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 .
DETAILED ACTION
2. This action is in response to the Request for Continued Examination and Amendment filed March 31, 2026.
3. Claims 21, 26, 31, and 36 have been amended.
4. Claims 21-40 have been examined and are pending with this action.
Response to Arguments
5. Applicant's arguments filed March 31, 2026 with respect to the rejection of claims 21-40 have been fully considered but are moot because the arguments do not apply to any of the references being used in the current rejection.
After further searching and consideration, Cummings (US 2021/0264520 A1), herein referenced Cummings, teaches the steps of independent claims 21, 26, 31, and 36, as newly amended and dependent claims 27, 29-30, 32, 34-35, 37, and 39-40.
Rouhani et al. (US 2021/0019605 A1), herein referenced Rouhani, has been cited to teach the missing limitations of dependent claims 23, 28, 33, and 38, primarily with respect to ensuring data watermarking as claimed.
For the reasons above and the rejections set forth below, claims 21-40 have been rejected and remain pending.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
6. Claims 21-22, 24-27, 29-32, 34-37, and 39-40-40 are rejected under 35 U.S.C. 102(a)(1) and 102(a)(2) as being anticipated by Cummings (US 2021/0264520 A1).
INDEPENDENT:
As per claim 21, Cummings teaches a first user device, comprising:
first circuitry configured to execute a first artificial intelligence topology partition defining an operational role within a distributed artificial intelligence topology (see Cummings, [0061]: “The client device may include one or more applications, processors, displays, input devices, and network interfaces. The applications may be configured to perform the various functions and methods discussed herein. The processors (e.g., central processing units, graphics processing units, neural processing units, etc.) may locally execute applications and render display images, or they may facilitate remote execution and rendering of applications and display images.”; [0076]: “In various embodiments, individual AI suggestions may be visible or invisible to a user depending upon the expansion state of the underlying portfolio hierarchy. For example, when the top-level node of the portfolio hierarchy is fully contracted, no AI suggestions may be visible to the user.”; [0077]: “In various embodiments, individual AI suggestions may be accessible or inaccessible to a user depending upon the user's role and associated privileges. For example, a user with the role of financial advisor (and the associated privileges to access all AI suggestions for optimizing the portfolios of the financial clients whom they serve) may access both the approved and rejected AI suggestions contained within an AI view overlaid on a financial client's portfolio presented on the client display of the financial advisor's client device. In contrast, another user with the role of financial client (and the associated privileges to access only approved AI suggestions for optimizing their portfolio) may access only the approved AI suggestions within an AI view overlaid on their portfolio presented on the client display of their client device.”; [0083]: “More specifically, at block 606, the hierarchical portfolio, or portions thereof, may be enriched by portfolio enrichment service 206, relevant user data (e.g., user profile, investment objectives, income estimates, liabilities, expenses, etc.) and global financial data (e.g., market data, economic data, policy statements, analyst research, forecasts, reports, etc.) may be compiled into a data input package by portfolio suggestion service 208, and the contents of the data input package may be submitted to one or more machine learning (ML) models, such as a trained multilayer neural network model 1500, running on one or more local or remote machine learning servers”; [0199]: “It is to be noted that because portfolios 300 and 1206 originated from the same genesis portfolio, they represent different revisions of the same hierarchical portfolio within a lineage of descendent revised portfolios; therefore, they share the same portfolio identifier (e.g., the hash of the genesis portfolio). Next, with the unique portfolioID of the hierarchical portfolio of interest determined, investment system 102 may utilize the portfolioID to lookup, via the key rack, the contract address that stores the RecordViews smart contract responsible for autonomously managing the storage and retrieval of AI views associated with the hierarchical portfolio identified by portfolioID.”; and [0330]: “For example, based on training data collected by or accessible to intelligent investment system 102 or a group of federated investment systems (i.e., linked systems that share data assets, such as user data or global financial data), a multilayer neural network model may learn”); and
the first circuitry being configured to carry out the operational role by selectively applying personal data stored locally at the first user device to population-ready generated output received from a remote artificial intelligence topology partition associated with a second user device, wherein the personal data remains stored locally at the first user device and is not transmitted to the remote artificial intelligence topology partition (see Cummings, Abstract: “The method may further comprise generating, based on the output of a neural network machine learning model, artificial intelligence suggestions for changing the hierarchical portfolio, assembling the AI suggestions and suggestion locations into an actionable artificial intelligence view of the hierarchical portfolio, and transmitting the AI view to the client device.”; [0046]: “The portfolio suggestion service 208, in an embodiment, compiles a data input package suitable for processing by machine learning algorithms (e.g., machine learning algorithms 136) running as trained machine learning models on one or more machine learning servers (e.g., machine learning servers 128). The data input package may contain, but is not limited to, relevant user data (e.g., user profile, financial goals, investment objectives, income estimates, life events, liabilities, expenses, etc.) associated with the user submitting the request for financial advice, as well as global financial data (e.g., market data, news and events, sentiment, forecasts, policy statements, macroeconomic data, industry reports, microeconomic data, corporate filings, analyst research, etc.) typically unrelated