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 1-20 are presented for examination.
Response to Arguments
Applicant’s arguments, filed 01/28/26, with respect to the rejection under 35 USC 102 have been fully considered and are persuasive. The rejection of claims of claims 1-4, 6-11, 13-18 and 20 under 35 USC 102 has been withdrawn. However a new rejection has been made in view of 35 USC 103.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
As per claims 1, 8 and 15:
Step 1: The claims are directed to a network component (machine), method (process), and storage media (manufacture).
Step 2A, Prong 1 (Identify Judicial Exception): Yes. The claim recites displaying elements, receiving selections, determining context, receiving an inquiry, and communicating with an language model to receive a response. These claims are directed to an abstract idea. Specifically, it is a combination of collecting/presenting information (a method of organizing human activity) and using a model to evaluate context and answer a query (a process that can practically be performed in the human mind, i.e., a mental process).
Step 2A, Prong 2 (Practical Application): No. The claims do not integrate the abstract idea into a practical application. The recited hardware components ("network component," "processors," "UI") are invoked at a high level of generality merely as a tool to execute the abstract idea.
Step 2B (Inventive Concept): No. The additional elements (displaying, receiving, communicating) are well-understood, routine, and conventional computer functions. The recitation of an "language model" is broad and generic in the field of AI. Conclusion: Ineligible under § 101.
As per claims 2, 9 and 16:
Step 2A, Prong 1: Yes. The claims add steps for identifying a service and generating an API call to obtain context. This is directed to data collection and information gathering, which are abstract ideas.
Step 2A, Prong 2: No. Gathering data via a service call or API is a standard mechanism of modern computing. It is considered "mere data gathering" necessary to perform the abstract idea, which does not constitute a practical application.
Step 2B: No. Generating a call to a service is a routine and conventional network operation. It does not provide an inventive concept. Conclusion: Ineligible under § 101.
As per claims 3, 10 and 17:
Step 2A, Prong 1: Yes. Receiving a natural language inquiry via a chat box is data collection and communication (abstract idea).
Step 2A, Prong 2: No. Limiting the abstract idea of receiving a query to a specific technological environment (a chat box UI) or a specific format (natural language) does not integrate the idea into a practical application.
Step 2B: No. Chat boxes and natural language inputs are conventional UI paradigms. Conclusion: Ineligible under § 101.
As per claims 4, 11 and 18:
Step 2A, Prong 1: Yes. Substituting "language models" with an "LLM" and an "SLM" does not change the core abstract idea. It remains directed to the mental process of analyzing data to generate a response.
Step 2A, Prong 2: No. Simply reciting two distinct generic models without claiming a specific, technical way they interact to solve a technological problem is merely applying the abstract idea using generic tools.
Step 2B: No. Using multiple models of different sizes is a conventional approach in machine learning. Conclusion: Ineligible under § 101.
As per claims 5, 12, and 19:
Step 2A, Prong 1: Yes. Training an SLM and deciphering context are abstract ideas, mapping to mathematical concepts (the training algorithms) and mental processes (deciphering meaning).
Step 2A, Prong 2: As currently drafted, "training... with specifics" and "deciphering" are claimed functionally rather than technically. Under current USPTO guidance, functional claiming of AI results without specifying the technical implementation does not pass prong 2.
Step 2B: No. The generically claimed steps of "training" and "deciphering" lack the specificity to qualify as significantly more than the abstract idea. Conclusion: Ineligible under § 101.
As per claims 6, 13 and 20:
Step 2A, Prong 1: Yes. Displaying available UI elements and receiving a selection of the context is data collection (abstract idea).
Step 2A, Prong 2: No. This is considered pre-solution activity. Adding steps to display options to gather the necessary data for the core abstract idea does not integrate it into a practical application.
Step 2B: No. Displaying elements and receiving selections are routine and conventional. Conclusion: Ineligible under § 101.
As per claims 7 and 14:
Step 2A, Prong 1: Yes. Capturing a response and sharing it with authorized UIs is directed to the abstract idea of distributing information (a method of organizing human activity).
Step 2A, Prong 2: No. This constitutes insignificant post-solution activity. Furthermore, limiting distribution to "authorized" UIs introduces a secondary abstract concept (rules for access control) rather than a practical application.
Step 2B: No. Transmitting data across a network and enforcing basic authorization rules are conventional computer functions. Conclusion: Ineligible under § 101.
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 1-4, 6-11, 13-18 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Malak et al, US 2025/0094703 and further in view of Dimitrov et al, US 2025/0045796.
Regarding claim 1, Malak teaches a network component comprising one or more processors and one or more computer-readable non-transitory storage media coupled to the one or more processors and including instructions that, when executed by the one or more processors, cause the network component to perform operations (fig. 1) comprising:
Malak lacks or does not expressly disclose displaying a plurality of user interface (UI) elements to a user via a UI:
However Dimitrov teaches disclose displaying a plurality of user interface (UI) elements to a user via a UI (0037 and Fig 1: The content provider device 110 may present or display the additional context terms on the graphical user interface used to enter the set of in-context and out-of-context terms.);
Receiving a selection of UI element from the plurality of UI elements from the user via the UI (0037: The content provider device 110 may detect, identify, or receive selection of one or more of the additional context terms via the graphical user interface for defining the content delivery campaign. For example, the user on the content provider device 110 may click on a subset of the additional context terms to facilitate defining of the audience for the content delivery campaign. Upon selection, the content provider device 110 may provide, send, or transmit the selection of the additional context terms to the placement server 105.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Malia with Dimitrov to include displaying a plurality of elements on a UI in order for a user to make a selection for input, as taught by Dimitrov, paragraph 0037.
