This one paper might kill the LLM agent hype.
NVIDIA just published a blueprint for agentic AI powered by Small Language Models.
And it makes a scary amount of sense.
Here’s the full breakdown:
1/N I’m excited to share that our latest @OpenAI experimental reasoning LLM has achieved a longstanding grand challenge in AI: gold medal-level performance on the world’s most prestigious math competition—the International Math Olympiad (IMO).
Today, at Build we showed you how we are building the open agentic web. It is reshaping every layer of the stack, and our goal is to help every dev build apps and agents that empower people and orgs everywhere. Here are 5 big things we announced today:
Today is the start of a new era of natively multimodal AI innovation.
Today, we’re introducing the first Llama 4 models: Llama 4 Scout and Llama 4 Maverick — our most advanced models yet and the best in their class for multimodality.
Llama 4 Scout
• 17B-active-parameter model…
Last month we launched our Anthropic Economic Index, to help track the effect of AI on labor markets and the economy.
Today, we’re releasing the second research report from the Index, and sharing several more datasets based on anonymized Claude usage data.
New paper alert!
We developed the first automated theorem-proving framework for (hyperbolic) PDE solvers: now you can build *formally verified* physics simulations, with provable mathematical and physical correctness properties.
arXiv link and explanation in thread... (1/10)
AI models – especially Claude Sonnet 3.7 – often realize when they’re being evaluated for alignment.
Here’s an example of Claude's reasoning during a sandbagging evaluation, where it learns from documentation that it will not be deployed if it does well on a biology test:
Folks, we have set up a github repo for QwQ, specifically providing evaluation scripts for you to easily test the benchmark performance of reasoning models, and also reproduce our reported results. We provide step-by-step guidance for you to run the evaluation, and we hope this…
Gemma 3 (our open weight LLM) is here and for the first time available on both Google AI Studio and the Gemini API! It is also:
- Natively multimodal
- Long context (128K tokens)
- Can run on a single H100
Our new Agentic leaderboard is now live!💥
I've long wanted a way to quickly know which LLM is best for powering agents.
✅ So we've just built a leaderboard with Albert Villanova! This ranks LLMs powering a smolagents CodeAgent on subsets of various benchmarks.
🏆 GPT-4.5…
We are excited to share our #ICLR2025 paper on LeanAgent: the first lifelong learning agent for formal theorem proving in Lean.
LLMs have been integrated with interactive proof assistants like Lean for theorem proving with 100% accuracy. So far, these LLMs cannot continuously…
Introducing our official LLM.txt Generator API 📃
Concatenate any website into a single text file that can be fed into any LLM.
With our new alpha endpoint you can quickly generate llms.txt and llms-full.txt files for any website.
We’re rolling out AI Mode to Google One AI Premium subscribers today, opt in on Labs. And just like AI Overviews, AI Mode will get better with time and feedback. Get details here: blog.google/products/searc…
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"The future is already here, it’s just not very evenly distributed" (Gibson)
Not an AGI believer, LLMs are good at form not substance
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