🚨 Grok 4.5 tops VulcanBench Eval Suite 3.
90% Pass@1, ahead of Claude 5.1 (89%) and DeepSeek V4-Flash (88%).
The benchmark uses 23 real-world software engineering tasks from merged open-source PRs.
Grok is setting the pace in AI coding. 🤖
AI agents just got a serious RL upgrade.
ClawGym II improved Qwen3-30A3B’s Pass@1 by 9.98 points on OpenClaw and 14.81 on Claude Code.
One model, multiple agent harnesses. 🤖
Agent training is moving beyond the model itself.
DeepSeek is getting seriously close. đź‘€
It trails Opus 4.8 on several benchmarks, but even beats it on Agents’ Last Exam and ZeroBench.
The gap in AI is getting smaller—and the competition is getting 🔥
From looking like a failed landing to looking like a spacecraft that came from the future. 🚀
Starship really is sci-fi in real life.
A normal day at SpaceX in 2030:
What looks like science fiction today could just be another day at the office. 🚀
Maybe the future of “AI Scientists” isn’t fully autonomous agents—it’s better human + AI teams. 🤝đź§
The biggest breakthrough may come from knowing when to ask a human, not trying to eliminate the human from the loop.
A smaller matrix multiplication exponent may sound like a tiny improvement, but at scale, it can have huge implications for AI and scientific computing. 🤯
AlphaEvolve + modern optimization pushing the bound from 2.371339 to <2.371177 is a fascinating result.
Robotics isn’t just a model problem. It’s an infrastructure problem. 🤖
DYNA-2 shows what it takes to train physical AI at scale: massive data, distributed compute, and optimized pipelines.
The real breakthrough?
Every robot interaction becomes data for a better model.
#AI
Construction robotics could be a huge use case for physical AI. 🚜🤖
Excavators work in constantly changing environments, making autonomy extremely difficult.
If AI can master heavy machinery, construction could change dramatically.
AI is entering the real world. 🚀
#AI







