IP Library Granted Patent US 12,450,802
Granted Patent B1
US 12,450,802 · App. 18/465,565 · Granted Oct 21, 2025

Whiteboard content generation using language processing models

Inventors: Vijay Jayaram Rao (Sunnyvale, CA); David Patrick Vronay (Danville, CA)
Assignee: Zoom Communications, Inc.
G06T11/60G06F40/169G06F40/186G06F40/30
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Quick Facts
Patent No.
US 12,450,802
App. No.
18/465,565
Granted
Oct 21, 2025
Kind
B1
Abstract

User-generated graphical elements are added to a whiteboard. A content request is transmitted to a language processing model. The content request includes a textual document describing graphical elements of the whiteboard and a semantic description associated with the whiteboard. The graphical elements of the whiteboard may include the user-generated graphical elements. An updated textual document that includes graphical elements generated by the language processing model is received from the language processing model. The updated textual document is rendered in association with the whiteboard.

Claims (49)

1. A method, comprising:

adding user-generated graphical elements to a whiteboard;

generating a textual document that describes graphical elements of the whiteboard, including the user-generated graphical elements;

transmitting, to a language processing model, a content request comprising the textual document and a semantic description associated with the whiteboard;

receiving, from the language processing model, an updated textual document that includes graphical elements generated by the language processing model; and

rendering the updated textual document on the whiteboard.

2. The method of claim 1 , wherein transmitting the content request to the language processing model comprises:

retrieving the semantic description from a whiteboard template associated with the whiteboard for inclusion in the content request.

3. The method of claim 1 , wherein the content request further comprises graphical structural information specifying an arrangement of graphical elements in a whiteboard template associated with the whiteboard.

4. The method of claim 1 , further comprising:

presenting one or more queries associated with the whiteboard; and

formulating the content request in response to a selection of one of the one or more queries.

5. The method of claim 1 , further comprising:

receiving an open-ended query from a user of the whiteboard; and

formulating the content request based on the open-ended query.

6. The method of claim 1 , wherein the semantic description associated with the whiteboard comprises linguistic information describing an intended use of visual content within a whiteboard template associated with the whiteboard.

7. The method of claim 1 , wherein rendering the updated textual document in association with the whiteboard comprises:

highlighting, on the whiteboard, at least one of the graphical elements generated by the language processing model.

8. The method of claim 1 ,

wherein the updated textual document comprises an annotation to one of the user-generated graphical elements, and

wherein rendering the updated textual document in association with the whiteboard comprises:

highlighting the one of the user-generated graphical elements to indicate the annotation.

9. The method of claim 1 , wherein the user-generated graphical elements comprises at least one of a shape or text and properties defining an appearance of the shape or text.

10. A system, comprising:

one or more memories; and

one or more processors, the one or more processors configured to execute instructions stored in the one or more memories to:

add user-generated graphical elements to a whiteboard;

generate a textual document that describes graphical elements of the whiteboard, including the user-generated graphical elements;

transmit to a language processing model a content request comprising the textual document and a semantic description associated with the whiteboard;

receive, from the language processing model, an updated textual document that includes graphical elements generated by the language processing model; and

render the updated textual document on the whiteboard.

11. The system of claim 10 , wherein the semantic description is associated with a whiteboard template from which the whiteboard is instantiated.

12. The system of claim 10 , wherein the semantic description associated with the whiteboard comprises linguistic information describing an intended use of the whiteboard.

13. The system of claim 10 , wherein the language processing model is cloud-based.

14. The system of claim 10 , wherein the language processing model is integrated into a whiteboard software.

15. The system of claim 10 , wherein the language processing model is further configured to analyze the graphical elements and the semantic description to generate suggested content modifications, and wherein the suggested content modifications are included in the updated textual document.

16. A non-transitory computer readable medium storing instructions operable to cause one or more processors to perform operations comprising:

adding user-generated graphical elements to a whiteboard;

generating a textual document that describes graphical elements of the whiteboard, including the user-generated graphical elements;

transmitting to a language processing model a content request comprising the textual document and a semantic description associated with the whiteboard;

receiving, from the language processing model, an updated textual document that includes graphical elements generated by the language processing model; and

rendering the updated textual document on the whiteboard.

17. The non-transitory computer readable medium of claim 16 , wherein the operations further comprise:

formulating the content request based on an open-ended query received from a user of the whiteboard.

18. The non-transitory computer readable medium of claim 16 , wherein the operations further comprise:

formulating the content request in response to a selection of a user prompt selected from a set of user prompts.

