DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . This office action is in response to communication filed 10/30/2025.
The instant application having application No. 18/242,676 filed on September 6, 2023, claims priority to provisional appl. 63/486596, filed 2/23/2023, and to provisional appl. 63/450838, filed 3/8/2023.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 9/16/2025 and on 12/9/2025, were filed before the mailing date of the Final Office Action. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Status of the Claims
Claims 1, 7, 11, 17, and 20 are amended, claims 6 and 16 are canceled. Accordingly, claims 1-5, 7-15, and 17-20 are currently pending in the application.
Response to Amendment
(A). Regarding 35 U.S.C. § 101 rejection: Applicant’s amendment to claim 20 appropriately addressed the 101 signal per se rejection, the rejection is withdrawn.
(B). Regarding 35 U.S.C. § 101 abstract idea rejection: The amended claims are still abstract idea without significantly more, the 101 rejections are maintained as set forth below.
(C). Regarding art rejection: In regards to pending claims Applicant’s arguments are not persuasive; further, Applicant's amendments necessitated new grounds of rejections presented in the following art rejection.
Examiner Notes
Examiner cites particular columns, paragraphs, figures and line numbers in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner.
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 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.
Claim Objections
Claims 1-5, 7-15, and 17-20 are objected to because of the following informalities:
Claim 1, line 2, “the accuracy and efficiency” lacks proper antecedent basis.
Claims 11 and 20 have the same issue as claim 1, and are objected to for the same reason.
Dependent claims 2-5, 7-10, and 12-15, 17-19 are objected to for the same reason because they depend from their respective independent claim 1 or 11.
Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-5, 7-15, and 17-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
With respect to claim 1, This claim is within at least one of the four categories of patent eligible subject matter as it is directed to a method claim under Step 1.
Under Prong 1, Step 2A:
However, the limitations of claim 1,
“pre-processing, by the one or more processors, the set of data to format and extract feature vectors;
generating, by the one or more processors, one or more embeddings from the feature vectors;
determining, by the one or more processors executing a machine learning (ML) chatbot, based upon the embeddings library, that the set of data indicates a potential update to at least one component of the communication system, wherein the ML chatbot is trained with a plurality of training data corresponding to the communication system as inputs to generate a plurality of training update indications as outputs;
generating, by the one or more processors executing the ML chatbot, an update indication corresponding to the set of data; and
displaying, by the one or more processors, the update indication on a user interface for viewing by a user.”
as drafted, are functions that, under its broadest reasonable interpretation, cover performance of the limitation in the mind but for the recitation of a generic processing device. That is, other than reciting “by the one or more processors executing a machine learning (ML) chatbot” nothing in the claim element “determining, …, that the set of data indicates a potential update to at least one component of the communication system” precludes the step from practically being performed in the mind. E.g. but for the “by the one or more processors executing a machine learning (ML) chatbot” language, “determining” in the context of this claim encompasses the user manually determining whether the set of data indicates a potential update to at least one component of the communication system. For “wherein the ML chatbot is trained with a plurality of training data corresponding to the communication system as inputs to generate a plurality of training update indications as outputs”, as drafted, are functions that, under its broadest reasonable interpretation, cover performance of the limitation in the mind because human can collect training data corresponding to the communication system as inputs to train the ML chatbot to output update indications. Similarly, other than reciting “by the one or more processors executing the ML chatbot” nothing in the claim element “generating, …, an update indication corresponding to the set of data” precludes the step from practically being performed in the mind. E.g. but for the “by the one or more processors executing the ML chatbot” language, “generating” in the context of this claim encompasses the user manually generating an update indication corresponding to the set of data. And, other than reciting “by the one or more processors” nothing in the claim element “displaying, …, the update indication on a user interface for viewing by a user” precludes the step from practically being performed in the mind. E.g. but for the “by the one or more processors” language, “displaying” in the context of this claim encompasses the user manually displaying the update indication on a user interface for viewing by a user. Similarly, other than reciting “by the one or more processors” nothing in the claim precludes the user from manually performing “pre-processing, …, the set of data to format and extract feature vectors;” and “generating, … , one or more embeddings from the feature vectors;” Thus these claim limitations fall within the “Mental Processes” grouping of abstract ideas under Prong 1 Step 2A
Under Prong 2, Step 2A:
The judicial exception is not integrated into a practical application. The claim recites the following additional elements
“a communication system”,
“the one or more processors executing a machine learning (ML) chatbot”,
“retrieving, by one or more processors, a set of data corresponding to the communication system from one or more sources external to the communication system”,
“storing, by the one or more processors, the one or more embeddings in an embeddings library;”
Wherein a communication system, processors and ML chatbot are recited at a high-level of generality (i.e. as a generic communication system, or generic computer components performing generic computer functions) such that it amounts to no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. “retrieving, by one or more processors, a set of data …” and “storing, …, the one or more embeddings in an embeddings library” are insignificant extra-solution data retrieval activity such as gathering and storing data, according to MPEP 2106.05(g); thus, not indicative of an integration into a practical application.
