Show HN: Adding Mistral Codestral and GPT-4o to Jupyter Notebooks

1

Deepnote

Thank you for the list - I think I've come across all of these in my research! I'll try highlight the differences for each. - https://noteable.io/ - as you say, it doesn't exist anymore - https://deepnote.com - I actually mentioned this in the post but in my experience, the UX and features far behind what we've built already. I'd love to hear from anyone who's tried jupyter-ai to give us a shot and let me know what we're missing! The plus side of jupyter-ai is of course that it supports way more models and the codebase is a lot more hackable than what we've built. - https://colab.google/ - closed-source, similar challenges as with Deepnote. Another big challenge is that if you want to use Colab as a company, AFAICT, you need use their enterprise version (so that you can have native data collectors, support guarantees etc) and that only works with GCP so if you're an AWS shop, this might be a deal-breaker. - https://cocalc.com - hadn't used it so far but congrats on a great project! Will check it out. Didn't look in detail but first impressions makes it look like a fairly different interface from Jupyter. One of our goals was to go to where the users already are - that meant Jupyter. So that's definitely a major difference. - VSCode - as I've mentioned elsewhere, we're targeting a more of an analytics usecase with the features we're building. VSCode has AI features of course! But we'll look quite different once we build more items on the roadmap :).

#Data Science And Machine Learning #Data Science Tools #Data Science Notebooks 34 social mentions

2

CoCalc

Thank you for the list - I think I've come across all of these in my research! I'll try highlight the differences for each. - https://noteable.io/ - as you say, it doesn't exist anymore - https://deepnote.com - I actually mentioned this in the post but in my experience, the UX and features far behind what we've built already. I'd love to hear from anyone who's tried jupyter-ai to give us a shot and let me know what we're missing! The plus side of jupyter-ai is of course that it supports way more models and the codebase is a lot more hackable than what we've built. - https://colab.google/ - closed-source, similar challenges as with Deepnote. Another big challenge is that if you want to use Colab as a company, AFAICT, you need use their enterprise version (so that you can have native data collectors, support guarantees etc) and that only works with GCP so if you're an AWS shop, this might be a deal-breaker. - https://cocalc.com - hadn't used it so far but congrats on a great project! Will check it out. Didn't look in detail but first impressions makes it look like a fairly different interface from Jupyter. One of our goals was to go to where the users already are - that meant Jupyter. So that's definitely a major difference. - VSCode - as I've mentioned elsewhere, we're targeting a more of an analytics usecase with the features we're building. VSCode has AI features of course! But we'll look quite different once we build more items on the roadmap :).

#Mathematics #Python IDE #LaTeX 31 social mentions

3

Codeium

Codeium(https://codeium.com/) already supports this, along with VSCode jupyter notebook extensions. It has 400k downloads on the VSCode extension store. don't really see the point of this when codeium already exists..

#Developer Tools #AI #Coding 45 social mentions

4

Livebook

#Technical Computing #Numerical Computation #Text Editors 7 social mentions

5

Hacker News Search

Https://hn.algolia.com/?dateRange=all&page=0&prefix=false&query=%22system%20prompt%22&sort=byDate&type=story.

#Search Engine #Social Networks #Blogging 2360 social mentions

6

Hex

#Application And Data #Libraries #Data Science Tools 9 social mentions