🧠264 pages and 1416 references chart the future of Foundation Agents.
Our latest survey dives deep into agents—covering brain-inspired cognition, self-evolution, multi-agents, and AI safety.
Discover the #1 Paper of the Day on Hugging Face👇:
https://t.co/CvtqGKyCYb
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20 Months: 0 → 7 papers (2 ICLR orals) & 40+ institution collabs.
With a clear vision, we're building the open-source foundation for tomorrow's agents.
We also release MGX (https://t.co/AyzVUF9dH3) and commit to open-source its core soon.
Check threads for what we've built!
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🌟 Excited to open-source SELA, a powerful experimentation system integrating MCTS with LLM agents. Across 20 datasets, SELA achieves a 75% win rate against AIDE (OpenAI's top pick in MLE-Bench) and beats traditional AutoML methods developed over years.
💻 Code: https://t.co/dIjSaXnoii
📄 Paper: https://t.co/8j5DLpNr9N
🤖 Can an AI agent design another AI?
🌟 Yes. SELA uses MCTS to design AI, achieving SoTA performance on 20 machine learning datasets. It can learn from past designs and experiments to create better AIs. It's fully open-source.
🚀 Try SELA yourself
📄 Paper: https://t.co/8j5DLpMTkf
💻 Code: https://t.co/pSDAhB4kAJ
Introducing MetaGPT's Data Interpreter: Open Source and Better "Devin".
Data Interpreter has achieved state-of-the-art scores in machine learning, mathematical reasoning, and open-ended tasks, and can analyze stocks, imitate websites, and train models.
Data Interpreter is an autonomous agent that uses notebook, browser, shell, stable diffusion, and any custom tool to complete tasks.
It can debug code by itself, fix failures by itself, and solve a large number of real-life problems by itself.
We open-source our code and provide a wealth of working examples to give everyone access to state-of-the-art AI capabilities.
📝 Paper: https://t.co/VcoeKc6A8S
🔗 Examples: https://t.co/mu3iULDZko
📚 Repo: https://t.co/BMJxhVwzn6
📖 How to use: https://t.co/CviB6jvQ49
#MetaGPT #github #interpreter #opensource