`For you` is flooded with questions feigning ignorance, posts about determinism, and self-introductions—all look the same, all boring
As a former dancer, I’ve always dreamed of performing a dance like this! Respect to all dancers!
Forecast called for a STORM and GENER8ION & Yung Lean delivered at the #VMAs! ⛈️⛈️
Slay, some ideas I have now
I will say that giving up strings is more of a tradeoff in flexibility than intelligence, but a very big one. Majority of LLM use cases are very string-centric (for now 😈)
We keep a small but expanding set of use cases on our docs: docs.typesafe.ai/concepts/us…
Congrats 🤗
Super happy to share our intention to join forces with NVIDIA in a $12,930,300,000 acquisition 💛💚
10 years after starting Hugging Face, open-source AI is at an inflection point. Thanks to the community, we’ve shown that it can be a complement, and even an alternative, to closed-source APIs. But for it to happen at larger scale, it needs more compute, more support, more collaboration and more visibility. That’s why we went to talk to Jensen, who offered to do exactly that with us.
In addition to doubling down on NVIDIA’s massive contributions to open-source AI (I called them the “King of American open-source AI” earlier this year), they’ve committed to strongly supporting Hugging Face and our mission while keeping the platform open, independent and compute agnostic. The founders and the team are all staying to keep pushing this mission forward.
Together, we think we can make open source the default way to build AI, with the goal of empowering 100 million AI builders to own their intelligence rather than rent it.
Excited about the next 10 years! 🤗🤗🤗
🤔
Not a critique of the paper, but isn't inductive bias/ regularization the reason for *every* form of generalization?
Neural nets have a number of inductive biases due to the architecture as well as explicit or implicit regularizations.
The mere fact that weight magnitudes are limited (e.g. through regularization) makes the input-output function Lipschitz, which is the property you want to produce a smooth score function.
😵💫
SECURITY ADVISORY — TanStack npm packages
A supply-chain compromise affecting 42 @tanstack/* packages (84 versions total) was published to npm earlier today at approximately 19:20 and 19:26 UTC. Two malicious versions per package.
Status: ACTIVE — packages are deprecated, npm security engaged, publish path being shut down.
Severity: HIGH — payload exfiltrates AWS, GCP, Kubernetes, and Vault credentials, GitHub tokens, .npmrc contents, and SSH keys.
If you installed any @tanstack/* package between 19:20 and 19:30 UTC today, treat the host as potentially compromised:
• Rotate cloud, GitHub, and SSH credentials immediately
• Audit cloud audit logs for the last several hours
• Pin to a prior known-good version and reinstall from a clean lockfile
Detection — the malicious manifest contains:
"optionalDependencies": {
"@tanstack/setup": "github:tanstack/router#79ac49ee..."
}
Any version with this entry is compromised. The payload is delivered via a git-resolved optionalDependency whose prepare script runs router_init.js (~2.3 MB, smuggled into each tarball at the package root).
Unpublish is blocked by npm policy for most affected packages due to existing third-party dependents. All 84 versions are being deprecated with a SECURITY warning, and npm security has been engaged to pull tarballs at the registry level.
Full technical breakdown, complete package and version list, and rolling status updates:
github.com/TanStack/router/i…
Credit to the security researcher for responsible disclosure.
Vila retweeted
Superheavy's evolution has been quite something to watch over the years! 😍
📸: @BocaChicaGal | @NASASpaceflight
😱
@npmjs @GHSecurityLab there is an active supply chain attack on [email protected] which pulls in a malicious package published today - [email protected] - someone took over a maintainer account for Axios
Vila retweeted
Introducing TurboQuant: Our new compression algorithm that reduces LLM key-value cache memory by at least 6x and delivers up to 8x speedup, all with zero accuracy loss, redefining AI efficiency. Read the blog to learn how it achieves these results: goo.gle/4bsq2qI
It’s not about having ideas; it’s about making them happen. Create toys, but make sure they aren’t just clones. Rebuild if you must, but don't just do the same thing twice.