to the user.”; [0048]: “The portfolio view service 212, in an embodiment, assembles an artificial intelligence view (AI view) for overlay upon a hierarchical portfolio (e.g., a hierarchical portfolio contained or referenced in a request submitted by a user of investment system 102) by combining AI suggestions (e.g., AI suggestions from portfolio suggestion service 208) and location data (e.g., location data from portfolio mapping service 210). Within the assembled AI view (i.e., overlay layer), individual AI suggestions are organized by positions (i.e., locations) corresponding to the portfolio items to which they refer. This organizational process enables AI suggestions to be received, viewed, and understood by users in the context of the underlying hierarchical portfolio. For example, within an AI view overlaid upon a hierarchical portfolio displayed on a client device (e.g., client devices 106 or 108 or third-party systems 110), a first AI suggestion may be positioned, using location data from a mapping service (e.g., portfolio mapping service 210), near a first portfolio item to which it refers or a first portfolio item attribute to which it refers.”; [0110]: “providing AI views via an intelligent investment system (e.g., intelligent investment system 102), an important advantage associated with the key capability of the present technology to provide an AI view of a hierarchical portfolio is the ability for the financial firm to drive higher engagement levels with the individual and institutional financial clients that it serves by providing automated personalized context-specific financial advice based on various planned reviews or random events, such as periodic portfolio reviews (e.g., weekly reviews, monthly reviews, quarterly reviews, etc.), corporate events (e.g., earnings events, management events, merger or acquisition events, etc.), and global events (e.g., microeconomic events, geopolitical events, macroeconomic events, etc.).”; [0181]: “Anyone (e.g., users, validators, miners) may join, transactions are visible to all participants, and participant identity is typically masked.”; [0193]: “Upon the declaration of a function, in addition to setting visibility (e.g., public, external, internal, private) and access (e.g., view, pure) attributes, a function modifier may be applied to conditionally alter the execution flow of the function itself. For example, a function modifier may be constructed named onlyOwner that specifies particular condition under which a function is permitted to execute, such as when the sender of the calling message is equal to the owner of the contract.”; [0330]: “For example, based on training data collected by or accessible to intelligent investment system 102 or a group of federated investment systems (i.e., linked systems that share data assets, such as user data or global financial data), a multilayer neural network model may learn”; and [0337]: “where MU is the total number of users within the set of users, which may comprise any number (e.g., thousands, millions, tens of millions, hundreds of millions, etc.) of users managed within intelligent investment system 102 or across a group of federated investment systems.”).
As per claim 26, Cummings teaches a user device within an artificial intelligence infrastructure, the user device comprising:
first circuitry configured to carry out defined operations corresponding to a local topology partition of an artificial intelligence based topology (see Claim 21 rejection above); and
the first circuitry being configured to select at least one node of the artificial intelligence based topology from a plurality of personalized nodes associated with a respective third parties based on the personal data locally at the user device, wherein the personal data is not transmitted to the selected node (see Claim 21 rejection above).
As per claim 31, Cummings teaches a user device, comprising:
processing circuitry configured to receive generated output from a remote artificial intelligence node (see Cummings, [0067]: “generating AI suggestions for optimizing the relevant structure or content of the hierarchical portfolio 508”; [0068]: “The hierarchical portfolio may be from a portfolio stored on the client device or accessed remotely by the client device. For example, an application (e.g., web client application 112) may be run on a client device (e.g., client device 106) that provides access to a hierarchical portfolio by prompting the user to open a file (e.g., a local or remote document), click on a hyperlink (e.g., a link to a local or remote resource), or launch a service (e.g., portfolio management service 202).”; [0238]: “At block 1304, in an embodiment, intelligent investment system 102 may further update the AI view with the results of confirmed transactions”; [0245]: “For example, after updating the AI view to include a) indications of accepted suggestions, b) results from confirmed transactions, and c) off-chain or on-chain references to snapshots of the states of the prior hierarchical portfolio and the revised hierarchical portfolio”; and Claim 21 rejection above);
memory circuitry configured to store personal data (see Cummings, [0040]: “The data exchanged between client applications (e.g., client applications 112, 114, and 116) and intelligent investment system 102 and stored within various data sources (e.g., data sources 134, 136, and 138) may include, but are not limited to, global financial data, user data, portfolio data, or financial advice… User data may include, but are not limited to, user profile, financial goals, investment objectives and preferences, time horizon, risk tolerance, income estimates, inheritance, financial statements and accounts, life events, risks, or liability and expenses.”; [0068]: “The hierarchical portfolio may be from a portfolio stored on the client device or accessed remotely by the client device.”; and Claim 21 rejection above); and
the processing circuitry being configured to selectively apply at least a portion of the personal data locally at the user device within a secure local topology partition to personalize the generated output after generation by the remote artificial intelligence node without transmitting the personal data to the remote artificial intelligence node (see Cummings, [0181]: “In these public blockchains, participation is not limited. Anyone (e.g., users, validators, miners) may join, transactions are visible to all participants, and participant identity is typically masked.”; and Claim 21 rejection above).
