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 .
Response to Amendments
Claims 1, 4-13, 16-23, and 25 remain pending in the application.
Claims 1, 5, 12-13, 16, 17, 19, and 20-22 have been amended.
Claim 24 has been canceled.
Claim 25 has been newly added.
The amendment filed 12/04/2025 is sufficient to overcome the 35 U.S.C. 101
rejections of claims 1, 4-13, 16-23. The previous rejections have been withdrawn.
The amendment filed 12/04/2025 is sufficient to overcome the 35 U.S.C. 102(a)(2)
rejections of claims 1, 5, 8, 9, 12-13, and 18-21. The previous rejections have been withdrawn.
Response to Arguments
Argument 1, regarding the 101 rejections, applicant argues that the claims are directed towards reducing the computational burden of a user equipment device by reducing computational resources needed and enhancing computational efficiency with limiting skills executed by an aggregated assistant based on determined impact, confirmation of a request, and confirmation regarding user data. Examiner agrees and the 101 rejections have been withdrawn.
Argument 2, regarding the prior art rejections, applicant argues that none of the cited prior art teaches “the executing of the one or more skills is based on an upper limit that limits a number of times that each skill of the plurality of skills is re-executable”. Examiner notes this point is moot in view of the 35 U.S.C. 103 rejection of claim 1 over Galitsky in view of O'Flaherty et al (Pub. No.: US 20060248167 A1), hereafter O'Flaherty.
O'Flaherty teaches the executing of the one or more skills is based on an upper limit that limits a number of times that each skill of the plurality of skills is re-executable, and the plurality of skills corresponds to automation components for the providing of the computer resources to the UE (In block 90 a check is made to determine if a successful connection has been established between PDA and the central computer. If a successful connection has been made, the PDA may download data from the central computer. If not, the PDA may attempt to connect to the central computer again until the maximum number of attempts has been reached. P0015, figure 2B).
The full prior art rejections are outlined below.
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.
Claims 1, 5, 8, 9, 12-13, and 18-21 are rejected under 35 U.S.C. 103 as being as being unpatentable over Galitsky et al (Pub. No.: US 11847420 B2), hereafter Galitsky in view of O'Flaherty et al (Pub. No.: US 20060248167 A1), hereafter O'Flaherty.
Regarding claims 1, 13, and 20, Galitsky teaches receiving a first request from a user equipment (UE) via a network, to execute a sequence of actions for providing computer resources to the UE (A customer using a client computing device may request one or more services provided by a cloud infrastructure system, the services including providing computing resources such as storage or networks, C29:L46-52, C30:L32-38, figure 13); generating, as the automated assistant, an aggregated assistant in real time based on the first request, wherein the aggregated assistant comprises one or more skills of a plurality of skills of the automated assistant, and the one or more skills includes a database query skill to access a database based on the first request (In view of P0007 of the specification of the instant application, the automated assistant is the aggregated assistant including a plurality of skills. Autonomous agent 108 may include question answering engine 112, C4:L26-27. Question answering engine 112 may inquire documents stored in database 114 based on a question provided by a user, C5:L44-54); outputting, to the UE via the network, a second request to receive a confirmation regarding the first request and a confirmation regarding user data, wherein the second request indicates the first request and the user data (“At operation 1338, the order information is forwarded to an order management module 1320. In some instances, order management module 1320 may be configured to perform billing and accounting functions related to the order, such as verifying the order, and upon verification, booking the order.”, C30:L53-57, figure 13); receiving, from the UE via the network, the confirmation regarding the first request and the confirmation regarding the user data (in response to service request 1334, identity management module 1328 may verify the identity of a user/customer, using client device 1308, as well as verify whether or not the user/customer is authorized to perform actions relative to computer resources based on user/customer data, figure 13, C31:L30-46. At step 1338, the user from their client device sends a confirmation that they had ordered the service requested in request 1334, C30:L53-57); determining an impact of the providing of the computer resources to the UE, on a system associated with the automated assistant (the system may dedicate more or fewer computing resources to a request given by an entity if doing so makes the system more available to complete tasks based on the demand of the entity, C28:L22-28. This cloud system is compatible with other aspects of the present disclosure, C26:L49-54, which includes implementation of an autonomous agent, figure 1, C4:L24-31. The