Malak, as modified above, further teaches
Receiving, context, a selection of a user interface (UI) element from a UT (Fig. 2, 201 and paragraph 0041: A computing device receives natural language input relating to a table of data organized by columns (step 201). In an implementation, a user is working with a table of data in an environment of an analytics application. The user keys in a request relating to the data in the table in a user interface displayed in the application environment, such as in a chat pane.);
determining a context associated with the UT element (0041: The computing device classifies the request as a request for a visualization using two or more columns of data from the table.);
receiving an inquiry associated with the UT element (0041: Based on classifying the request, the computing device selects a prompt template to generate a prompt for an LLM service which will configure the visualization.);
communicating the inquiry and the context to one or more language models (The computing device generates a prompt tasking an LLM service with selecting columns for a visualization (step 203).); and
receiving, by the one or more language models, a response to the inquiry using the inquiry and the context (0042: In an implementation, the computing device generates a prompt based on the prompt template. The prompt includes fields to be populated by the user input and metadata from the table, such as a list of column names, a list of row names, a table or dataset name (if any), a filename, and the like. The prompt may also include fields for indicating the type of data in each column, such as whether the column contains quantitative data or qualitative data.)
Regarding claim 2, Malak teaches the network component of Claim 1, wherein: receiving the selection of the UI element from the UI comprises receiving an identifier associated with the UI element; and determining the context associated with the UI element comprises: determining a service associated with the identifier; onboarding the service; and generating a call to the service to obtain the context (0019: In the prompt template, each type of visualization has a corresponding visualization object identifier to be included in the JSON object. The prompt template tasks the LLM with returning the visualization object identifier corresponding to the selected visualization type. 0045: The computing device may also populate other attributes of the JSON object based on the columns selected by the LLM service. For example, the JSON object may include an attribute for the unique column identifier akin to a serial number which the computing device uses to reference the columns internally (rather than using the user-created column names). Upon receiving the column selections by name, the computing device may consult a relational database or look-up tool to determine the unique column identifier for the selected columns and populate the appropriate attributes accordingly.).
Regarding claim 3, Malak teaches the network component of Claim 1, the operations further comprising: receiving the inquiry from a chat box of the UT, wherein the inquiry comprises a question in the form of a natural language; and associating the inquiry with the context (0017: a user working with dataset or table of data in a user interface of a data analytics application enables a chat pane to open. In the chat pane, the user submits natural language input relating to data in the chat pane. The chat pane interfaces with a prompt engine of the analytics application which classifies the user input as a request to create a visualization, to edit an existing visualization, to receive assistance with using the application, or some other type of input.).
Regarding claim 4, Malak teaches the network component of Claim 1, wherein the one or more language models comprise a large language model (LLM) and a small language model (SLM) (0005: The application generates a prompt for a large language model (LLM) service which includes the names of the table columns.).
Regarding claim 6, Malak teaches the network component of Claim 1, the operations further comprising: displaying one or more available UI elements to the user via the UI; and receiving, in response to displaying the one or more available UI elements to the user via the UI, the selection of the context (0027: for what the user wants to display. Rather, using a chat interface, a user can simply input in natural language form what it is that the user wants to capture from the data, however imprecise the language or uncertain the intent. Once a visualization is created, the user can edit the visualization in a similar manner, submitting a natural language request which is sent to the LLM to identify modifications to the JSON object. 0036: the prompt template includes an instruction tasking LLM service 121 with selecting data to display in a visualization responsive to user input 114.).
Regarding claim 7, Malak teaches the network component of Claim 1, the operations further comprising: capturing the response to the inquiry; and sharing the response to the inquiry with one or more other UIs that are authorized to display the context and response to the inquiry (0048: the visualization engine may generate a blank visualization based on the object identifier, then configure the visualization according to other attributes, such as drawing data from the selected columns of the table, modifying style elements of the table, and so on. With a visualization complete, the computing device displays the visualization in the application environment on the computing device.).
As per claims 8-11, 13-14, and 15-18, 20, this is a method and media version of the claimed component discussed above in claims 1-4, 6-7 wherein all claimed limitations have also been addressed and/or cited as set forth above.
Claims 5, 12 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Malak as applied to claims 1-4, 6-11, 13-18 and 20 above, and further in view of Braunstein et al, US 2020/0184148
Regarding claims 5, 12 and 19, Malak lacks or fails to expressly disclose APIs. However, Braunstein teaches training the SLM with specifics of application programming interfaces (APIs) and their associated rules; and deciphering, by the SLM, the context to assist the one or more language models with generating the response to the inquiry (0007: The SLM approach aims to estimate the likelihood that sequences of words appear in the language (i.e., estimate the probability distributions over all possible sentences in the language). The probability estimation of different words and word sequences can highlight patterns of behavior of the communications in the network, or of communications via channels standardized by an API, in the same manner as the technique might estimate the likelihood that a pattern of words recurs in a novel. Applying patterns detected may lead to generation of rules which may describe the normal behavior of the network.). It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Malak with Braunstein to include APIs in order to utilize communication standards, as taught by Braunstein, paragraph 0007.
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 AUBREY H WYSZYNSKI whose telephone number is (571)272-8155. The examiner can normally be reached M-F 9-5.
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/AUBREY H WYSZYNSKI/Primary Examiner, Art Unit 2434
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