Under Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements “a communication system”, and “the one or more processors executing a machine learning (ML) chatbot”, that are mere use of generic computer to implement the abstract idea, thus, are not an inventive concept. “retrieving, by one or more processors, a set of data …” and “storing, …, the one or more embeddings in an embeddings library” are insignificant extra-solution data retrieval and storing activities which are recognized as well-understood, routine, and conventional activities, see MPEP § 2106.05(d)(II). Accordingly, the claim does not appear to be patent eligible under 35 USC 101.
With respect to claim 11, This claim is within at least one of the four categories of patent eligible subject matter as it is directed to a system claim under Step 1.
This claim recites A system to implement a method that is disclosed in claim 1 and therefore recites the same abstract idea as claim 1, please see the office action analysis regarding claim 1.
Claim 11 recites more additional elements that are not recited in claim 1, i.e. “a user interface” and “a non-transitory computer-readable memory” but these elements are recited at a high-level of generality (i.e. as a generic computer component) such that it amounts to no more than mere instructions to apply the exception using a generic computer component.
With respect to claim 20, This claim is within at least one of the four categories of patent eligible subject matter as it is directed to a non-transitory machine-readable medium claim under Step 1.
This claim recites a non-transitory machine-readable medium to implement a method that is disclosed in claim 1 and therefore recites the same abstract idea as claim 1, please see the office action analysis regarding claim 1.
Claim 20 recites more additional elements that are not recited in claim 1, i.e. “a machine” and “a non-transitory computer-readable medium” but these elements are recited at a high-level of generality (i.e. as a generic computer component) such that it amounts to no more than mere instructions to apply the exception using a generic computer component.
With respect to claims 2 and 12, “wherein generating the update indication further comprises:
generating, by the one or more processors executing the ML chatbot, the update indication corresponding to the set of data and an update template associated with the update indication,
wherein the update template includes data from the set of data required to process the update for the communication system.” wherein the “generating …” process is the same generating process as in claim 1 which is analyzed as mental process, please refer to office action regarding claim 1 above for analysis. And the limitation “wherein the update template includes data from …” as drafted, is merely indicating a field of use or technological environment in which to apply a judicial exception, and does not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application. See MPEP § 2106.05(h).
With respect to claims 3 and 13, “wherein the ML chatbot is further trained using a plurality of training user inputs corresponding to a plurality of training update templates, and the method further comprises:
receiving, at the one or more processors, a user input corresponding to the update indication; and
generating, by the one or more processors executing the ML chatbot, the update template based upon the user input and in a style representative of the user input.” Wherein “the ML chatbot is further trained using a plurality of training user inputs corresponding to a plurality of training update templates” is similar to the chatbot training in claim 1 which is analyzed as mental process, please refer to office action regarding claim 1 above for analysis. The “generating …” process is the same generating process as in claim 1 which is analyzed as mental process, please refer to office action regarding claim 1 above for analysis. And the limitation “receiving, at the one or more processors, a user input corresponding to the update indication” is insignificant extra-solution data gathering activity which is recognized as well-understood, routine, and conventional activity, see MPEP § 2106.05(d)(II).
