Based on our record, GitHub seems to be a lot more popular than Distill. While we know about 2071 links to GitHub, we've tracked only 25 mentions of Distill. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Have an github account, if not create one https://github.com. - Source: dev.to / 1 day ago
Git for version control and GitHub for storing remote versions of the repository. - Source: dev.to / 4 days ago
Image Registry Account: Sign up for an account on GitHub, DockerHub, or any other container image registry. You'll use this account to store and manage your container images. - Source: dev.to / 5 days ago
I think it would be more reasonable to judge whether it is promotion according to its content, quality, purpose, instead of domain name. I totally agree one should get flagged if one posts the same product or application for the same use case again and again. But in my situation, they are different tools for different use cases. I don't think this demo would get flagged if it was uploaded and presented in the... - Source: Hacker News / 5 days ago
Steps: - name: Generate summary run: | echo "Pull Request for [${{ github.event.pull_request.title }}](https://github.com/${{ github.repository }}/pull/${{ github.event.pull_request.number }}) has been updated 🎉" >> $GITHUB_STEP_SUMMARY echo "Image tagged **v${{ needs.determine_app_version.outputs.app_version }}** has been built and pushed to the registry." >> $GITHUB_STEP_SUMMARY This will... - Source: dev.to / 6 days ago
Distill was a new take at publishing research/ideas in deep learning in a visual way: https://distill.pub/ I love their articles and while it was hard to sustain, the quality of the ones in their are pretty good. They provide some tips and templates on how to develop such visual storytelling articles. - Source: Hacker News / 8 months ago
Explainable AI is far from early stages. Read into anthropic ai’s work in mechanistic interpretability like toy models of superposition along with the rest of the transformer-circuits papers. Read chris olah’s distill papers. Read neel nanda’s recent work on reverse engineering how language models grok modular addition. Read kevin meng’s work on locating and editing facts inside of gpt. Read openai’s paper on... Source: about 1 year ago
I also wasn't aware of either The Pudding or distill.pub. So thanks for just mentioning those. Source: about 1 year ago
Anything from Setosa [0] is really good. It contains interactive, animated illustrations of several Machine Learning ideas. I _loved_ reading papers from Distill Pub [1] as they contained interactive diagrams. My most favorite one so far is the thread on Differentiable Self-organizing Systems [2]. I liked the lizard example very much as it is interactive, and lizards grow lost organs back. I think this is funny.... - Source: Hacker News / over 1 year ago
If you include deep learning in CS then https://distill.pub/ has a lot to offer in this category. - Source: Hacker News / over 1 year ago
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