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 responsive to communication(s): original application filed on 07/16/2024, said application claims a priority filing date of 07/16/2024.
Claims 1-20 are pending. Claims 1, 10 and 19 are independent.
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 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Bhattacharya et al. (U.S. Patent 12,556,559; hereinafter “Bhat”) in view of Tetreault et al. (U.S. Patent 9,886,955; hereinafter “Tet”).
In regard to independent claims 1, 10 and 19, Bhat teaches a method, comprising: receiving a natural language input for a storage system; providing an input to a generative artificial intelligence (AI) model comprising the natural language input; and receiving, from the generative AI model and based on the input, an output (Bhat, col 95, lines 5-19).
Having input via an interface and having an output via interface is well known in the art. However, Bhat is not explicit on receiving input via natural language interface and the output being includes one or more user interface elements presented via the natural language interface.
Tet teaches a system associated with inputting natural language input and rendering output from generative artificial intelligence (AI) wherein said system teaches receiving input via natural language interface and the output being includes one or more user interface elements presented via the natural language interface (Tet, figure 2; “Note: Chat interface rendered by element 103 being the natural language interface”).
Bhat and Tet are analogous art because they are from same field of endeavor, system associated with inputting natural language input and rendering output from generative artificial intelligence (AI).
Therefore, before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to apply the teaching of Tet, receiving input via natural language interface and output includes one or more user interface elements presented via the natural language interface, to Bhat. Motivation for doing so would have been to perform storage management task using natural language (e.g. chat based or conversation based) interface and input rather than generally menu driven interface and make the system easy to use (Tet, col 9, lines 40-45).
In regard to dependent claims 2, 11 and 20, Bhat as modified by Tet using the same motivation to combine as applied above, teaches presenting the one or more user interface elements (Tet, figure 2; “Note: element 103 includes one or more interface elements”).
In regard to dependent claims 3 and 12, Bhat as modified by Tet using the same motivation to combine as applied above, teaches the one or more user interface elements are presented via the natural language interface (Tet, figure 2; “Note: element 103 includes the natural language interface”).
In regard to dependent claims 4 and 13, Bhat as modified by Tet using the same motivation to combine as applied above, teaches training the generative AI model based on training data comprising one or more annotated user interface elements (Tet, col 11, lines 31-36).
In regard to dependent claims 5 and 14, Bhat as modified by Tet using the same motivation to combine as applied above, teaches the one or more user interface elements are encoded using a markup language (Tet, figure 2; “Note: element 112 means client user interface is markup based”).
In regard to dependent claims 6 and 15, Bhat as modified by Tet using the same motivation to combine as applied above, teaches the storage system is associated with a particular entity and the method further comprises: receiving, from the generative AI model and based on one or more cohorts of the particular entity, another one or more user interface elements; and presenting a user interface comprising the other one or more user interface elements (Tet, col 14, lines 52-60).
In regard to dependent claims 7 and 16, Bhat as modified by Tet using the same motivation to combine as applied above, teaches the user interface corresponds to a particular user interface type and the other one or more user interface elements are based on the particular user interface type (Tet, col 14, lines 52-60; “Note: based on the level of user’s knowledge different user interface type is rendered”).
In regard to dependent claims 8 and 17, Bhat as modified by Tet using the same motivation to combine as applied above, teaches providing the input to the generative AI model further comprises providing, to the generative AI model, the input further comprising one or more contextual attributes associated with the natural language input (Tet, col 13, lines 63-67 and col 14, lines 1-5).
In regard to dependent claims 9 and 18, Bhat as modified by Tet using the same motivation to combine as applied above, teaches providing, via the natural language interface, one or more suggested prompts, wherein the natural language input is selected from the one or more suggested prompts (Tet, col 11, 63-67 and col 12, lines 1-2).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Williams et al. U.S. Publication 2024/0281410 - Teaches a system rending Natural Language Interface in response inputting natural language input.
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/Reza Nabi/
Primary Examiner, Art Unit 2174
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