The intersection of AI + crypto is full of hype; but also some real, foundational use cases. Two areas from this @a16zcrypto piece strongly align with what we're building at @SaharaLabsAI: •Provenance for AI IP •User-owned, portable agents My quick take 👇

Excited to release new repo: nanochat! (it's among the most unhinged I've written). Unlike my earlier similar repo nanoGPT which only covered pretraining, nanochat is a minimal, from scratch, full-stack training/inference pipeline of a simple ChatGPT clone in a single,

Learn why these women are choosing Waymo over traditional ride-hailing services and say they feel much safer.

Sean Ren of @SaharaLabsAI and Oleg Golev of @SentientAGI discussing signal vs. noise at the intersection of AI and crypto.

🚀New dataset release: WildChat-4.8M 4.8M real user-ChatGPT conversations collected from our public chatbots: - 122K from reasoning models (o1-preview, o1-mini): represent real uses in the wild and very costly to collect - 2.5M from GPT-4o 🔗 https://t.co/gvBPEo4hqg (1/4)

LLMs can appear to reason well, but a single wrong token can derail the whole output. Our new work shows that token-level memorization is a key cause of failure, especially under distribution shift. Introducing: STIM 🔍🧠 https://t.co/iIdEoVrDPQ 🧵 #NLProc

Excited to be speaking at Berkeley #SBC2025 #BASS2025 about convergence of AI x Web3 and how we could create an open, collaborative economy for an AI-driven future. Our blockchain product lead shares the tech architecture for how we achieve on-chain monetization flows for AI

🔈BASS SBC Speaker Highlight 🔈 @xiangrenNLP Co-Founder @SaharaLabsAI & @FranklinBi General Partner @PanteraCapital

I’ll be at @aclmeeting next week to present this work! 🇦🇹 Excited to meet old friends and make new ones. Let’s catch up if you like thinking more about the future of human-centred NLP, personalization and multi-turn interactions or just wanna get some nice Viennese coffee ☕️

I passed my thesis defense today! 😊 It's been a rewarding journey at @nlp_usc @CSatUSC. Many thanks to @xiangrenNLP @robinomial @swabhz @avestime, and everyone who supported me!

Welcome back @xiangrenNLP, Co-Founder & CEO of @SaharaLabsAI, to #KBW2025: IMPACT! Sean is leading the charge for decentralized AI platforms that empower collaboration and fairness! 📍Sept 23–24 | Walkerhill, Seoul 🎟 https://t.co/zjVaOwyoAG #KBW #KoreaBlockchainWeek #Web3

1+1=3 2+2=5 3+3=? Many language models (e.g., Llama 3 8B, Mistral v0.1 7B) will answer 7. But why? We dig into the model internals, uncover a function induction mechanism, and find that it’s broadly reused when models encounter surprises during in-context learning. 🧵

Data Services Platform (DSP) is LIVE! 🔆 Now anyone, anywhere in the world, can contribute to AI development and earn real rewards for their work. 🔆 $450K+ in $SAHARA + partner rewards available day one! Get started today → https://t.co/mklUe0bfTF #AIforALL

We @Zai_org are thrilled to open-source GLM-4.1V-9B-Thinking, a VLM that can think with long CoTs. SoTA in <10B VLMs, comparable to Qwen-2.5-VL-72B in 18 tasks. One RL to rule them all! Details - Tech report: https://t.co/sxsKy2xP2P - Code: https://t.co/O8WXX7vK0F

In case you missed this — We're going behind the scenes — how it came together, what's live now, and what this unlocks. We shared the vision on AI developer platform and AI marketplace, and talked through what's next for @SaharaLabsAI.

This is what open, user-owned AI infrastructure looks like - not just models, but a full stack where contributors can create, share, and capture value. Proud of the team for getting us here. This is just the beginning.

You can now: •Build your own AI agents •Add your own data or source from our Marketplace •Deploy serverlessly •Register fully on-chain •Set licenses, remix permissions, and earn royalties

Last week was huge at @SaharaLabsAI! We just launched the Agent Builder and AI Marketplace in Open Beta. AI shouldn't just be powerful - it should be buildable, ownable, and composable by anyone. And now anyone - devs and non-devs alike - can go from idea to working agent

I didn't believe when I first saw, but: We trained a prompt stealing model that gets >3x SoTA accuracy. The secret is representing LLM outputs *correctly* 🚲 Demo/blog: https://t.co/qJ6SUFauHo 📄: https://t.co/8UyEYd0s7l 🤖: https://t.co/n4O6bLcoFW 🧑‍💻: https://t.co/L1WLzupAry

from “memory of search engines” —> “memory of foundational models” We continue to be higher order tool users as tools evolve 😄

Here's a recent talk I gave recapping the last 6-12 months of AI progress, why getting perfect models is hard, how labs are likely approaching the next phase of training (for agents), and other interesting tidbits across the reasoning landscape. Topics: 00:00 Introduction & the

Excited to partner with @okx!