With respect to claims 4 and 14, “wherein the update indication includes (i) a predicted update associated with at least one component of the communication system, (ii) a predicted impact of the predicted update, and (iii) a predicted time of the predicted update” as drafted, is merely indicating a field of use or technological environment in which to apply a judicial exception, and does not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application. See MPEP § 2106.05(h).
With respect to claims 5 and 15, “further comprising:
receiving, at the one or more processors, a user input including (i) a first indication corresponding to the predicted update associated with the at least one component of the communication system, (ii) a second indication corresponding to an impact of the predicted update to the communication system, and (iii) third indication corresponding to a time of the predicted update; and
re-training, by the one or more processors, the ML chatbot based upon the user input.” Wherein the “receiving … “ process is similar to the receiving process in claim 3 which is analyzed as insignificant extra-solution activity, please refer to office action regarding claim 3 above for analysis. The “re-training …” process is similar to the chatbot training process in claim 1 which is analyzed as mental process, please refer to office action regarding claim 1 above for analysis.
With respect to claims 7 and 17, “wherein generating the update indication further comprises:
retrieving, by the one or more processors, one or more prior update indications from an update indication database based upon the one or more embeddings; and
generating, by the one or more processors executing the ML chatbot, the update indication based upon the set of data and the one or more prior update indications.” Wherein the “retrieving …” and “generating …” processes are similar to the retrieving and generating processes in claim 1 which are analyzed as mental processes, please refer to office action regarding claim 1 above for analysis.
With respect to claims 8 and 18, “wherein generating the update indication further comprises:
inputting, by the one or more processors, a plurality of documentation corresponding to the communication system into the ML chatbot; and
generating, by the one or more processors executing the ML chatbot, the update indication based upon the set of data corresponding to the communication system and the plurality of documentation.” Wherein the “generating …” process is similar to the generating process in claim 1 which is analyzed as mental processes, please refer to office action regarding claim 1 above for analysis. Wherein the “inputting … “ process, as drafted, are functions that, under its broadest reasonable interpretation, cover performance of the limitation in the mind but for the recitation of a generic processing device. That is, other than reciting “by the one or more processors” nothing in the claim element “inputting, …, a plurality of documentation corresponding to the communication system into the ML chatbot” precludes the step from practically being performed in the mind. E.g. but for the “by the one or more processors” language, “inputting” in the context of this claim encompasses the user manually inputting a plurality of documentation corresponding to the communication system into the ML chatbot. And the one or more processors are recited as generic computer component to implement the identified abstract idea.
With respect to claim 9, “wherein the potential update to the at least one component of the communication system corresponds to at least one of: (i) a software update or (ii) a hardware update.” as drafted, is merely indicating a field of use or technological environment in which to apply a judicial exception, and does not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application. See MPEP § 2106.05(h).
With respect to claims 10 and 19, “wherein:
the one or more sources external to the communication system comprises one or more of:(i) a social media platform, (ii) a news platform, (iii) a blog, (iv) a manufacturer website, or (v) a service provider website; and
the set of data corresponding to the communication system comprises one or more of: (i) a social media post, (ii) an article posted on a news platform, (iii) a blog excerpt, or (iv) a portion of the manufacturer website or the service provider website.” as drafted, is merely indicating a field of use or technological environment in which to apply a judicial exception, and does not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application. See MPEP § 2106.05(h).
Claim Rejections - 35 USC § 103
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 of this title, 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, 4, 9-11, 14, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Molander et al. (US 20230273783 A1, hereinafter “Molander”) in view of ZHANG et al. (US 20240037896 A1, hereinafter “ZHANG”), Rawat et al. (US 20210326757 A1, hereinafter “Rawat”), NING et al. (US 20240267243 A1, hereinafter “NING”) and Pascal et al. (US 20230386657 A1, hereinafter “Pascal”).
