nathan lile
@NathanThinks
ceo/cofounder @ https://SynthLabs.ai hiring in SF 🌁 scaling synthetic reasoning. recurrent rabbit hole victim. nothing great is easy.
Superintelligence isn't about discovering new things; it's about discovering new ways to discover I think our latest work formalizes Meta Chain-of-Thought which we believe lies on the path to ASI When we train models on the problem-solving process itself—rather than the final…
We have a new position paper on "inference time compute" and what we have been working on in the last few months! We present some theory on why it is necessary, how does it work, why we need it and what does it mean for "super" intelligence.
Apple dropping diffusion based Coding LLMs on Hugging Face was not on my bingo
China is winning the race to Type 1 Civilization and we're not even aware it's happening. By 2030, China will have the manufacturing capacity to build an entire U.S. worth of generation from solar and storage alone - every single year. The flow of energy is what drives physical…
Check out our latest pod with @JessePeltan, which is just 3 hrs straight of him dropping bangers like the one below
Really great collaborating with @NathanThinks! Reach out if you're working on synthetic data generation, offline RL, or simulating agentic behavior.
Earlier this year we partnered with SynthLabs (synthlabs.ai), a post-training research lab, to generate a 351 billion token synthetic dataset 10x faster and 80% cheaper. Read more in our case study: sutro.sh/case-studies/s…
you have no idea how hard it is to get an rlhf model to be even “centrist” much less right reactionary. they must have beat this guy up pretty hard
blocked it because of this. No hate on the timeline please!
I’m not big on identities, but I am extremely proud to be American. This is true every day, but especially today—I firmly believe this is the greatest country ever on Earth. The American miracle stands alone in world history. I believe in techno-capitalism. We should encourage…
Xiaomi got 200,000 orders in 3 minutes for the YU7 and I’m not even surprised. The value proposition is just nuts. I’m kinda of bummed because it means a few more years of having to satisfy demand from China before global expansions.
the future is about smart tokens
What if models could learn which problems _deserve_ deep thinking? No labels. Just let the model discover difficulty through its own performance during training. Instead of burning compute 🔥💸 on trivial problems, it allocates 5x more on problems that actually need it ↓
What if models could learn which problems _deserve_ deep thinking? No labels. Just let the model discover difficulty through its own performance during training. Instead of burning compute 🔥💸 on trivial problems, it allocates 5x more on problems that actually need it ↓
Our new method (ALP) monitors solve rates across RL rollouts and applies inverse difficulty penalties during RL training. Result? Models learn an implicit difficulty estimator—allocating 5x more tokens to hard vs easy problems, cutting overall usage by 50% 🧵👇1/10
Check out our latest research on data. We're releasing 24T tokens of richly labelled web data. We found it very useful for our internal data curation efforts. Excited to see what you build using Essential-Web v1.0!
[1/5] 🚀 Meet Essential-Web v1.0, a 24-trillion-token pre-training dataset with rich metadata built to effortlessly curate high-performing datasets across domains and use cases!
congrats @rm_rafailov on your hard-earned acceptance to the USofA as alien of officially extraordinary ability. The alien piece comes as no surprise to your mates of course, but at least the general public now has fair warning and a fighting chance. To celebrate with a fitting…
When we first published our work on this 9 months ago it was rejected for being impractical in realistic cases. Six months later it was rejected for lack of novelty. It’s the way academic publishing goes.
Another generative / inference-time scaling reward modeling paper. It's the direction things are going.
I was going to call this dumb, but former NTSB board member John Goglia just texted me and told me to reply with this instead: The issue raised in The Rehearsal is whether the authority gradient affects copilots' willingness to assert themselves at critical junctures and…
Nathan Fielder’s question has been asked and answered!
Thank you to @synth_labs and friends for making this possible!🥳
This is Plastic. Made with Veo3. Spoilers in the next post. Watch before reading
btw we have ongoing research on this front! we're open-science, pro-publication, and love collaboration. want to push this frontier forward? we're growing our SF team & always open to research partners—reach out, my DMs are open 📩
excellent work by @jaseweston & team—extending our "Generative Reward Models" work with RL (GRPO) to optimize LLM reasoning during judgment scalable (synthetic) evaluation continues to be AI's key bottleneck!
Prompt Theory (Made with Veo 3) What if AI-generated characters refused to believe they were AI-generated?
Platonic GANs >Repeat after me—your embeddings were never yours
excited to finally share on arxiv what we've known for a while now: All Embedding Models Learn The Same Thing embeddings from different models are SO similar that we can map between them based on structure alone. without *any* paired data feels like magic, but it's real:🧵