7);
a cryptographic strategy validation mechanism, configured to authenticate origin and integrity of shared computational strategies, ensuring that only verified and secure strategies are disseminated and adopted across the blockchain network, thereby maintaining network security posture while facilitating decentralized learning (claim 8);
a network condition monitoring module within the FLIS, configured to continuously assess a current state of the blockchain network, including transaction volume, block generation time, and overall network congestion, and dynamically adjust the dissemination of computational strategies to prioritize those most effective under prevailing network conditions (claim 1);
the incentive mechanism is further configured to: implement a tiered reward structure that variably compensates nodes based on an impact level of their contributed computational strategies on the blockchain network's efficiency and carbon footprint, thereby incentivizing the development and sharing of groundbreaking strategies that offer the highest benefits in terms of TPS improvement and energy consumption reduction (claim 10);
FLIS is responsible for aggregating, analyzing, and disseminating optimized computational strategies across the blockchain network to reduce computational resource requirements for block generation and transaction validation (claim 11);
an incentive mechanism to reward nodes that develop and disseminate efficient computational strategies adopted by other nodes within the blockchain network (claim 11);
automatically selecting and applying the most efficient computational strategy at each node from those disseminated by the FLIS, based on current network conditions, hardware capabilities of the node, and predefined criteria for optimizing block generation and transaction validation processes, through a dynamic strategy adoption module configured within each node (claim 11);
an auto-approval mechanism for validators in the POS system to automatically approve transactions using an optimal strategy selected from those published by the FLIS in scenarios where a validator is temporarily unavailable, ensuring uninterrupted transaction validation within the blockchain network (claim 11);
a privacy-preserving mechanism to ensure that sensitive transaction data remains within the node, and only anonymized performance metrics and strategy parameters are shared with the FLIS for the purpose of strategy optimization (claim 11);
dynamic strategy adoption module to periodically review and update the selected computational strategy based on real-time analysis of network performance data and emerging computational strategies identified by the FLIS, ensuring that each node consistently operates using the most effective and resource-efficient strategy available (claim 11);
the feedback loop is configured to enhance the precision of future strategy selections by incorporating real-world performance data into a strategy refinement process (claim 12);
recognizing high-priority transactions through a priority transaction identification feature within the auto-approval mechanism, configured to expedite the validation of these transactions by applying the most efficient computational strategy available, optimizing the blockchain network's responsiveness to time-sensitive transactions (claim 13);
authenticating the origin and integrity of shared computational strategies using a cryptographic strategy validation mechanism within the strategy sharing protocol, ensuring that only verified and secure strategies are disseminated and adopted across the blockchain network, thereby maintaining the network's security posture (claim 14);
continuously assessing the current state of the blockchain network, including transaction volume, block generation time, and overall network congestion, through a network condition monitoring module within the FLIS, and dynamically adjusting the dissemination of computational strategies to prioritize those most effective under the prevailing network conditions (claim 15);
a tiered reward structure within the incentive mechanism, designed to variably compensate nodes based on the impact level of their contributed computational strategies on the blockchain network's efficiency and carbon footprint, incentivizing the development and sharing of groundbreaking strategies that offer the highest benefits in terms of TPS improvement and energy consumption reduction (claim 16);
a decentralized strategy update mechanism that allows nodes to directly exchange updates on computational strategies without relying on the FLIS, enhancing network ability to rapidly adapt to changes and innovations in computational strategies and further decentralizing a learning process (claim 17);
nodes work together to identify and mitigate potential security threats or inefficiencies in computational strategies, leveraging collective intelligence of the blockchain network to enhance security and efficiency through Federated Learning (claim 19).
invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. The specification discloses in terms of blocks and their functional description (see Fig. 1-2 and 6). Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
The dependent claims are rejected as they depend on claim(s) above.
Response to Argument(s)
The applicant amends the claim 1 and claim 11 to explicitly recite that the system and method are “computer-implemented” using “one or more processors and memory storing instructions” and asserts that such amendment provides “the necessary computer structure for the functional limitations previously interpreted under 112(f).
