Oxford Researcher: Why Do Large Models Become Increasingly "Ineffective" in Deeper Layers? скачать в хорошем качестве

Oxford Researcher: Why Do Large Models Become Increasingly "Ineffective" in Deeper Layers?

【Open AGI Forum】From 12 Rejections to Oxford Researcher: How a '93-Born Scholar cracked the Academic Code. This episode's core theme: The LLM Depth Bottleneck—why the bottom 30% of your large model's layers are "slacking off." From training dynamics to representation collapse, from Mix-of-Depths to the mathematical limits of Scaling Law, a methodological discourse on efficiency and essence. 🔬 Key Highlights: Why is your 4090 running idle?—A technical deconstruction of the LLM depth bottleneck European AI lagging behind China and the US: Academic tradition vs. mobilizing resources for grand endeavors Diffusion, MoE, Mamba: Which directions are overhyped/undervalued? "Research is easy, life is hard": The research philosophy of a 28-year-old PI A decade-long observation of AI development across the UK, France, and the Netherlands