🔥The 9th Round of Easy Loan, Earn $40 Reward is in progress❗️ ⏰ Promotion Period: January 15th - Feburary 15th, 2025 👉 Register now and check more details at gate.io/campaigns/358

Looking forward to a lively panel discussion on agentic futures this Thursday at World Summit AI: We do AI different.! There's immense potential in what Agentic AI can help us accomplish, but we're largely still navigating the critical security and safety considerations that will determine how we

Excited to share 🤯 that our LMUnit models with Contextual AI just claimed the top spots on RewardBench2 🥇 How did we manage to rank +5% higher than models like Gemini, Claude 4, and GPT4.1? More in the details below: 🧵 1/11

How are people actually interfacing with all of these models? Besides the typical few shot learning / prompting, the overwhelming answer is RAG (or retrieval augmented generation). 70% of respondents say they’re using RAG in one way or another.

According to The Information, OpenAI is requiring customers to spend at least $10 million for a new consulting-like service using forward deployed engineers (FDEs), around a dozen people hired in recent months, several of whom previously worked at Palantir, where OpenAI engineers

Why Video Failed based on Sergey Levine “Language Models in Plato’s Cave”: sergeylevine.substack.com/p/language-mod…

Seven years ago, I co-led a paper called 𝗛𝗼𝘁𝗽𝗼𝘁𝗤𝗔 that has motivated and facilitated many #AI #Agents research works since. Today, I'm asking that you stop using HotpotQA blindly for agents research in 2025 and beyond. In my new blog post, I revisit the brief history of

Excited to release Contextual-SQL! 🏆#1 local Text-to-SQL system that is currently top 4 (behind API models) on BIRD benchmark! 🌐Fully open-source, runs locally 🔥MIT license 🧵

horrifying bug of the day is finding out the vllm and huggingface produce significantly different logprobs discuss.vllm.ai/t/numerical-di…

Claude Opus 4 is the first to beat the human baseline 🤯 It simply has better analytic skills on pricing. Not sure why more people aren't talking about this (but look for my video on this)

Is your RAG pipeline actually retrieving the right chunks? I just dropped a video walking through a full retrieval analysis for Retrieval-Augmented Generation (RAG) systems — and not just in theory. 🧪 What I cover: • Why retrieval quality matters way more than people think •

I suspect the next few weeks after Grok 4 follows the same pattern as Grok 3 xAI beats everyone to market with the first RonnaFLOP model. The benchmarks show the 10-20% improvement the scaling law suggests. In the coming months, the other labs release their RonnaFLOPs, catch up.

Thanks to Elon Musk and the xAI team for inviting us to share the latest updates to vending bench. Grok 4 jumps to the top of the leaderboard.