DETAILED ACTION
This action is responsive to the preliminary amendment filed 6 January 2025.
Status of the Claims
Claims 21-40 are newly added.
Claims 1-20 have been canceled.
Claims 21-40 are pending.
Priority
Claims 22-26, 29-33, and 36-40 are not entitled to the benefit of prior-filed Application No. 18/349,777.
Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. § 119(e) or under 35 U.S.C. §§ 120, 121, or 365(c) is acknowledged. Applicant has not complied with one or more conditions for receiving the benefit of an earlier filing date under 35 U.S.C. § 120. The later-filed application must be an application for a patent for an invention which is also disclosed in the prior-filed application (nonprovisional application or provisional application). The disclosure of the invention in the prior-filed application and in the later-filed application must be sufficient to comply with the requirements of 35 U.S.C. § 112(a) except for the best mode requirement. See Transco Products, Inc. v. Performance Contracting, Inc., 38 F.3d 551, 32 USPQ2d 1077 (Fed. Cir. 1994).
The disclosure of the prior-filed application fails to provide adequate support or enablement in the manner provided by 35 U.S.C. § 112(a) for one or more claims of this application.
Regarding claim 22, there is a lack of support for at least the following limitations: “determine a runtime status associated with the first machine learning model execution engine; and cause the runtime status associated with the first machine learning model execution engine to be displayed on a graphical user interface.” The prior-filed application does not disclose these limitations for at least the same reasons provided below with respect to the disclosure of the instant application.
Claims 23-25 depend on claim 22, and thus are not supported for at least the reasons given above.
Regarding claim 26, there is a lack of support for at least the following limitations: “transmit the search results set to a remote storage device.” The prior-filed application does not disclose these limitations for at least the same reasons provided below with respect to the disclosure of the instant application.
Regarding claim 27, there is a lack of support for at least the following limitations: “generate, based at least in part on the first search results subset, the second search results subset, and a third search results subset, an updated search results set.” The prior-filed application does not disclose these limitations for at least the same reasons provided below with respect to the disclosure of the instant application.
Claims 29-34 and 36-40 are also not supported for at least the same reasons given above.
Claim Rejections - 35 U.S.C. § 112(a)
The following is a quotation of 35 U.S.C. § 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
Claims 22-27, 29-34, and 36-40 are rejected under 35 U.S.C. § 112(a) as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, at the time the application was filed, had possession of the claimed invention.
Regarding claim 22, there does not appear to be adequate support for the following limitations: “determine a runtime status associated with the first machine learning model execution engine; and cause the runtime status associated with the first machine learning model execution engine to be displayed on a graphical user interface.” The specification does not disclose the above limitation. Rather, the specification merely discloses “a user interface may provide visual display of machine learning model execution run status in real-time.” Specification ¶ 74. There is no mention of a runtime status.
Additionally, the claim defines the invention in functional language specifying a desired result. A claim may lack written description support when the claim defines the invention in functional language specifying a desired result, but the disclosure fails to sufficiently identify how the function is performed or the result is achieved. MPEP § 2163.03(V). Specifically, a software-related claim must adequately describe, in sufficient detail, a computer and algorithm that achieves the claimed functionality. Id. § 2161.01(I). With regards to the claim at issue, the written description fails to provide an algorithm for determining a runtime status.
Claims 23-25 are rejected for substantially the same reason indicated above for claim 22, at least due to their dependence on the claim.
Regarding claim 26, there does not appear to be adequate support for the following limitation: “transmit the search results set to a remote storage device.” The specification does not disclose the above limitation. There is no mention of transmitting a search results set to a remote storage device.
Regarding claim 27, there does not appear to be adequate support for the following limitation: “generate, based at least in part on the first search results subset, the second search results subset, and a third search results subset, an updated search results set.” The specification does not disclose the above limitation. There is no mention of updating a search results set.
Additionally, the claim defines the invention in functional language specifying a desired result. A claim may lack written description support when the claim defines the invention in functional language specifying a desired result, but the disclosure fails to sufficiently identify how the function is performed or the result is achieved. MPEP § 2163.03(V). Specifically, a software-related claim must adequately describe, in sufficient detail, a computer and algorithm that achieves the claimed functionality. Id. § 2161.01(I). With regards to the claim at issue, the written description fails to provide an algorithm for updating search results set.