With respect to claim 1 (Currently Amended), Molander discloses A computer-implemented method for proactively managing updates in a communication system to improve the accuracy and efficiency of update identification and implementation, the method comprising:
determining, by the one or more processors executing a machine learning [(ML) chatbot], [based upon the embeddings library], that the set of data indicates a potential update to at least one component of the communication system, wherein the [ML chatbot] is trained with a plurality of training data corresponding to the communication system as inputs to generate a plurality of training update indications as outputs (e.g. para [0081], “… in another embodiment the analysis may include inputting the collective data into an artificial neural network trained to generate, as an output, a recommendation as to whether or not the updated version of the software program should be installed on the first computer device. …” wherein a recommendation reads on indicating a potential update, Fig. 1 shows a communication system);
generating, by the one or more processors executing the ML [chatbot], an update indication corresponding to the set of data (e.g. para [0083], “… if it is determined that the updated version of the software program should be installed on the first computer device at step 508, then flow proceeds to at least one of step 514, step 516, or step 518. At step 514, the update controller notifies the first user that installation of the updated version on the first computer device is recommended. …” wherein notifies the user reads on an update indication); and
Molander does not appear to explicitly disclose
a machine learning chatbot,
retrieving, by one or more processors, a set of data corresponding to the communication system from one or more sources external to the communication system;
pre-processing, by the one or more processors, the set of data to format and extract feature vectors;
generating, by the one or more processors, one or more embeddings from the feature vectors;
storing, by the one or more processors, the one or more embeddings in an embeddings library;
(determining, by the one or more processors executing a machine learning (ML) chatbot), based upon the embeddings library, that the set of data indicates a potential update …;
displaying, by the one or more processors, the update indication on a user interface for viewing by a user.
However, in analogous art, ZHANG discloses
pre-processing, by the one or more processors, the set of data to format and extract feature vectors (e.g. Fig. 3, para [0085], “… the control unit 220 of the computing apparatus 200 extracts feature vectors related to each character of a video from video data including vision data and subtitle data and question data for answering video questions and answers, …”);
generating, by the one or more processors, one or more embeddings from the feature vectors (e.g. para [0085], “… and generates an input embedding using the feature vectors related to the character.”);
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the invention of Molander and the invention of ZHANG because it provides techniques for effectively acquiring desired information. A person having ordinary skill in the art would have been motivated to make this combination, with a reasonable expectation of success, for the purpose of providing techniques for effectively acquiring desired information as suggested by ZHANG (see para [0021, 0022]).
Molander as modified by ZHANG does not appear to explicitly disclose
a machine learning chatbot,
retrieving, by one or more processors, a set of data corresponding to the communication system from one or more sources external to the communication system;
storing, by the one or more processors, the one or more embeddings in an embeddings library;
(determining, by the one or more processors executing a machine learning (ML) chatbot), based upon the embeddings library, that the set of data indicates a potential update …;
displaying, by the one or more processors, the update indication on a user interface for viewing by a user.
However, in analogous art, Rawat discloses
storing, by the one or more processors, the one or more embeddings in an embeddings library (e.g. Fig. 2, Global Embeddings. Para [0073], “… The data 218 can be stored in one or more databases. …”);
(determining, by the one or more processors executing a machine learning (ML) chatbot), based upon the embeddings library, that the set of data indicates a potential update … (e.g. para [0064], “The information indicative of the updates may include the locally-updated embeddings (e.g., the updated embeddings or a difference between the updated embeddings and the previous embeddings). …”);
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the invention of Rawat because it provides techniques for more effective and/or accurate embeddings to be generated in fewer training iterations. A person having ordinary skill in the art would have been motivated to make this combination, with a reasonable expectation of success, for the purpose of providing techniques for more effective and/or accurate embeddings to be generated in fewer training iterations as suggested by Rawat (see para [0026]).
Molander as modified by ZHANG and Rawat does not appear to explicitly disclose
a machine learning chatbot,
retrieving, by one or more processors, a set of data corresponding to the communication system from one or more sources external to the communication system;
displaying, by the one or more processors, the update indication on a user interface for viewing by a user.
