Google Just Quietly Dropped SELF IMPROVING AI Agent... Kaggle Gold Medals | MLE STAR

🔥 Google’s MLE-STAR Just Changed the Game Google Research just released MLE-STAR, a state-of-the-art machine learning engineering agent that’s racking up gold medals on Kaggle and outperforming previous AI benchmarks — including OpenAI’s own agents. This video breaks down: -What MLE-STAR is and why it matters -How it tackles recursive self-improvement -The Kaggle competitions it's dominating -Why this could be a major step toward automated AI research We’ll also look at: -Key benchmark comparisons with OpenAI's models -Google’s novel scaffolding system and how it boosts performance -Real-world applications of machine learning agents today -This might be the clearest signal yet that AI is learning how to build better versions of itself. 📚 Links & Resources 🔗 Full paper: https://research.google/blog/mle-star-a-state-of-the-art-machine-learning-engineering-agents/ https://arxiv.org/abs/2506.15692 🏆 Kaggle Competitions: https://www.kaggle.com/competitions 💬 What do you think? Are we on the edge of an intelligence explosion? Is recursive self-improvement the next leap? Drop your thoughts in the comments. 👍 Like, Subscribe & Share if you found this valuable! The latest AI News. Learn about LLMs, Gen AI and get ready for the rollout of AGI. Wes Roth covers the latest happenings in the world of OpenAI, Google, Anthropic, NVIDIA and Open Source AI. ______________________________________________ My Links 🔗 ➡️ Twitter: https://x.com/WesRothMoney ➡️ AI Newsletter: https://natural20.beehiiv.com/subscribe Want to work with me? Brand, sponsorship & business inquiries: [email protected] Check out my AI Podcast where me and Dylan interview AI experts: https://www.youtube.com/@Wes-Dylan ______________________________________________ TIMELINE 00:00 - Google’s MLE-STAR 00:15 - Self-Improving AI 00:35 - Automating AI Research 00:58 - Intro to Kaggle 01:52 - Vesuvius Scroll Challenge 03:38 - ML in Real Life 04:20 - MLE-STAR vs OpenAI 05:38 - Benchmark Results 06:30 - Agent Scaffolding 08:17 - Fixing Code Bloat 10:12 - Modular AI Models 12:00 - Recursive Improvement #ai #openai #llm