Oracle Public Cloud is an example of a cloud system which provides subscription-based services, C27:L57-63); rendering a decision on whether to execute the sequence of actions, wherein the rendering of the decision is based on the determined impact, the received confirmation regarding the first request, and the received confirmation regarding the user data (Question answering engine 112 determines what kind of request the user has made and performs actions based on analysis of the user query. C5:L32-53); providing the computer resources to the UE based on the decision to execute the sequence of actions, wherein the providing of the computer resources comprises executing the database query skill of the one or more skills of the aggregated assistant (upon receiving an order, order provisioning module 1324 provides resources needed to fulfill the prescription order. At operation 1344, a notification of the provided service is sent to users on their client device(s), figure 13, C31:L2-21. An example of one of the subscriptions offered is access to an autonomous agent, figure 1, C4:L24-31, through the Oracle Public Cloud, C27:L57-63), … and outputting to the UE via the network an explanation about the rendered decision to execute the sequence of actions (constructed answer, including explanation chains regarding the decision process, are provided at the user device via user interface. C2:L66-67, C3:L1-5, and C5:L48-54), wherein the explanation includes: information about why a particular portion of the user data is used to render the decision to execute the sequence of actions (Explanation is constructed using a discourse tree. Leaves of the discourse tree correspond to particular portions of the text, meaning each leaf of the tree evaluates particular portions of the user query. C5:L58-67, C6:L1-14), and a technical causal chain explaining how the particular portion of the user data is used to render the decision to execute the sequence of actions, including whether the user data is shared with an entity different from the UE (Explanation is constructed using a discourse tree. Leaves of the discourse tree correspond to particular portions of the text, meaning each leaf of the tree evaluates particular portions of the user query. C5:L58-67, C6:L1-14. These complete decision trees are created by explanation chain manager 124, which generates explanation chains. Explanation chains include a chain of premises, with each element in the chain being used to imply its predecessor(s), C4:L38-49. Information supplied by the user data may be used to form these explanation chains, C5:L47-52).
Galitsky does not appear to explicitly teach “the executing of the one or more skills is based on an upper limit that limits a number of times that each skill of the plurality of skills is re-executable, and the plurality of skills corresponds to automation components for the providing of the computer resources to the UE”.
O'Flaherty teaches the executing of the one or more skills is based on an upper limit that limits a number of times that each skill of the plurality of skills is re-executable, and the plurality of skills corresponds to automation components for the providing of the computer resources to the UE (In block 90 a check is made to determine if a successful connection has been established between PDA and the central computer. If a successful connection has been made, the PDA may download data from the central computer. If not, the PDA may attempt to connect to the central computer again until the maximum number of attempts has been reached. P0015, figure 2B).
Accordingly, it would have been obvious to a person having ordinary skill in the
art before the effective filing date of the claimed invention, having the teachings of Galitsky and O'Flaherty before them, to include O'Flaherty’s specific teaching of a maximum limit of attempts of downloading data from a central computer in Galitsky’s system of Conversational Explainability. One would have been motivated to make such a combination of setting a maximum number of attempts a device may connect for the purpose of downloading data (see O'Flaherty P0015, figure 2B) and saving computing resources to be better available to carry out tasks on large data sets based on demand from a business, government agency, research organization, private individual, group of like-minded individuals or organizations, or other entity. (see Galitsky C28:L22-28).
Regarding claims 5 and 21, Galitsky in view of O'Flaherty teaches the limitations of claims 1 and 20 as outlined above. Galitsky further teaches receiving a query for a provenance of the user data used to render the decision to execute the sequence of actions (Question answering engine 112 receives one or more user queries from user device 106. Question answering engine 112 determines what kind of request the user has made and performs actions based on analysis of the user query. C5:L31-33); and generating a summary explanation about the provenance of the user data used to render the decision to execute the sequence of actions (Explanation chain manager 124 generates explanation chains and stores them in database 114. C4:L63-65. These chains are used when making decisions. C5:L47-54).