19. The non-transitory computer readable medium of claim 16 , wherein the content request comprises instructions to the language processing model to highlight graphical elements added by the language processing model in the update textual document.

20. The non-transitory computer readable medium of claim 16 , wherein the instructions further comprise:

receiving a command to accept one of graphical elements generated by the language processing model.

Assignments (2)
CHANGE OF NAME Recorded Jan 7, 2025
From: ZOOM VIDEO COMMUNICATIONS, INC.
To: ZOOM COMMUNICATIONS, INC.
Reel/Frame 069839/0593 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 12, 2023
From: RAO, VIJAY JAYARAM; VRONAY, DAVID PATRICK
To: ZOOM VIDEO COMMUNICATIONS, INC.
Reel/Frame 064877/0282 →
References Cited (35)
US 9558467B1 · Simon · 2017 [cited by examiner]
US 10642478B2 · Snyder · 2020 [cited by examiner]
US 10691429B2 · Ananthapur Bache · 2020 [cited by examiner]
US 10782844B2 · Farouki · 2020 [cited by examiner]
US 11030445B2 · Yu · 2021 [cited by examiner]
US 11249627B2 · Mondri · 2022 [cited by examiner]
US 11704009B2 · Blume · 2023 [cited by examiner]
US 20070126755A1 · Zhang · 2007 [cited by examiner]
US 20120169772A1 · Werner · 2012 [cited by examiner]
US 20140365918A1 · Caldwell · 2014 [cited by examiner]
US 20180300302A1 · Holley · 2018 [cited by examiner]
US 20190108493A1 · Nelson · 2019 [cited by examiner]
US 20200320166A1 · Rouaix · 2020 [cited by examiner]
US 20210042662A1 · Pu · 2021 [cited by examiner]
US 20210342785A1 · Mann · 2021 [cited by examiner]
US 20230118500A1 · Shapiro · 2023 [cited by examiner]
US 20230237192A1 · Kahan · 2023 [cited by examiner]
US 20240028350A1 · Sharma · 2024 [cited by examiner]
US 20240129148A1 · Clegg · 2024 [cited by examiner]
US 20240177358A1 · Maurer · 2024 [cited by examiner]
US 20240265193A1 · Schafer · 2024 [cited by examiner]
US 20240311576A1 · Mikutel · 2024 [cited by examiner]
US 20240329802A1 · Katahanas · 2024 [cited by examiner]
US 20250086865A1 · Menges · 2025 [cited by examiner]
WO WO2014200715A1 · 2014 [cited by examiner]
WO WO2015095343A1 · 2015 [cited by examiner]
WO WO2021141688A1 · 2021 [cited by examiner]
WO WO2022104606A1 · 2022 [cited by examiner]
Chen, Qi, et al, “An E-whiteboard Application to Support Early Design-Stage Sketching of UML Diagrams”, Department of Computer Science, University of Auckland, DOI: 10.1109/HCC.2003.1260232, Oct. 31, 2003, pp. 219-226. … [cited by examiner]
Lemma, Remo, et al, “CEL: Touching Software Modeling in Essence”, 2015 IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER), Apr. 8, 2015, pp. 439-448. (Year: 2015). [cited by examiner]
Schafer, Bernhard, et al, “Sketch2Process: End-to-End BPMN Sketch Recognition Based on Neural Networks”, IEEE Transactions on Software Engineering (vol. 49, Issue: 4, 2023, pp. 2621-2641). (Year: 2023). [cited by examiner]
Jeda.ai, World's first Generative AI Online Whiteboard, https://www.jeda.ai/online-whiteboard, retrieved from internet Sep. 12, 2023, 12 pages. [cited by applicant]
YouTube, Jeda.ai all “/ commands” for Help Center, https://www.youtube.com/watch?v=FG4U8QAqLm0&list=TLGG8AfF1ZYW1rcwNDA4MjAyMw&t=21s, Jedaai, Jun. 5, 2023, 2 pages. [cited by applicant]
YouTube, Jeda.ai—Template Analysis for Help Center, https://www.youtube.com/watch?v=2HuJj6mNSKs&list=TLGG-QA0S63cne8wNDA4MjAyMw&t=13s, Jedaai, Jun. 5, 2023, 2 pages. [cited by applicant]
TechTarget, Unified Communications, Whiteboard collaboration app Miro to get generative AI tools, https://www.techtarget.com/searchunifiedcommunications/news/366538361/Whiteboard-collaboration-app-Miro-to-get-generative… [cited by applicant]