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 .
Response to Arguments
Applicant’s arguments with respect to claims 1-10, 12-21 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-10, 12-21 are rejected under 35 U.S.C. 103 as being unpatentable over Batina et al, US Patent Pub. 20240289361 A1, in view of Pringle, US Patent Pub. 20240031367 A1, in view of Hardee et al, US Patent Pub. 20220161145 A1.
Re Claim 1, Batina et al discloses a visual collaboration system comprising: a processor (para 0024: processor); and a machine-readable medium storing executable instructions that, when executed (paras 0072, 0111: software program code is stored on a memory and executed by a processor), cause the processor to perform operations comprising: providing, via a collaboration template generator module, a collaboration template including a brainstorming canvas to a display device, wherein the collaboration template includes an artificial intelligence (AI) chat interface to receive a natural language command from at least one of the plurality of participants (para 0042: image canvas and chatbot AI interface where user asks questions and the AI responses with prompts for user to in return respond to said prompts; wherein chatbot interface selections are being simultaneously updated on the image canvas); receiving, via a receiver module, the natural language command from the participant (paras 0042, 0044: natural language processing for user queries); combining, via an AI request generator module, the natural language command with context prompts generated by a context prompt generator system to form a combined AI request and transmitting the combined AI request to an AI system (paras 0029, 0036-0038: context data, whereby historical context implies context is stored for later utilization; para 0042: user query transmitted via AI chatbot interface to AI, wherein AI responds with a prompt to user to select further options; para 0044: natural language processing is how user queries are processed); in response to the combined AI request transmitted to the AI system, receiving an AI response, via an AI response receiver module, from the AI system (para 0042: user query transmitted via AI chatbot interface to AI, wherein AI responds with a prompt to user to select further options; para 0044: natural language processing is how user queries are processed; para 0050: display); and in response to receiving the AI response from the AI system, instructing at least one of the display devices of the participants, via an AI response transmitter module, to display the AI response on the brainstorming canvas of the template on the display device of the participant (para 0042: image canvas and chatbot AI interface where user asks questions and the AI responses with prompts for user to in return respond to said prompts; wherein chatbot interface selections are being simultaneously updated on the image canvas; para 0050: display); but fails to disclose a plurality of participants coupled to the system; the context prompts further including template note location information that provides a location of notes already on the collaboration template, AI response that includes a recommendation for placement of a new note on the collaboration template and providing the recommendation to at least one of the plurality of participants on wherein the new note is to be posted on the collaboration template in a logical location relative to the location of the notes already on the collaboration template. However, Pringle discloses a system that teaches the concept of pop-up windows that pop up within the AI chat interface (Pringle, para 0108: pop-up windows accessible via user-adaptive GUI (e.g. chat bots, messaging module etc; para 0120: pop-up windows include actionable notices, alerts, icons, links to suggested services and/or resources, messages from enhanced AI driven chat-bot discussions (e.g. with links to begin interactions (user interface UI); wherein the messages are read as notes); wherein the pop-up window chat-bot discussions enables user interactions that include predetermined types of interactions (Pringle, para 0041: predetermined types of interactions), including the ability to intelligently via AI, relatively locate the user-adaptive GUI and its subsequent pop-up window chat bots in a relative location on the user interface (UI) (Pringle, paras 0066, 0082); whereby a plurality of participants can engage with the AI interface system (Pringle, para 0108: plurality of users; para 0106: plurality of users). It would have been obvious to modify the Batina et al system such that it enables a plurality of users to engage with the AI interface along with the ability for the AI interface to generate pop-up messages/notes with suggestions with the ability for a user to select the message and initiate a subsequent chat-bot/user interactions to accept further user queries to the AI system as taught in Pringle for the purpose of enabling multiple users to utilize the system simultaneously while also enabling a dynamic feedback system.
Hardee et al discloses a system that teaches the concept of modifying user interface (UI) of the a display wherein AI is used to analyze user preferences such as size UI locations on a display, duration of display etc, for various user interface elements such as avatars, textual contents (pop-up windows with suggestions) (Hardee et al, para 0042: machine learning (AI) techniques used to recognize user patterns of UI arrangements including size and locations etc) and make recommendations to the user/viewer of what size, location etc preferences they will like for their various UIs on their display (Hardee et al, paras 0044, 0081) with the user/viewer selecting their preference from said recommendations (Hardee et al, paras 0047, 0084: rules updated with feedback from the user/viewer). It would have been obvious to modify the Pringle system as used to modify Batina et al, such that the UI of Pringle is analyzed by machine learning (AI), make recommendations to its users/participants/viewers as to the sizes and locations of the pop-up windows with the users/participants/viewers being able to provide feedback of their preference based on said recommendations as taught in Hardee et al for the purpose of giving users/participants/viewers control as to where they want the pop-windows located with the help of machine learning (AI) to optimize the locations and sizes of the pop window.
Re Claim 2, the combined teachings of Batina et al, Pringle and Hardee et al disclose the system of claim 1, wherein the AI chat interface includes a dialog box to allow the plurality of participants to submit the natural language command via a keyboard device (Batina et al, para 0074: keyboard used for user query entry into AI chatbox interface; Pringle, para 0108: plurality of users; para 0106: plurality of users).
Re Claim 3, the combined teachings of Batina et al, Pringle and Hardee et al disclose the system of claim 1, wherein the AI chat interface includes a microphone to allow the plurality of participants to enter the natural language command verbally (Batina et al, para 0074: microphone used for user query entry into AI chatbox interface; Pringle, para 0108: plurality of users; para 0106: plurality of users).