Regarding claims 8 and 18, Galitsky in view of O'Flaherty teaches the limitations of claims 5 and 13 as outlined above. Galitsky further teaches the summary explanation includes a reason why the particular portion of the user data is examined to render the decision to execute the sequence of actions (Explanation is constructed using a discourse tree. Leaves of the discourse tree correspond to particular portions of the text, meaning each leaf of the tree evaluates particular portions of the user query. C5:L58-67, C6:L1-14).
Regarding claim 9, Galitsky in view of O'Flaherty teaches the elements of claim 5 as outlined above. Galitsky further teaches wherein the explanation includes information about how the particular portion of the user data is used to render the decision to execute the sequence of actions (Explanation is constructed using a discourse tree. Leaves of the discourse tree correspond to particular portions of the text, meaning each leaf of the tree evaluates particular portions of the user query. C5:L58-67, C6:L1-14).
Regarding claims 12 and 19, Galitsky in view of O'Flaherty teaches the limitations of claims 5 and 13 as outlined above. Galitsky further teaches generating decision elements by the one or more skills of the plurality of skills or one or more agents of the aggregated assistant (In view of figure 3A of the instant application, skills include the authorization skill and the DBQ skill. “Identity management module 1328 may be configured to provide identity services, such as access management and authorization services in system environment 1300.”, C31:L31-34. “a service in a computer network cloud infrastructure may include protected computer network access to storage, a hosted database”, C27:L45-47); and including one or more explanations of the decision elements automatically (cloud infrastructure system 1302 may be adapted to automatically provision, manage and track a customer's services offered by cloud infrastructure system 1302. C28:L29-32).
Claims 4, 10, and 17 are rejected under 35 U.S.C. 103 as being as being unpatentable over Galitsky in view of O'Flaherty and further in view of Cui et al (Pub. No.: US 20210392706 A1), hereafter Cui.
Regarding claims 4, 10, and 17, Galitsky in view of O'Flaherty teaches the elements of claims 1, 5, and 13 as outlined above.
Galitsky in view of O'Flaherty does not appear to explicitly teach requesting confirmation to share at least a portion of the user data with the entity to render the decision to execute the sequence of actions.
Cui teaches requesting confirmation to share at least a portion of the user data with the entity to render the decision to execute the sequence of actions (“request to share media of the first user equipment with the second user equipment”, P0041).
Accordingly, it would have been obvious to a person having ordinary skill in the
art before the effective filing date of the claimed invention, having the teachings of Galitsky, O'Flaherty, and Cui before them, to include Cui’s specific teaching of users choosing to share their data with other user devices in Galitsky’s system of Conversational Explainability. One would have been motivated to make such a combination of letting users know if their data will be shared with other user devices (see Cui P0041) and sharing resources among different user devices to access different applications from different user devices (see Galitsky C16:L34-38 and C29:L61-63).
Claims 6-7, 16, and 22 are rejected under 35 U.S.C. 103 as being as being unpatentable over Galitsky in view of O'Flaherty and further in view of Cohen et al (Pub. No.: US 20210142253 A1), hereafter Cohen.
Regarding claims 6 and 22, Galitsky in view of O'Flaherty teaches the claim limitations of claims 5 and 21 as outlined above. Galitsky further teaches augmenting the provenance of the user data and an explanation of a part of the user data used by each action of the sequence of actions (response is provided to user query including the explanation chain. If the decision feature meets (or in some cases, does not meet) the premise provided by the explanation chain, the decision feature (e.g., including the user data) may be provided in the explanation generated. C24:L10-19).
Galitsky in view of O'Flaherty does not appear to explicitly teach generating the summary explanation about the provenance of the user data by using an explainability model.
Cohen teaches generating the summary explanation about the provenance of the user data by using an explainability model (explainability model is used to provide explanations for the local behavior of the decision model. P0045-P0046, P0054-P0055).