In response, the examiner would like to point out that claim 1 has been amended to recite that the plurality of nodes each includes one or more processors and memory storing instructions, when executed by the one or more processors, cause the plurality of nodes to participate in a blockchain network. Claim 11 does not recite one or more processors and memory storing instructions, rather the preamble has been amended to recite “computer-implemented method”.
Furthermore, the claim amendment in claim 1 is only limiting the “plurality of nodes” as being modified by sufficient structures. The other claimed expression(s), i.e., detailed above in the claim interpretation section” are not modified by sufficient structures. In other word, the claimed limitations as noted above in the claim interpretation section meet the following three-prong test: i.e., (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.
In response to the applicant’s remark pertaining to assertion that the claim amendment(s) “avoids undue experimentation”, the applicant is reminded that the “undue experimentation” was not the basis of the 112(a) rejection. Rather, the basis of the rejection is that the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. The specification discloses in terms of blocks and their functional description (see Fig. 1-2 and 6).
The applicant presents similar arguments in the 112(b), arguments that have been addressed above.
For these reasons, the rejection(s) are maintained.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
“BAFL: A Blockchain-Based Asynchronous Federated Learning Framework” disclose a federated learning machine learning that protects data privacy through collaborative learning of AI models across a large number of devices in a distributed fashion. The disclosure ensures that the model data cannot be tampered with while asynchronous learning speeds up global aggregation. The reference discloses a method that is used to evaluate the participant rank and proportion of the local model trained on the devices and provides a method of optimizing the block generation rate. The publication, however, is silent to at least the object of the machine learning model (i.e., strategies aimed at reducing computational resources required for block generation and transaction validation); an incentive mechanism configured to reward nodes that develop and share efficient computational strategies …; auto-approval mechanism that is configured to automatically approve transactions using an optimal strategy …
US Patent Publication No. 2022/0245528 discloses a systems and methods for federated learning using peer-to-peer networks, i.e., blockchain. Each participating nodes are equipped with a local model. A node is elected as a collaborator node using a consensus algorithm. This collaborator node generates and broadcasts public/private key pair while other participating nodes also generate their public/private key pair that is used for each communication with the collaboration node. This technique allows the participating node to encrypt and broadcast a message comprising a parameter for a local machine learning model for the participant node and allow the collaborator to receive the message and update an aggregated machine learning model with the parameter. This update from the aggregated machine leaning model is then broadcasted to the participant nodes so that the participant nodes can update their local machine learning models with the update. The publication, however, is silent to the object of the machine learning model (i.e., strategies aimed at reducing computational resources required for block generation and transaction validation); an incentive mechanism configured to reward nodes that develop and share efficient computational strategies …; auto-approval mechanism that is configured to automatically approve transactions using an optimal strategy …
US Patent Publication No. 2025/0247227 discloses a blockchain-base AI system. Nodes within the blockchain network are trained using local data which are transmitted to the blockchain node application to detect anomalous code segment updates and anomalous blockchain activity. The disclosure discloses federated learning that allows a model to be collaboratively trained across multiple decentralized edge device. The disclosure discloses privacy compliance as well as incentive reward structure for encouraging data contributors, developers, and other participants to contribute to the AI system’s improvement. The disclosure, however, is silent to at least the object of the machine learning model (i.e., strategies aimed at reducing computational resources required for block generation and transaction validation); auto-approval mechanism that is configured to automatically approve transactions using an optimal strategy …; a dynamic strategy adoption module configured within each node to automatically select and apply the most efficient computational strategy shared by the FLIS based on current network conditions, hardware capabilities of the node, and predefined criteria for optimizing block generation and transaction validation processes.
“A Blockchained Incentive Architecture for Federated Learning” discloses a federated learning framework in which each distributed client trains local model on the local database, and then sends the local model gradient to the central coordinator for global model optimization. This allows the client to contribute in the global model optimization without revealing the local raw data to any other participants. The disclosure, however, is silent to at least the object of the machine learning model (i.e., strategies aimed at reducing computational resources required for block generation and transaction validation); auto-approval mechanism that is configured to automatically approve transactions using an optimal strategy …
The cited reference, alone or in combination, does not teach the particulars of claim 1. The other independent claim, claim 11, is significantly similar but narrower in scope of claim 1. As such, the cited reference does not teach claim 11.
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/STEVEN S KIM/Primary Examiner, Art Unit 3698