Re Claim 4, the combined teachings of Batina et al, Pringle and Hardee et al disclose the system of claim 1, wherein the context prompt generator system provides context to the natural language command sent to the AI system based on context information stored in a context database (Batina et al, paras 0029, 0036-0038: context data, whereby historical context implies context is stored for later utilization; para 0042: user query transmitted via AI chatbot interface to AI, wherein AI responds with a prompt to user to select further options; para 0044: natural language processing is how user queries are processed).
Re Claim 5, the combined teachings of Batina et al, Pringle and Hardee et al disclose the system of claim 4, wherein the context prompt generator system receives context information that includes information regarding previous events pertaining to the product or service which the natural language command pertains to (Batina et al, para 0036: context of e-commerce products; wherein information regarding previous events pertaining to the product or service is selected from the Markush claim language).
Re Claim 6, the combined teachings of Batina et al, Pringle and Hardee et al disclose the system of claim 1, wherein the AI system is a large language model (LLM) (Batina et al, paras 0042, 0044: the AI is LLM).
Re Claim 7, the combined teachings of Batina et al, Pringle and Hardee et al disclose the system of claim 1, wherein the response from the AI system includes at least one of a text-based response and a visual response (Batina et al, paras 0038, 0041: AI chat response could also be text responses; paras 0042-0044: chat AI response to user query includes images for user to carry out further selection; wherein visual response is selected from the Markush language).
Re Claim 8, the combined teachings of Batina et al, Pringle and Hardee et al disclose the system of claim 1, wherein the response from the AI system generates the notes to display on the display device of one or more of the plurality of participants (Batina et al, paras 0038, 0041: AI chat response could also be text responses; paras 0042-0044: chat AI response to user query includes images for user to carry out further selection).
Re Claim 9, the combined teachings of Batina et al, Pringle and Hardee et al disclose the system of claim 8, wherein the notes include text-based replies from the AI system (Batina et al, paras 0038, 0041: AI chat response could also be text responses; paras 0042-0044: chat AI response to user query includes images for user to carry out further selection).
Re Claim 10, the combined teachings of Batina et al, Pringle and Hardee et al disclose the system of claim 8, wherein the notes include image-based replies from the AI system (Batina et al, paras 0038, 0041: AI chat response could also be text responses; paras 0042-0044: chat AI response to user query includes images for user to carry out further selection).
Re Claim 12, the combined teachings of Batina et al, Pringle and Hardee et al disclose the system of claim 1, wherein an on-canvas UI is activated by clicking on one the notes generated by the AI system response (Pringle, para 0108: pop-up windows accessible via user-adaptive GUI (e.g. chat bots, messaging module etc; para 0120: pop-up windows include actionable notices, alerts, icons, links to suggested services and/or resources, messages from enhanced AI driven chat-bot discussions (e.g. with links to begin interactions (user interface UI); wherein the messages are read as notes).
Re Claim 13, the combined teachings of Batina et al, Pringle and Hardee et al disclose the system of claim 1, but fail to explicitly disclose wherein pre-defined instructions include instructions to suggest additional similar ideas beyond an idea on the notes, which the idea has been suggested by the AI system in the AI response to the natural language commands. It would have been obvious to modify Pringle et al as used to modify Batina et al such that its predetermined interactions carries out searches based on outputs from AI model, whereby predetermined interactions could naturally include search outputs not included by AI model as AI model is a guide for search engine (Batina et al, paras 0080-0083) for the purpose of providing the system with a more robust search capability.
Re Claim 14, the combined teachings of Batina et al, Pringle and Hardee et al disclose the system of claim 1, wherein natural language commands made by one of the plurality of participants are private to the one of the plurality of participants providing the natural language commands (Pringle, paras 0046, 0095: 1-on-1 and multi-party secure chat implies that the system could be made private to a particular number of participants and/or include all participants; wherein secure chat can be initiated by the user initiating the secure chat).
Re Claim 15, the combined teachings of Batina et al, Pringle and Hardee et al disclose the system of claim 1, wherein the executable instructions, when executed, cause the processor to perform a further operation comprising allowing a participant who generated the natural language command to determine which other participants will receive the AI response to the natural language command (Pringle, paras 0046, 0095: 1-on-1 and multi-party secure chat implies that the system could be made private to a particular number of participants and/or include all participants; wherein secure chat can be initiated by the user initiating the secure chat).
Claim 16 has been analyzed and rejected according to claims 1, 7-11.
Re Claim 17, the combined teachings of Batina et al, Pringle and Hardee et al disclose the interface of claim 16, further comprising a theme area, separate from the brainstorming area, to display groups of the notes displayed in the brainstorming area (Pringle, para 0115: second region includes interactive notices/messages which include further interactive dialogue boxes for user interaction).
Re Claim 18, the combined teachings of Batina et al, Pringle and Hardee et al disclose the interface of claim 16, further comprising a meeting chat interface, separate from the brainstorming area, to allow communication between the user and other users of the visual collaboration application separate from collaboration using the brainstorming area (Pringle, para 0108: AI chat interface for the users).
Claim 19 has been analyzed and rejected according to claim 1.
Claim 20 has been analyzed and rejected according to claim 5.
Claim 21 has been analyzed and rejected according to claim 12.
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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/GEORGE C MONIKANG/Primary Examiner, Art Unit 2692 3/27/2026