As per claim 36, Cummings teaches a user device, comprising:
processing circuitry configured to receive generated image output from a remote artificial intelligence node, the generated image output being personalizable (see Claim 21 and Claim 31 rejections above);
memory circuitry configured to store personal image data (see Claim 21 and Claim 31 rejections above); and
the processing circuitry being configured to selectively apply at least a portion of the personal image data locally at the user device within a secure local topology partition to personalize the generated output without transmitting the personal image data to the remote artificial intelligence node (see Claim 21 and Claim 31 rejections above).
DEPENDENT:
As per claims 22, 27, 32 and 37, which respectively depend on claims 21, 26, 31, and 36, Cummings further teaches wherein: the first user device is operable to allow recipients to personalize shared content (see Cummings, [0098]: “The answers to these questions, in the form of attributes and attribute values associated with the AI view and AI suggestions contained within the AI view, are specifically designed to help the one or more users of the AI view, including the financial client and financial advisors to the financial client as well as other employees authorized to review the AI view, to a) develop a better understanding of the opportunities for optimizing the structure or content of the hierarchical portfolio, b) encourage collaboration and discussion among users to share their knowledge or concerns about these opportunities including any potential risks associated therewith, and… ”; [0100]: “an important advantage associated with the key capability of the present technology to provide an AI view of a hierarchical portfolio is the ability for the financial firm to drive higher engagement levels with the individual and institutional financial clients that it serves by providing automated personalized context-specific financial advice based on various planned reviews or random events, such as periodic portfolio reviews (e.g., weekly reviews, monthly reviews, quarterly reviews, etc.), corporate events (e.g., earnings events, management events, merger or acquisition events, etc.), and global events (e.g., microeconomic events, geopolitical events, macroeconomic events, etc.).”; and [0330]: “For example, based on training data collected by or accessible to intelligent investment system 102 or a group of federated investment systems (i.e., linked systems that share data assets, such as user data or global financial data), a multilayer neural network model may learn a set of near-optimal parameters values for a collection”).
As per claims 24, 29, 34, and 39, which respectively depend on claims 21, 26, 31, and 36, Cummings further teaches wherein: the first user device is operable to support secure output personalization (see Cummings, [0007]: “Given its inherent capacity to securely, immutably, and permanently record multiple sequences of AI views of multiple hierarchical portfolios over long periods of time, the portable financial record may serve as an analytical foundation for tracing, tracking, and analyzing the complete history of context-specific financial advice (i.e., all of the AI views of the hierarchical portfolios owned by the investor) provided to, accepted by, and acted upon by the investor. This fundamental advantage of the present technology enables the investor or trusted advisors of the investor to make better financial decisions based on knowledge and insights accumulated over time in the blockchain-based portable financial record.”; [0076]: “In various embodiments, individual AI suggestions may be visible or invisible to a user depending upon the expansion state of the underlying portfolio hierarchy. For example, when the top-level node of the portfolio hierarchy is fully contracted, no AI suggestions may be visible to the user.”; [0193]: “Upon the declaration of a function, in addition to setting visibility (e.g., public, external, internal, private) and access (e.g., view, pure) attributes, a function modifier may be applied to conditionally alter the execution flow of the function itself. For example, a function modifier may be constructed named onlyOwner that specifies particular condition under which a function is permitted to execute, such as when the sender of the calling message is equal to the owner of the contract… Such a modifier may be important, especially in the case of a public blockchain, in order to prevent unidentified parties from inadvertently, or purposefully, adding new views to the RecordViews contract.”; and [0271]: “6) Determine the access rights to the PFR for the trusted advisor to the financial client.”).
