Check out their YouTube channel where they show plenty of interesting features. But just to list some I can think of: - optional reactivity (i.e. you create chain of cells where editing 5th cells in the past causes update down the stream, pretty neat when working with dataframes). Its reactivity is a very cool feature once used to but you might not want it for something like running heavy ML training task so it can be toggled off - you can switch notebook to multi-column notebook mode - notebook is a web app that has sidebar with a lot of menus, there cool sections like Docs, Packages (you can download new packages right away there with uv), plenty of LLM integration with their custom prompts where you can reference dataframes so that it would be able to understand schema, some SQL and other DB integrations as well, cells can even contain SQL instead python code and output query result into python variable - thanks to reactivity it got a lot of interactive elements like sliders buttons text fields or ability to create entire own widgets, there's even mode where all code blocks get hidden and you're left with complete app - you can make web export of notebook that will translate python to WASM and publish it as fully working static page (though publishing something heavy complex like torch probably won't go well), this fits well with previous point as you can basically build simple interface hide all the code and publish it (like imagine matplotlib with couple of sliders) - DataFrames (pandas/polars) displayed as interactive tables where you can filter by columns, scroll through pages of rows etc - notebook stored in a .py format, unlike .ipynb with its json like structure. So code is very Git-friendly but you don't store computation results anymore