However, in analogous art, NING discloses
a machine learning chatbot (e.g. para [0078], “In the present embodiment, the creation of the communication group, the association of target objects and the maintenance of the communication group are realized through the chatbot; …”),
displaying, by the one or more processors, the update indication on a user interface for viewing by a user (e.g. para [0078], “… The input first information and the automatically-generated update message are synchronized into the communication group, the notification message is sent in the form of a message card via the chatbot, and the information page of the target object is opened via the applet after the notification message is triggered, …” wherein the notification message is triggered indicates that the notification message is displayed).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the invention of NING because it can ensure the consistency of information about collaborative users and improve the collaboration efficiency. A person having ordinary skill in the art would have been motivated to make this combination, with a reasonable expectation of success, for the purpose of ensuring the consistency of information about collaborative users and improve the collaboration efficiency as suggested by NING (see para [0017]).
Molander as modified by ZHANG, Rawat and Ning does not appear to explicitly disclose
retrieving, by one or more processors, a set of data corresponding to the communication system from one or more sources external to the communication system;
However, in analogous art, Pascal discloses
retrieving, by one or more processors, a set of data corresponding to the communication system from one or more sources external to the communication system (e.g. para [0063], “… the first computing device may first download/retrieve a file from the external server, wherein the file comprises information on which software patches are available for which versions of said at least one medical practice software and then compare the retrieved information with the information comprised in the above-mentioned exemplary local database or local file in order to determine whether to download/retrieve any software patch(es) present on/provided by the external
server. …”);
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the invention of Pascal because it provides techniques that facilitate and improve the managing, maintaining and updating of medical practice software. A person having ordinary skill in the art would have been motivated to make this combination, with a reasonable expectation of success, for the purpose of providing techniques that facilitate and improve the managing, maintaining and updating of software as suggested by Pascal (see para [0005, 0009]).
With respect to claim 4 (Original), Molander discloses wherein the update indication includes (i) a predicted update associated with at least one component of the communication system (e.g. para [0080], “At step 508, a determination is made whether or not the updated version of the software program should be installed on the first computer device. …” wherein the updated version of the software program reads on the predicted update), (ii) a predicted impact of the predicted update (e.g. para [0079], “… The update controller may compile or aggregate the point values to produce a score associated with the updated version of the software program.” Wherein a score associated with the updated version of the software program reads on a predicted impact), and (iii) a predicted time of the predicted update (e.g. para [0083], “… The notification may also prompt the first user to either select immediate installation of the updated version or to schedule installation of the updated version. …”).
With respect to claim 9 (Original), Molander discloses wherein the potential update to the at least one component of the communication system corresponds to at least one of: (i) a software update (e.g. para [0080], “At step 508, a determination is made whether or not the updated version of the software program should be installed on the first computer device. …”) or (ii) a hardware update.
With respect to claim 10 (Original), Molander as modified by Zhang, Rawat, Ning and Pascal discloses The computer-implemented method of claim 1, Pascal further discloses wherein:
the one or more sources external to the communication system comprises one or more of:(i) a social media platform, (ii) a news platform, (iii) a blog, (iv) a manufacturer website, or (v) a service provider website (e.g. para [0052], “… the first computing device may query said server from the external network, e.g., a web server on the internet, to check whether there are any new software patches available for at least one computing device of said plurality of computing devices of the local network.” For motivation to combine, please refer to office action regarding claim 1); and
the set of data corresponding to the communication system comprises one or more of: (i) a social media post, (ii) an article posted on a news platform, (iii) a blog excerpt, or (iv) a portion of the manufacturer website or the service provider website (e.g. para [0055], “Said determination can inter alia be based on comparing the information, e.g., metadata, in the file retrieved from the server of the external network with the information comprised in the local database or in the local file stored in the local network that may store all information regarding what versions of the at least one medical practice software are installed on the computing devices of the local network.” Wherein the file retrieved form the server reads on a portion of the service provider website. For motivation to combine, please refer to office action regarding claim 1).