Accordingly, it would have been obvious to a person having ordinary skill in the
art before the effective filing date of the claimed invention, having the teachings of Galitsky, O'Flaherty, and Cohen before them, to include Cohen’s specific teaching of an explainability model being used to provide explanations for the local behavior of the decision model in Galitsky’s system of Conversational Explainability. One would have been motivated to make such a combination of an explainability model being used to provide explanations for the local behavior of the decision model (see Cohen P0045-P0046, P0054-P0055) and generating explanation chains to provide explanations to the user about the decision made (see Galitsky C24:L10-19).
Regarding claims 7 and 16, Galitsky in view of O'Flaherty teaches the claim limitations of claims 5 and 13 as outlined above. Galitsky in view of O'Flaherty does not appear to explicitly teach wherein the summary explanation is configured as a summary of landmarks to be drilled down recursively.
Cohen teaches wherein the summary explanation is configured as a summary of landmarks to be drilled down recursively (recursive partitioning is applied to the decision model to enable insight into covariate relationships between the set of features used to train the decision model. P0078).
Accordingly, it would have been obvious to a person having ordinary skill in the
art before the effective filing date of the claimed invention, having the teachings of Galitsky, O'Flaherty, and Cohen before them, to include Cohen’s specific teaching of recursive partitioning being applied to the decision model in Galitsky’s system of Conversational Explainability. One would have been motivated to make such a combination of recursive partitioning being applied to the decision model (see Cohen P0078) and generating explanation chains to provide explanations to the user about the decision made (see Galitsky C24:L10-19).
Claim 11 is rejected under 35 U.S.C. 103 as being as being unpatentable over Galitsky in view of O'Flaherty and further in view of Rand et al (Pub. No.: US 20220044149 A1), hereafter Rand.
Regarding claim 11, Galitsky in view of O'Flaherty teaches the claim limitations of claim 5 as outlined above. Galitsky in view of O'Flaherty does not appear to explicitly teach wherein the aggregated assistant is configured to be debugged based on sample compositions.
Rand teaches wherein the aggregated assistant is configured to be debugged based on sample compositions (debugging is done based on samples of code that contain a detected error, signaled by a Boolean flag. P0085, P0093).
Accordingly, it would have been obvious to a person having ordinary skill in the
art before the effective filing date of the claimed invention, having the teachings of Galitsky, O'Flaherty, and Rand before them, to include Rand’s specific teaching of debugging a AI assistant based on samples of code that contain a detected error in Galitsky’s system of Conversational Explainability. One would have been motivated to make such a combination of debugging a AI assistant based on samples of code that contain a detected error (see Rand P0085, P0093) and adjusting internal parameters of a model to improve its accuracy (see Galitsky C20:L22-26).
Claim 23 is rejected under 35 U.S.C. 103 as being as being unpatentable over Galitsky in view of O'Flaherty and further in view of Reinhold (Pub. No.: US 20180367309 A1), hereafter Reinhold.
Regarding claim 23, Galitsky in view of O'Flaherty teaches the claim limitations of claim 1 as outlined above. Galitsky in view of O'Flaherty does not appear to explicitly teach outputting, to the UE via the network, a third request to receive a permission for sharing the user data with the one or more skills for the providing of the computer resources to the UE; receiving, from the UE via the network, the permission for the sharing of the user data; detecting, based on the executing of the one or more skills using the shared user data, whether the shared user data is sufficient for the providing of the computer resources to the UE; in a case where the shared user data is sufficient, providing the computer resources to the UE; in a case where the shared user data is not sufficient: requesting additional user data for the providing of the computer resources to the UE; and re-executing the one or more skills using the shared user data and the additional user data.
