Where? I have tried Bluesky a couple of times last year and it's minuscule compared to X. I just need to create a new account on X, then follow some popular account like ICML, ICLR, arXiv.stats, arXiv.ML and I'll get more research news than I could ever consume from the feed, the recommendation from related accounts often provide all the big releases from big labs, no following needed.

I largely agree with you on the relative scales.

But I definitely notice a pretty significant portion of the academic CS community are beginning to materialize on bluesky. You can probably start with Nathan Lambert (natolambert) or Jeremy Howard's bsky and branch out from there. (They tend to be schelling points for open AI networks, simonw also, swyx would be if he started using bsky also.)

Paper skygest curates people you follow into a feed of posts mentioning papers if you want to cut down on other noise. (https://bsky.app/profile/paper-feed.bsky.social)

You can browse starter packs (https://github.com/stevendborrelli/bluesky-tech-starter-pack...) to get an idea of where the communities are forming. For instance, the macOS/iOS people I used to follow on twitter are posting more on bluesky. If steipete started posting there, that would be half my twitter/x feed anyway..

Where? Twitter is increasingly useless/hype only in that regard.

On bsky, like a few AI/tech things (simonw, dan abramov, jeff dean, ethan mollick etc, and the people in their replies). Then use discover and this 'for you' feed - https://bsky.app/profile/spacecowboy17.bsky.social to find additional things to like. Then follow the people who post what you're liking. (spacecowboy17 is running a feed that looks at your likes and then populates the feed with people who have a similar like cluster to you). Consider adding this anti-ai-ai labeler if you're put off by some people - https://bsky.app/profile/antiantiai.bsky.social

I think the bsky ML/tech content is relatively thin and people are overstating its volume. But it does exist, and some of it is not posted elsewhere. (Or the posters aren't at least.)

I don't know how your twitter is tuned, but I'm overwhelmed by the volume of meaningful twitter ML info. If you turn on swipe to 'not interested in this post' and bookmark/like/click even a few posts (and maybe follow a few AI people), it really becomes a feed of just ML info very quickly. And it's pretty easy to get the engagement bait filtered out this way too.

Thank you for that, will try.

There is still a lot of ML in my Twitter feed, it's just over the years it morphed to the fad of the month (currently Claude Code mostly). And I try to follow new interesting accounts all the time but still the quality seems to be going down.