With respect to claim 11 (Currently Amended), it is directed to a system to implement the method disclosed in claim 1, please see the rejections directed to claim 1 above which also cover the limitations recited in claim 11. Note that, Molander teaches A system for proactively managing updates in a communication system to improve the accuracy and efficiency of update identification and implementation, comprising:
a user interface;
one or more processors; and
a non-transitory computer-readable memory coupled to the one or more processors and the user interface, the memory storing instructions thereon that, when executed by the one or more processors, cause the one or more processors to (e.g. Fig. 1):
With respect to claim 14 (Original), it recites same features as claim 4, and is rejected for the same reason.
With respect to claim 19 (Original), it recites same features as claim 10, and is rejected for the same reason.
With respect to claim 20 (Currently Amended), it is directed to a machine-readable medium to implement the method disclosed in claim 1, please see the rejections directed to claim 1 above which also cover the limitations recited in claim 20. Note that, Molander teaches A non-transitory machine-readable medium comprising instructions for proactively managing updates in a communication system to improve the accuracy and efficiency of update identification and implementation, that, when executed, cause a machine to at least (e.g. Fig. 1, wherein memory reads on machine-readable medium):
Allowable Subject Matter
Claims 2-3, 5, 7-8, 12-13, and 15, 17-18 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims, and after the 101 abstract idea rejections are overcome.
Response to Arguments
Applicant's arguments filed 10/30/2025 have been fully considered but they are not persuasive.
At p9 to p14 second paragraph of the Remarks, Applicant argued that “Under Step 2A, Prong Two, Applicant respectfully submits that the claims integrate any judicial exception into a practical application at least in view of the following Step 2A, Prong Two considerations.” Particularly, at p10 first full paragraph of the Remarks, Applicant argued that “At least these elements of representative claim 1 provide an improvement upon many existing computing technologies in the field of communication system update management.”
Examiner respectfully disagrees, because, as set forth in the office action above, the “pre-processing …”, “generating …”, and “determining …” processes are identified as mental processes. The “storing …” process is insignificant extra-solution activity which is recognized as well-understood, routine, and conventional activity, see MPEP § 2106.05(d)(II). Thus, these elements do not integrate the identified abstract idea into a practical application.
After citing some paragraphs of the instant spec in part of p10-p11 of the Remarks, at p11 second from the last paragraph of the Remarks, Applicant argued that “As such, the transformation from static and error-prone update workflows to ML-based update management "transform[s] or reduc[es] the maintenance and updating of a communication system...from a non-optimal or error state to an optimal state." …. More specifically, the above-identified elements recited in amended claim 1 help achieve the advantages described in at least paragraphs [0027]-[0031], [0040], and [0104] of the specification. In particular, "pre-processing...the set of data to format and extract feature vectors" enables normalization and preparation of heterogeneous external and internal system data for downstream ML analysis. See, e.g., id. at paras. [0028] and [0040]. The step of "generating...one or more embeddings from the feature vectors" creates structured, compact numeric representations of update-related information, which are then "stored, ... in an embeddings library." This architecture allows for efficient storage, retrieval, and comparison of diverse data inputs while retaining semantic and operational relationships within the data.”
Examiner respectfully disagrees, because, as set forth in the office action, “the transformation from static and error-prone update workflows to ML-based update management” is merely using a computer with software (ML) as a tool to implement the identified abstract idea. The transformation may reduce maintenance and/or transform from a non-optimal state to an optimal state for updating a communication system, it is the benefit of using a computer as a tool, technology is not affected. As explained above in 33, the “pre-processing …”, “generating …”, and “determining …” processes are identified as mental processes. And the “storing …” process is insignificant extra-solution activity which is recognized as well-understood, routine, and conventional activity, see MPEP § 2106.05(d)(II).