Reinhold teaches outputting, to the UE via the network, a third request to receive a permission for sharing the user data with the one or more skills for the providing of the computer resources to the UE (“ User: Attempts to access computer resource Password System (PS): Upon detecting a computer resource access request: PS: (display step) Display login screen asking user for userID and password”, P0125); receiving, from the UE via the network, the permission for the sharing of the user data (“User: Enters userID and password”, P0125); detecting, based on the executing of the one or more skills using the shared user data, whether the shared user data is sufficient for the providing of the computer resources to the UE (“PS: Attempt to retrieve user's record from password verification database indexed by userID…PS: Extract the following three data strings from the user's record: version info, verification data, salt PS: Calculate a hash value of the password and salt using the hash technique specified by version”, P0125); in a case where the shared user data is sufficient, providing the computer resources to the UE (“PS: Allow access”, P0125); in a case where the shared user data is not sufficient: requesting additional user data for the providing of the computer resources to the UE (“PS: If there is no record indexed by userID, display login fail message then go to display step… If the hash value calculated in previous step does not match verification data, display login fail message then go to display step”, P0125); and re-executing the one or more skills using the shared user data and the additional user data (When user data is not sufficient, a login fail message is displayed and user is prompted to try again, P0125).
Accordingly, it would have been obvious to a person having ordinary skill in the
art before the effective filing date of the claimed invention, having the teachings of Galitsky, O'Flaherty, and Reinhold before them, to include Reinhold’s specific teaching of verifying user data before providing computer resources in Galitsky’s system of Conversational Explainability. One would have been motivated to make such a combination of verifying user data before providing computer resources (see Reinhold P0125) and leveraging fewer computer resources to free up the cloud infrastructure system for carrying out tasks based on demand of various entities (see Galitsky C28:L22-28).
Claim 25 is rejected under 35 U.S.C. 103 as being as being unpatentable over Galitsky in view of O'Flaherty and further in view of Nowak-Przygodzki et al (US 20190080169 A1), hereafter Nowak-Przygodzki.
Regarding claim 25, Galitsky teaches determining a failure in execution of a first planner attempt of the plurality of planner attempts, wherein the execution of the first planner attempt is based on a first set of skills from the plurality of skills of the automated assistant (Automated assistant fails to identify user’s request, C19:L45-51)… and receiving, based on the executing of the second planner attempt, additional information for the providing of the computer resources (order provisioning module 1324 provides resources based on requests made by the user, C31:L2-16).
Galitsky does not appear to explicitly teach “executing, based on the determining of the failure in the execution of the first planner attempt, a second planner attempt of the plurality of planner attempts using a second set of skills from the plurality of skills of the automated assistant, wherein the second set of skills includes the database query skill, an optical character recognition (OCR) skill, and a resource skill”.
Nowak-Przygodzki teaches executing, based on the determining of the failure in the execution of the first planner attempt, a second planner attempt of the plurality of planner attempts using a second set of skills from the plurality of skills of the automated assistant, wherein the second set of skills includes the database query skill, an optical character recognition (OCR) skill, and a resource skill (instead of inputting text or audio requests, users may input images for the automated assistant to process with optical character recognition (OCR) as well as evaluate queries a knowledge graph or other databases, P0060-P0061, P0027).
Accordingly, it would have been obvious to a person having ordinary skill in the
art before the effective filing date of the claimed invention, having the teachings of Galitsky, O'Flaherty, and Nowak-Przygodzki before them, to include Nowak-Przygodzki’s specific teaching of an automated assistant using optical character recognition, a knowledge graph, and other databases to evaluate requests and queries made by a user in Galitsky’s system of Conversational Explainability. One would have been motivated to make such a combination of an automated assistant using optical character recognition, a knowledge graph, and other databases to evaluate requests and queries made by a user (see Nowak-Przygodzki P0060-P0061, P0027) and an autonomous agent evaluating a user query against explanation chains to describe the logical chain of explanations associated with a decision (see Galitsky C23:L66-67, C24:L1-9).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20220114020 A1 (Akkapeddi et al) teaches a capacity optimizing tool that limits how many computational resources are allocated to devices based on events that may require more resources than allocated (see Akkapeddi P0016, P0028, P0031).
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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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/I.M./Examiner, Art Unit 2141
/MATTHEW ELL/Supervisory Patent Examiner, Art Unit 2141