Published by: Shanghai Jiao Tong University, SII, Taptap, GAIR
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Key Take Aways
The article introduces ASI-ARCH, an autonomous system capable of conducting scientific research in neural architecture discovery, representing a significant step towards AI-driven model innovation.
The system moves beyond traditional Neural Architecture Search (NAS), shifting from automated optimisation to genuine automated innovation through hypothesising, implementing, and empirically validating novel architectures.
ASI-ARCH autonomously conducted 1,773 experiments over 20,000 GPU hours, leading to the discovery of 106 state-of-the-art linear attention architectures.
A notable “AlphaGo” style moment is highlighted, where the system's unexpected architectural breakthroughs reveal emergent design principles surpassing human intuition.
The authors establish a first empirical scaling law for scientific discovery itself, demonstrating that research breakthroughs can be sc...
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