At p11 last to p12 first paragraph of the Remarks, Applicant argued that “As discussed during the interview, by structuring data corresponding to the communication system as embeddings and updating the embeddings library in response to retrieved data, the system can "accurately and efficiently determine potential updates to communication system subsystems/components and generate update indications corresponding to those potential updates." …. The architecture leverages the ML chatbot trained on communication system-specific data to perform similarity and/or pattern analysis with these embeddings across the embeddings library and generate system-tailored update indications. ….”
Examiner respectfully disagrees, because, structuring data, generating embeddings and updating the embedding library in response to retrieved data are all mental processes, as human can manually perform these tasks. Even the system can “accurately and efficiently determine potential updates to communication system subsystems/components and generate update indications corresponding to those potential updates.” The accuracy and the efficiency are the benefit of using a computer as a tool. Similarly, similarity and/or pattern analysis with these embeddings and generating system tailored update indications are mental processes, the trained ML chatbot is merely using a computer with software (ML chatbot) as a tool to implement the identified abstract idea of mental processes. Again no technology is affected, as the computer works the same as it would before the instant case.
At p12 second paragraph of the Remarks, Applicant argued that “Compared to conventional methods, which require ad hoc detection, template creation, and comparison, the present techniques substantially reduce such error-prone guesswork. Instead, communication system update management using the present techniques leverages a computationally efficient and continuously updated ML-framework that transforms new/retrieved data into update signals through several computing-specific steps. At least by updating the embeddings library over time, the ML chatbot of the present techniques continuously improves the underlying computing efficiency and accuracy by creating an ever- expanding reference list (library) contained in software the chatbot can query and analyze in a manner the human mind is simply incapable of achieving. As such, the present techniques improve the reliability of update identification and deployment and reduce unnecessary resource consumption by analyzing compact representations in the embeddings library rather than raw, unstructured data, thereby "improving the functioning of the computer itself or any other technology or technical field."”
Examiner respectfully disagrees, because, the conventional methods may be prone to human error, but it is not guesswork. The ML-framework is less error prone, just like accuracy and efficiency, it is the benefit of using a computer as a tool, it does not affect technology. Updating the embeddings library, analyzing/comparing embeddings and generating update indications are mental processes. Even using the ML-framework, the raw, unstructured data still need be processed, such as a pre-processing process. The ML-framework may improve the reliability of update identification (because less prone to human error), again, it is the benefit of using a computer as a tool, technology is not affected.
At p12 last paragraph of the Remarks, Applicant argued that “Further, Applicant respectfully submits that, when considered as a whole, at least the particular arrangement and interaction of the components in the above-recited claim elements (e.g., feature extraction, embedding generation, dynamic update of an embeddings library, and ML-driven update determination) yields a specific and concrete implementation that addresses real-world technical problems in communication system update management. For example, Applicant respectfully submits the independent claims are similar to those in BASCOM Global Internet Services, Inc. v. AT&TMobility LLC, at least because the claims represent more than an abstract idea, achieving a concrete improvement in computer functionality through the inventive combination of claim elements.”
Examiner respectfully disagrees, because, in BASCOM, “an inventive concept may be found in the non-conventional and non-generic arrangement of the additional elements, i.e., the installation of a filtering tool at a specific location, remote from the end-users, with customizable filtering features specific to each end user”. The instant case does not recite any feature similar to BASCOM. Thus, BASCOM is not applicable. As set forth in the office action and as explained above, the feature extraction, embedding generation, dynamic update of an embeddings library, and update determination are mental processes, the ML-framework is merely using a computer with software (ML) as a tool to implement the identified abstract idea, even viewed as a whole, the claim does not appear to be patent eligible under 35 USC 101.
At p13 first two paragraphs of the Remarks, Applicant compared the instant case to BASCOM, and argued that “As mentioned, existing techniques suffer from notable inefficiency and unreliability. See, e.g., Specification, paras. [0004], [0005], [0027]-[0031], and [0040]. The independent claims overcome these challenges (and yield technical improvements) at least by integrating update- related data from diverse external data sources (e.g., social media platforms, news platforms, blogs, manufacturer websites, and service provider websites) using an embedding and ML-based analytical architecture to proactively manage communication system updates, in a manner such existing techniques are unable to replicate. See Specification, paras. [0006], [0014], and [0020].”
