We’ve expanded Under The Hood after seeing people’s appreciation of more transparency into government-required content filtering. In addition to showing labels applied to your account and posts in the prior month, Under The Hood now shows if your account or posts had their visibility limited because of required compliance with local law(s). For example, you can see if any of your posts were withheld in a country following a legal demand – and which country. We’re making this Under The Hood update available to all accounts that meet the basic eligibility criteria (10+ posts in prior month, account at least one year old). You can get your report at nitter.net/i/under_the_hood

People want notes fast. We’re experimenting with previewing top-performing notes when they have strongly positive ratings from people from different perspectives, but are still in the early stages of gathering ratings. Now available to a limited group in the US. We’ll shape it with your feedback. Details in the Guide: communitynotes.x.com/guide/e…

If these data centers are so essential to our national security and economy and have such amazing benefits they should prove it by building them in the richest zip codes in America first.

Big thank you @audreyt @idhantgulati @IgorBrigadir @jonathanstray @liyushan27 @vboykis who voluntarily reviewed a draft version of the new X algo open-source repository in advance of yesterday's launch. Their feedback helped improve its value to the public, including: • Proving that the Phoenix scorer could be built and run outside of the company • Identifying missing packages, files, etc. that were referenced, so we could get them into the public release • Highlighting questions people might have, so we could add comments and clarifications. This includes questions like “are the params the real prod ones?” which led us to publish explanations of how we keep them up to date in the repository, and comment timestamps so the public can see when they’re updated • Providing feedback about what info would be most helpful in the new Under the Hood label transparency tool (which shaped what we included) • Recommendations on how to improve the README & documentation, to make the code more understandable • Ideas like publishing the history of the recent “mutuals” ranking change and how it would have shown up if the code had been open-source at that time • and more… It’s been great to have input from people outside the company, and we hope for much more now that it’s all public! Issues and PRs are open in the repo: github.com/xai-org/x-algorit…

Today’s For You release is in the open-source repo. Notable updates: • How ranking weights actually work • A new filter required for Brazil’s 2026 election All the details: github.com/xai-org/x-algorit…

Today’s For You release is in the open-source repo. Notable updates: • How ranking weights actually work • A new filter required for Brazil’s 2026 election All the details: github.com/xai-org/x-algorit…

This is not accurate: "one report erases 468 likes." That's not what the code is doing. The weights are a multiple on your own predicted probability of Liking, Reporting, etc, which is substantially driven by your own behavior. And the baseline probability of a Report is more than 1000x lower. Also: nitter.net/nikitabier/status/2087…

My favorite little nugget in the repo: check out the behind-the-scenes for the recent bidirectional follow boost algo change that lots of you loved! If the boost weight changes again, you'll see it in a future code export. github.com/xai-org/x-algorit…

Big transparency update for the X algo! Would love you all to kick the tires on this: -expect regular code exports as production code changes rather than this just being a one-time batch code dump -check if you're 'shadowbanned' with the new 'under the hood' page to see labels applied to your account (currently in a pilot phase) -runnable training code (would love to see people try this on open source datasets) What else would you want to see??

30-50% more notes are now showing in Japan and many other countries. The increase is driven by the expansion of the Gaussian scoring model to more regions. Details in the open source guide: communitynotes.x.com/guide/e…