According to @AndrewYNg, the Jupyter team launched Jupyter AI to embed chat-based code generation and debugging directly inside Jupyter notebook cells, with the debut showcased at JupyterCon this week, source: Andrew Ng on X. According to @AndrewYNg, Jupyter AI is built specifically for notebooks and supports dragging cells to chat, generating cells from chat, and attaching API docs or other context so the LLM writes more accurate code, source: Andrew Ng on X. According to @AndrewYNg, Jupyter AI is integrated into the DeepLearning.AI platform via a free short course co‑taught by Andrew Ng and Jupyter co‑founder Brian Granger, and as an open‑source project it can also be installed and run locally after the course, source: Andrew Ng on X; DeepLearning.AI short course page. According to @AndrewYNg, the announcement includes no mention of cryptocurrencies, tokens, pricing, or monetization details, so no direct crypto or token catalyst was disclosed in this release, source: Andrew Ng on X.

According to @DeepLearningAI, a new course titled Jupyter AI: AI Coding in Notebooks teaches users to use Jupyter AI’s chat interface to generate, debug, and explain code directly in notebooks, build a book research assistant using the Open Library API, and create a stock-market analysis workflow that visualizes and interprets real data; source: @DeepLearningAI on X, https://twitter.com/DeepLearningAI/status/1985399396318539928. It also confirms the instructors are Andrew Ng and Brian Granger, co-founder of Project Jupyter, and provides an enrollment link at bit.ly/4qDAGjT; source: @DeepLearningAI on X, https://twitter.com/DeepLearningAI/status/1985399396318539928.