Introducing Deepnote AI
Deepnote's AI Copilot is revolutionizing data exploration in notebooks with efficient and contextual code suggestions. As generative AI transforms data analytics, Deepnote believes that notebooks are the ideal platform for AI-assisted exploration.
Notebooks and AI: The Perfect Match
Generative AI is rapidly changing the landscape of data analytics. With the ability to use natural language for analytical code, generate visualizations, and sift through large datasets conversationally, we are witnessing exciting advancements. While it's hard to predict AI's full integration into analytical workflows, one thing is clear: the innovations we've seen so far hint at vast untapped potential.
At Deepnote, we believe that data notebooks will play a crucial role in this transformation. Unlike simple chat interfaces, notebooks provide a dynamic platform for AI assistance, allowing users to stay immersed in their workflow. The modular structure of notebooks and the iterative cycle of inputs and outputs create intuitive touchpoints for engaging AI proactively.
AI Copilot
We are thrilled to introduce the first member of the Deepnote AI family: AI Copilot. This tool is designed for data scientists and analysts who primarily work in Python or other coding languages. AI Copilot offers lightning-fast code suggestions, understanding the full context of your notebook. The more context you provide, the more relevant suggestions you receive, allowing you to focus on the big picture while the AI handles repetitive coding tasks.
To ensure quality, we partnered with Codeium, which delivers speed, performance, and generous context windows. In our Beta program, customers reported a significant boost in productivity, comparable to experiences in classic IDEs using GitHub Copilot, but with the added benefits of collaborative notebooks.
Next in Deepnote AI
Code completion is just the beginning of our journey to transform data work in notebooks through AI. We have many exciting features in development aimed at enhancing productivity for analytics professionals and lowering the barrier to impactful data work for everyone, regardless of technical skills. Upcoming conversational AI features will assist in generating, editing, debugging, and understanding both code and SQL.
Stay tuned for updates as we continue to unveil these exciting developments. The future for notebooks has never looked brighter!
Conclusion
Deepnote AI is set to redefine how we interact with data notebooks, making analytics more accessible and efficient. Ready to experience the future of data exploration?
About the Author
Gabor Szalai is the Head of Product Management at Deepnote. A technology enthusiast and sci-fi fan, he is optimistic about the future of AI. When not tackling challenging problems with his team, he enjoys reading and lifting heavy objects. Follow Gabor on .
