DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1, 10-11 and 20 have been amended. Claims 2, 4, 12 and 14 have been canceled. Claims 21-22 have been added. Claims 1, 3, 5-11, 12 and 15-22 have been examined.
Response to Arguments/Amendments
The prior claim objections and rejections under 35 USC § 101 have been withdrawn in view of the claim amendments.
Applicant's arguments filed 9/8/20205 have been fully considered but they are not persuasive.
On p. 11 of the remarks, Applicant argues that the combination of Zhang and Renard fail to teach the amended claim limitations of claims 1 and 11. However, review of the references reveal teaching of the amended limitations in support of the combination of references as cited below. Zhang provides a teaching of managed processes and modifications while Renard teaches supervised and autonomous processes and self-modification. The references combine to teach the claimed limitations.
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, 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, 3, 5-7, 9-11, 13, 15-17 and 19-22 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent 11829280 to Zhang et al. (" Zhang") in view of U.S. Patent Application Publication 20180173999 by Renard et al. ("Renard").
In regard to claim 1, Zhang discloses:
1. A method of application modernization engine executed by one or more processors, the application modernization engine providing an improved process optimization of an enterprise computer system, the method comprising: See Zhang Fig. 5, broadly depicting a method.
receiving, by one or more artificial intelligent agents of the application modernization engine, data of the enterprise computer system and one or more objectives, See Zhang col. 7, lines 43-48, “To start the containerization process, in some embodiments, a user invokes an “inventory” command provided by the software modernization application 114 to identify applications within the user's operating environment 122 that can be containerized (e.g., including legacy software application 124 in the example of FIG. 1).” Also see col. 9, lines 5-8, “the instrumentation agent 130 monitors and generates log data reflecting the operation of the legacy software application 124 during execution.”
Zhang does not expressly disclose:
the one or more artificial intelligent agents comprising at least one of a supervised modernization agent, an assisted modernization agent, and an autonomous modernization agent; and However, this is taught by Renard. See Renard, ¶ 0056, “Depending on the embodiment, the agent may be fully autonomous, semi-supervised or supervised.” It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use Renard’s agent training with Zhang’s modernization application. Using the known technique of agent training to assist with the predictable inventory functionality of Zhang would have been obvious to one of ordinary skill in the art, since one of ordinary skill in the art would recognize that Zhang was ready for improvement to incorporate the trained agent of Zhang.
Zhang also discloses:
processing, by the one or more artificial intelligent agents, the data to implement one or more processes on top of the enterprise computer system to achieve the one or more objectives, Zhang, col. 8, lines 58-65, “In some embodiments, at circle “3A,” the software modernization application 100 further uses an instrumentation agent 130 or other component to profile and monitor execution of the legacy software application 124 (e.g., application profile/monitoring 132) to generate, at circle “3B,” instrumentation data 134 to be used to automatically generate test cases, as described in more detail below.” Also col. 12, lines 20-23, “Assuming the tests run against the containerized application 142 are successful in the test environment 146, the code deployment service 138 then deploys, at circle “7A,” the containerized application 148 …”
the one or more processes being one or more outputs that augment the enterprise computer system with one or more capabilities. Zhang, col. 9, lines 5-11, “In some embodiments, the instrumentation agent 130 monitors and generates log data reflecting the operation of the legacy software application 124 during execution, where the log data records information about requests and responses 202 received and sent by the legacy software application 124 responsive to interactions with client application(s) 200.” Also col. 10, lines 5-8, “In some embodiments, the containerization tools 118 also generates, at circle “4,” one or more test cases 136 based on the instrumentation data 134 obtained by the instrumentation agent 130.”
wherein the supervised modernization agent provides one or more managed processes and modifications … for the one or more outputs that augment the enterprise computer system with the one or more capabilities. See Zhang, col. 7, line 53 – col. 8 line 6, “In some embodiments, responsive to an analyze command, the containerization tools 118 analyze the identified application and generate a file containing analysis results. … In some embodiments, the containerization tools 118 use the information contained in the analysis file to generate a container image and associated artifacts for the application. In some embodiments, the analysis file is editable, and a user can modify containerization configurations contained in the analysis file and elsewhere, where such configurations are used by various containerization processes performed by the software modernization application 114.” Also see col. 10, lines 58-60, “In some embodiments, the software modernization application 114 enables users to modify and supplement the automatically generated test cases 136 as desired.”