Claims 29-34 and 36-40 are rejected for substantially the same reasons given above.
Claim Rejections - 35 U.S.C. § 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 21-40 are rejected under 35 U.S.C. § 103 as being unpatentable over Redkar et al., US 2018/0276553 A1, in view of Lawrence et al., US 2055/0222981 A1.
Regarding claim 21, Redkar discloses a system comprising one or more processors and at least one non-transitory computer readable storage media storing instructions that, with the one or more processors, configure the system to:
Receive a search query. Redkar teaches a model management system receiving a user statement (e.g., natural language query). Redkar figs. 2, 4 (step 405), ¶¶ 29, 44-45.
Determine, based at least in part on the search query, a first machine learning model execution engine. Redkar teaches determining an intent type and parameters based on the user statement. Redkar fig. 4 (steps 410, 415), ¶ 46. The model management system may select a machine learning model based on the intent type and parameters. Id. fig. 4 (step 420), ¶ 48.
Generate, based at least in part on the search query and using the first machine learning model execution engine, a first search results subset. Redkar teaches using the selected model to generate results. Redkar fig. 4 (step 425), ¶ 53.
Redkar does not disclose, but Lawrence discloses:
Generate, based at least in part on the first search results subset and a second search results subset, a search results set arranged according to an order based at least in part on a score generated for a first search result of the first search results subset or a second search result of the second search results subset. Lawrence teaches merging two results sets, including ordering the results according to a relevancy score. Lawrence fig. 3 (step 322), ¶ 99. The
It would have been obvious before the effective filing date of the claimed invention to a person with ordinary skill in the art to modify Redkar’s process of querying machine learning models with Lawrence’s process of merging results sets. Such a modification would increase utility by allowing for presentation of more comprehensive search results.
Regarding claim 22, which depends on claim 21, Redkar discloses: determine a runtime status associated with the first machine learning model execution engine; and cause the runtime status associated with the first machine learning model execution engine to be displayed on a graphical user interface. Redkar illustrates a graphical user interface displaying that an ML model is running. Redkar fig. 2.
Regarding claim 23, which depends on claim 22, Redkar discloses wherein the search query is received via the graphical user interface. Redkar fig. 2 (user statement 205), ¶ 29.
Regarding claim 24, which depends on claim 22, Redkar discloses cause a device rendered object to be displayed on the graphical user interface. Redkar fig. 2 (chat interface 200).
Regarding claim 25, which depends on claim 24, Redkar discloses detect an interaction with the device rendered object via the graphical user interface. Redkar fig. 2 (chat interface 200), ¶ 29.
Regarding claim 26, which depends on claim 21, Lawrence discloses transmit the search results set to a remote storage device. Lawrence teaches transmitting the results set to a display processor. Lawrence ¶ 99. The display processor can be contained in memory (i.e., a storage device). Id. ¶ 52.
Regarding claim 27, which depends on claim 21, Lawrence discloses generate, based at least in part on the first search results subset, the second search results subset, and a third search results subset, an updated search results set. Lawrence teaches merging more than two results sets. Lawrence fig. 7, ¶¶ 123, 129.
Claims 28-34 are drawn to methods for performing the functions of the system recited in claims 21-27, respectively. Accordingly, these claims are rejected for substantially the same reasons as indicated in the above rejections of the corresponding claims.
Claims 35-40 are drawn to instructions stored in a medium that implement the functions of the system recited in claims 21-26, respectively. Accordingly, these claims are rejected for substantially the same reasons as indicated in the above rejections of the corresponding claims.
Conclusion
Although particular portions of the prior art may have been cited in support of the rejections, the specified citations are merely representative of the teachings. Other passages and figures in the cited prior art may apply. Accordingly, Applicant should consider the entirety of the cited prior art for potentially teaching all or part of the claims.
The following prior art made of record and not relied upon is considered pertinent to applicant’s disclosure:
Govindarajan et al., US 2018/010167 A1, discloses ranking search results using a machine learning model.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Asher D Kells whose telephone number is (571)270-7729. The examiner can normally be reached Mon. - Fri., 8 a.m. - 4 p.m..
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kieu Vu can be reached at 571-272-4057. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
Asher D. Kells
Primary Examiner
Art Unit 2171
/Asher D Kells/ Primary Examiner, Art Unit 2171
Prosecution Insights