Lee Johnson

[Lee Johnson @NewEngland96]

@HarperSCarroll 1000x this! There is more to AI than LLMs.

[Lee Johnson @NewEngland96]

@elliotarledge Dang, those Mac Minis really went up in price.

[Charlotte FC @CharlotteFC]

THAT FIRST GOAL FEELING 😤

[Lee Johnson @NewEngland96]

@asymmetricinfo Flew American last week and both of my legs had the same problem. They don’t bother to update their boards or their website. If you’re lucky you get a gate announcement 2 minutes before your supposed boarding time.

[Lee Johnson @NewEngland96]

@MCameron008 I made it about 20 minutes then I switched to the Telemundo broadcast.

[Gillette Stadium @GilletteStadium]

Three months until Ed Sheeran returns to Gillette Stadium! Follow us and repost for your chance to win tickets. ♾️🩷

[Gillette Stadium @GilletteStadium]

Matchday giveaway! Follow us and RT this post for your chance to win this World Cup swag!

[Lee Johnson @NewEngland96]

@_ToddBeane Hope you stayed up to watch this one.

[Georgia Channing @cgeorgiaw]

🤗🤗🤗introducing Hugging Science -- the home of AI for science 🤗🤗🤗

open models and datasets are the powerhouse of science (see the PDB), but finding the models and data you actually need for your breakthrough is hard af

you shouldn't need to scrape arxiv, own your own wetlab, fight a custom HDF5 parser, build a fusion stellarator, and beg for compute before you've trained a single epoch

so we're changing that

we've put all the best science on @huggingface in one place:
- 78GB of genomics data
- 11TB of PDE simulations
- 100M cell profiles
- 9T DNA base pairs
- 13M molecular trajectories
- 400k medical QA pairs

and much more, all open, and all ready for training (+ you can also now filter and search by domain, task, and keyword)

we've put together all the biggest releases from our partners at NASA, Google, OpenAI, Meta FAIR, Arc Institute, Ginkgo, SandboxAQ, Proxima Fusion, NVIDIA, Ai2, OpenADMET, InstaDeep, Future House, Polymathic AI, LeMaterial, Earth Species Project, Merck, and Eve Bio

if you're not sure where you fit in -- work on open challenges for problems that matter: including fusion stellarator design, ADMET, antibody developability, multilingual medicine, catalysis and materials, and scientific reasoning.

we're already changing how science gets done:

a fusion startup needed a benchmark for stellarator plasma confinement that didn't exist. @proximafusion shipped ConStellaration on Hugging Science: a leaderboard, dataset, and eval metrics, all in one place.

a drug discovery team wanted to predict hPXR induction. OpenADMET put up a blind challenge: 11,000+ compounds assayed at Octant, 513 held out, two tracks (pEC50 + structure). Anyone in the world can train and submit.

an antibody team at @Ginkgo released GDPa1, a developability dataset for stability, manufacturability, and immunogenicity prediction, with a live leaderboard scoring every submission.

if you know a problem the ML community should be working on, let us know. make a challenge! this is about putting all the tools for solving science in one place. so we can hillclimb!

→ https://t.co/T4l4r1lDz0

[Lee Johnson @NewEngland96]

@RobertStock6 Ha, was just going to suggest SHAP.

Love the work you’re doing diving into this space!

[Sylvain Filoni @fffiloni]

The safest model format just became everyone’s shared standard.🤗

https://t.co/Gjw8G90K3a

[clem 🤗 @ClementDelangue]

In a world where everyone can build websites, apps and features easily (thank you Cursor, Lovable, Claude and the likes), it will take more for you and your company to differentiate themselves (which is in my opinion the basis for success).

That's why we're seeing more and more people and companies starting to train, optimize and run their own models (rather than outsource this to third parties).

This is the future we want to enable with Hugging Face: empower millions of people to build AI themselves, not just be API users.

Cool new project in this vein from @mishig25: auto-research built on top of @huggingface so that your agents find and push their intermediary checkpoints, datasets, learn from papers and collaborate on the hub: https://t.co/YWCzp5ZIfC

Let's make all AI builders rather than AI users!

[Lee Johnson @NewEngland96]

@JeffPassan We were told that people would be surprised by ABS showing how often the umpires got things right. Instead we’re seeing that the players are much better judges of these close calls, and just how bad some of these umpires are.

[Sergio Parra @SergioParra_]

Los villanos siempre tienen doctorado.

Dr. Doom, el Dr. Octopus, el Dr. Doofenshmirtz, Hannibal Lecter o el Dr. No. Incluso el Dr. Frankenstein o el Dr. Evil.

En cambio, los buenos suelen quedarse en la maestría, como el maestro Yoda, el Maestro Roshi, el Maestro Splinter, el Maestro Miyagi, Shifu o el mismísimo Luke Skywalker.

Los estudios de posgrado corrompen el alma.

[Taiyi Wang @kevinwty]

[1/4] What's the key bottleneck stopping frontier models and agents from solving human-level tasks? Long-horizon task execution. 🧵

We tackle this head-on in our new 50-page paper: "A Subgoal-driven Framework for Improving Long-Horizon LLM Agents" — work I did as a student researcher at Autonomous Agents Team @GoogleDeepMind with Sian Gooding(@SianGooding ), Florian Hartmann, Oriana Riva, and Edward Grefenstette(@egrefen ).

The core insight: use milestones/subgoals as structured hints to guide agents through complex, long-horizon tasks. The arxiv link here: https://t.co/YyNyKcln2H

Example in web navigation: given the task "find and navigate to a filming location in Pennsylvania (not Pittsburgh) on the map", the key milestones are (1) search Wikipedia for the target film, (2) locate and navigate to the place on Maps. Completing these in sequence dramatically boosts success. 🗺️

[Rach @rachpradhan]

I replaced FastAPI's entire HTTP core with Zig.

Same decorator API. Same Pydantic models. 7× faster.

47,832 req/s vs FastAPI's 6,800. 2.09ms p50 latency.

Introducing. TurboAPI.

Here's the story..

[merve @mervenoyann]

just delivered the final_final_final.pdf for the vision language models book 🙌🏻

so tired of the marathon, but super happy my weekends now get hobby projects 🔥 lfg

[merve @mervenoyann]

@athleticKoder it's here but very raw and unedited, final version should come in few months https://t.co/9f8f8xJgfK

[tender @tenderizzation]

please join our performance engineer prayer circle for attention residuals:

🕯
🕯 🕯️
🕯 researcher 🕯️

🕯no make softmax 🕯

🕯 into top-k 🕯
🕯 🕯
🕯