Also see Renard, ¶ 0058, “However, prior to providing the response to the end user, the AI agent requests validation of the response by a human (e.g. trainer or validating user), and that input (e.g. approval or rejection of the response) is tracked and used to further train the AI/agent.”
Zhang does not expressly disclose: and the autonomous modernization agent provides one or more independent processes and self-modification. This is taught by Renard. See ¶ 0057, “In one embodiment, the AI/agent is fully autonomous and responds to an end user requests without supervision of a human (e.g. the trainer or validator). In some embodiments, the interactions between the end user (often human) and the AI/agent may be recorded (i.e. dialogue gathering) to be used by the natural training engine for additional training.” Also see ¶ 0063, “In some embodiments, when the AI/agent/bot encounters language it is unfamiliar with (e.g. a new word not in the global model) it triggers the local model engine 334. The local model engine 334 supplements the global model by creating or extending a local model with the new/unfamiliar/unrecognized word.” Note that the rationale for combining the teachings of Renard and Zhang is provided above.
In regard to claim 3, Zhang and Renard also teach:
3. The method of claim 1, wherein the assisted modernization agent provides one or more contemporaneous processes for the one or more outputs that augment the enterprise computer system with the one or more capabilities. See Renard, ¶ 0060, “in one embodiment, the AI/agent will ask a clarifying question, to clarify which area of knowledge the end user is interested in, and, based on the end user's response, determine the area of knowledge with which the end user's request is associated.”
In regard to claim 5, Zhang discloses:
5. The method of claim 1, wherein the one or more objectives are user defined parameters via a natural language statement or description of a business process. Zhang discloses objectives by way of the “inventory” business process. See Zhang, col. 7, lines 43-48, “To start the containerization process, in some embodiments, a user invokes an “inventory” command provided by the software modernization application 114 to identify applications within the user's operating environment 122 that can be containerized (e.g., including legacy software application 124 in the example of FIG. 1).” Note that while not relied upon to meet the language of the claim, Renard further teaches parameters via natural language. See Renard ¶ 0047, “In another example, in one embodiment, the training initiation engine 324 initiates a natural training of an agent responsive to user input received via a keyboard, such as the user typing “I'm going to teach you something.””
In regard to claim 6, Zhang discloses:
6. The method of claim 1, wherein the one or more processes are provided within a containerized application according to the one or more objectives. Zhang, col. 2, lines 4-7, “According to some embodiments, a software modernization application enables a user to identify a legacy application that the user desires to convert into a containerized application.” Also col. 12, lines 22-26, “the code deployment service 138 then deploys, at circle “7A,” the containerized application 148 based on the containerized application artifacts 128 to the computing device(s) 150 of the production environment 152.”
In regard to claim 7, Zhang does not expressly disclose the limitations. However, Renard teaches:
7. The method of claim 1, wherein the application modernization engine provides a fine-tuning of existing models utilized by the one or more artificial intelligent agents to solve a specific problem. See Renard, ¶ 0063, “The local model engine 334 supplements the global model by creating or extending a local model with the new/unfamiliar/unrecognized word.” It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use Renard’s model tuning in order to improve a model as suggested by Renard (see ¶ 0063).