Examiner respectfully disagrees, because, the instant claims do not recite features that are similar to BASCOM such as “the installation of a filtering tool at a specific location, remote from the end-users, with customizable filtering features specific to each end user”, thus BASCOM is applicable. Further, integrating update-related data and generating embeddings are mental processes, the ML-framework is merely using a computer with software (ML) as a tool to implement the identified abstract idea. The instant case may provide a solution to challenges to existing techniques, but the solution is abstract idea without significantly.
At p13 third paragraph of the Remarks, Applicant argued that “By leveraging embeddings, the claimed elements avoid the inefficiency/imprecision and unreliability present in existing (e.g., rule-based) techniques, ensuring computing resources are directed toward the analysis of contextually/semantically similar embedded data, rather than wasteful raw-data scanning. Moreover, the claimed determination process, using embeddings- based (e.g., similarity-based) evaluation against a dynamically updated embeddings library via a ML chatbot, ensures that highly similar/relevant updated information is selected for inclusion as part of an update indication and potential system response/update(s). As such, the present techniques employ an advanced technical mechanism that avoids the pitfalls of traditional, imprecise approaches, which do not systematically structure or analyze incoming data. Instead, the claimed approach processes and embeds data for efficient and highly precise ML-driven action, thereby overcoming the shortcomings of slow, erroneous, and resource-intensive legacy strategies.”
Examiner respectfully disagrees, because, generating and using embeddings are mental processes as human can manually perform these tasks. Even using the ML-framework, raw-data still need be processed such as pre-processing process. selecting similar/relevant updated information for inclusion as part of an update indication and potential system response/update(s) is mental process, the instant claims may avoid the inefficiency/imprecision and unreliability present in the existing techniques, but the efficiency/precision and reliability are benefits of using a computer as a tool, no technology is affected.
At p13 last to p14 first paragraph of the Remarks, Applicant argued that “Accordingly, Applicant respectfully submits the independent claims, like the claims in BASCOM, are directed to more than an abstract idea. They provide a specific technical solution to challenges in communication system updating, leveraging inventive process combinations to achieve tangible improvements in the functioning of the underlying computing systems.”
Examiner respectfully disagrees, because, as explained above, the instant claims do not recite feature similar to BASCOM such as “the installation of a filtering tool at a specific location, remote from the end-users, with customizable filtering features specific to each end user”, thus BASCOM is applicable. Further, as set forth in the office action, and as explained above, the ML-framework is merely using a computer with software (ML) as a tool to implement the identified abstract idea. The other claim elements are either mental processes or insignificant extra-solution activities which are recognized as well-understood, routine, and conventional activities. The instant claims may provide a solution to challenges to existing techniques, but the solution is abstract idea without significantly; no technology is affected. Even viewed as a whole, the claim does not appear to be patent eligible under 35 USC 101.
At p14 second paragraph of the Remarks, Applicant argued that “At least for the above reasons, Applicant respectfully submits that claim 1 overcomes the rejection under 35 U.S.C. § 101. Amended independent claims 11 and 20 include similar elements as claim 1 and therefore overcome the rejections under 35 U.S.C. § 101 for at least the reasons set forth above, as are all claims depending respectively therefrom. Therefore, Applicant respectfully requests reconsideration and withdrawal of the rejections under 35 U.S.C. § 101.”
Examiner respectfully disagrees, because, as explained, and as set forth in the office action above, claim 1 is still abstract idea without significantly more and does not appear to be patent eligible under 35 USC 101. Similarly, all other claims are abstract idea without significantly more. The 101 abstract idea rejections are maintained.
At p14 last two paragraphs to p15 of the Remarks, Applicant argued with respect to 103 rejections. These arguments are moot upon new grounds of rejections made in the office action above.
Conclusion
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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/ZENGPU WEI/
Examiner, Art Unit 2197
/Thuy Dao/Primary Examiner, Art Unit 2192