By [Your Name], Senior Journalist and Editor
The design and optimization ofAI models traditionally relies heavily on expert knowledge and manual labor, making the process time-consuming and susceptible to individual biases. However, a groundbreaking new research project,spearheaded by the MetaGPT open-source community, is challenging this paradigm.
SELA: AI-Designed AI Achieves State-of-the-ArtPerformance
SELA, a novel AI design framework, leverages the power of Monte Carlo Tree Search (MCTS) to automatically design and optimize AI models. Developed by researchers from DeepWisdom, UC Berkeley, HKUST, UCSD,SCNU, Stanford, HKBU, Montreal & MILA, SELA has achieved state-of-the-art (SOTA) performance across 20 diverse datasets.
The key innovation of SELA lies in its ability to learnfrom historical design and experimental data, enabling it to iteratively design and refine AI models that surpass previous benchmarks. This self-learning capability distinguishes SELA from existing AI design approaches, which often rely on predefined architectures or manual tuning.
Outperforming OpenAI’s AIDE
SELA’s success isparticularly noteworthy as it outperforms AIDE, the AI design framework currently used by OpenAI. This achievement underscores the potential of AI-driven design to revolutionize the field of AI development.
A Collaborative Effort
The development of SELA is a testament to the collaborative spirit of the open-source community. The projectwas spearheaded by DeepWisdom, a leading AI research and development company, and involved researchers from top universities and research labs worldwide.
Implications for the Future of AI
The open-sourcing of SELA marks a significant milestone in the evolution of AI. By empowering AI to design and optimize itself, SELAopens up exciting possibilities for the future of AI development. It promises to accelerate progress in AI research, reduce the dependence on human expertise, and democratize access to advanced AI technologies.
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