As per claims 25, 30, 35, and 40, which respectively depend on claims 21, 26, 31, and 36, Cummings further teaches wherein: the first user device is operable to use public and private data for secure communication and anonymous advertising (see Cummings, [0086]: “The machine or cluster of machines may be configured support single-tenant or multi-tenant operations within a private cloud providing dedicated cloud resources (e.g., compute, storage, networking, security, etc.) for a single tenant (i.e., a business, such as a financial service firm), a public cloud providing shared cloud resources across multiple tenants, a hybrid cloud providing both dedicated and shared cloud resources by combining the dedicated resources of a private cloud with the shared resources of a public cloud, or a multi-cloud environment providing dedicated or shared cloud resources spanning a plurality of cloud service providers. The machine or cluster of machines may be further configured support various virtual machine hypervisors (e.g., Red Hat KVM, VMware ESXi, Microsoft Hyper-V, etc.) or container engines and orchestrators (e.g., Docker Engine, Google Kubernetes Engine, Amazon Elastic Kubernetes Service, Microsoft Azure Kubernetes Service, etc.).”; [0181]: “Anyone (e.g., users, validators, miners) may join, transactions are visible to all participants, and participant identity is typically masked.”; and [0133]: “Moreover, in various embodiments, an actionable AI view (e.g., AI view 400) may further contain context-specific promotional advertisements or product recommendations in addition to precisely located AI suggestions with recommended asset transactions. This key capability of the present technology offers an important advantage from the perspective of a financial firm: the ability to capture additional streams of revenue for the firm. More specifically, the financial firm may capture lead generation, customer conversion, or asset transaction revenue streams by directing online advertising traffic (e.g., traffic from banner ads, pay-per-click ads, cost-per-action ads, etc.), financial product recommendations (e.g., recommendations for mutual fund products, ETF products, ESG products, smart-beta/factor products, etc.), or asset transaction orders (e.g., orders to buy, sell, or transfer assets) to various third parties, including brand or performance advertisers targeting investors (e.g., individual or institutional investors), asset management companies offering mutual funds or ETFs to investors, and electronic trading platforms or other financial service companies providing asset transaction services for investors.”).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
7. Claims 23, 28, 33, and 38 are rejected under 35 U.S.C. 103 as being unpatentable over Cummings (US 2021/0264520 A1) in view of Rouhani et al. (US 2021/0019605 A1).
As per claims, which respectively depend on claims 23, 28, 33, and 38, although Cummings further teaches wherein: the first user device is operable to ensure data flow security, digital rights management, and malware prevention (see Cummings, [0007]: “Given its inherent capacity to securely, immutably, and permanently record multiple sequences of AI views of multiple hierarchical portfolios over long periods of time, the portable financial record may serve as an analytical foundation for tracing, tracking, and analyzing the complete history of context-specific financial advice (i.e., all of the AI views of the hierarchical portfolios owned by the investor) provided to, accepted by, and acted upon by the investor. This fundamental advantage of the present technology enables the investor or trusted advisors of the investor to make better financial decisions based on knowledge and insights accumulated over time in the blockchain-based portable financial record.”; [0193]: “Such a modifier may be important, especially in the case of a public blockchain, in order to prevent unidentified parties from inadvertently, or purposefully, adding new views to the RecordViews contract.”; and [0271]: “6) Determine the access rights to the PFR for the trusted advisor to the financial client.”), Cummings does not explicitly teach operable to ensure watermarking.
Rouhani teaches a device operable to ensure watermarking (see Rouhani, [0004]: “Systems, methods, and articles of manufacture, including computer program products, are provided for embedding a digital watermark in a machine learning model”; and [0012]: “In some variations, the first digital watermark may be embedded in a first copy of the first machine learning model distributed to a first client. A third digital watermark may be embedded in a second copy of the first machine learning model distributed to a second client. The first client may be determined to be a source of the second machine learning model based at least on the second digital watermark extracted from the second machine learning model matching first digital watermark embedded in the first copy of the first machine learning model.”).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the system of Cummings in view of Rouhani by implementing a device operable to ensure watermarking. One would be motivated to do so because Cummings teaches in paragraph [0076], “In various embodiments, individual AI suggestions may be visible or invisible to a user depending upon the expansion state of the underlying portfolio hierarchy. For example, when the top-level node of the portfolio hierarchy is fully contracted, no AI suggestions may be visible to the user.” and [0181]: “Anyone (e.g., users, validators, miners) may join, transactions are visible to all participants, and participant identity is typically masked.”, emphasis added.
Conclusion
8. For the reasons above, claims 21-40 have been rejected and remain pending.
9. Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL Y WON whose telephone number is (571)272-3993. The examiner can normally be reached on Wk.1: M-F: 8-5 PST & Wk.2: M-Th: 8-7 PST.
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/Michael Won/Primary Examiner, Art Unit 2443
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