In regard to claim 9, Zhang discloses:
9. The method of claim 1, wherein the application modernization engine provides the improved process optimization of the enterprise computer system through executing the one or more artificial intelligent agents to implement the one or more processes to achieve the one or more objectives. Zhang, Fig. 5, elements 502-508, describing execution of agents to implement the process and achieve the objective. Also col. 9, lines 5-11, “In some embodiments, the instrumentation agent 130 monitors and generates log data reflecting the operation of the legacy software application 124 during execution, where the log data records information about requests and responses 202 received and sent by the legacy software application 124 responsive to interactions with client application(s) 200.”
In regard to claim 10, Zhang discloses:
10. The method of claim 1, wherein the application modernization engine implements the method during a runtime of the enterprise computer system. Zhang, col. 8, lines 61-62, “monitor execution of the legacy software application 124 …”
In regard to claim 11, Zhang discloses:
11. A computer program product stored on a non-transitory computer readable medium, the computer program product comprising program code of an application modernization engine, See Zhang, col. 19 lines 1-3, “In some embodiments, system memory 820 may be one embodiment of a computer-accessible medium configured to store program instructions and data as described above.”
All further limitations of claim 11 have been addressed in the above rejection of claim 1.
In regard to claims 13, 15-17 and 19-20, parent claim 11 is addressed above. All further limitations of claims 13, 15-17 and 19-20 have been addressed in the above rejections of claims 3, 5-7 and 9-10, respectively.
In regard to claim 21, Zhang discloses:
21. The method of claim 1,
wherein the supervised modernization agent provides the one or more managed processes and … See Zhang, col. 12, lines 3-11, “At a high level, in the example of FIG. 1, the software modernization application 114 may create a code deployment pipeline that first deploys a containerized version of the legacy software application 124 to a test or beta environment, performs the test cases to ensure expected operation of the application in the test environment, then deploys the containerized version of the legacy software application 124 to a production environment and again performs the test cases.”
modifications are implemented on top of a legacy systems, user interface or a data source layer to achieve the one or more objectives. Zhang col. 6, lines 48-55, “Existing software applications can be “containerized” by packaging the software application in an appropriate manner and generating other artifacts (e.g., a container image, container file, other configurations) used to enable the application to run in a container engine. Though each container runs isolated processes, multiple containers can share a common operating system, for example, by being launched within the same virtual machine.”
In regard to claim 22, Zhang discloses:
22. The method of claim 1, wherein the autonomous modernization agent augments a data source layer on top of a legacy system or user interface to provide the one or more independent processes and self-modification with the one or more capabilities. See Zhang, col. 10, lines 12-19, “For example, if the legacy software application 124 is a web-based service, the instrumentation data may include log information detailing API requests received by the application (e.g., including request methods and parameters) and the types of responses sent by the legacy application based on processing the requests (e.g., including response parameters or other data).”
Claims 8 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang in view of Renard as applied above, and further in view of U.S. Patent Application Publication 20240031217 by Pahud et al. ("Pahud").
In regard to claim 8, Zhang does not expressly disclose the limitations. However, Pahud teaches:
8. The method of claim 1, wherein an observatory of the application modernization engine monitors performance and efficiency of the one or more artificial intelligent agents. See Pahud, ¶ 0105, “More specifically, within an enterprise's contact center environment, it is beneficial, if not critical, to constantly monitor and evaluate performance of agent instances, both in real-time and over a period of time, to ensure continual and optimal efficiency. This may include monitoring and evaluating agent instance performance and, more specifically, how efficient a particular agent instance (or group of agent instances) is … ” It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use Pahud’s monitoring with Zhang’s agents in order to ensure continual and optimal efficiency as suggested by Pahud (see ¶ 0105).
In regard to claim 18, parent claim 11 is addressed above. All further limitations of claim 18 have been addressed in the above rejection of claim 8.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to James D Rutten whose telephone number is (571)272-3703. The examiner can normally be reached M-F 9:00-5:30 ET.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Li B Zhen can be reached at (571)272-3768. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/James D. Rutten/Primary Examiner, Art Unit 2121
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