Nathan Lambert@natolambert · XAI 摘要
当前AI进步常被归因于少数算力雄厚的实验室。推文指出，社会动态、政策、技术扩散（diffusion）等其他因素同样深刻影响AI演进，且此领域存在未被充分重视的影响力机遇。开放科学与开放模型是应对方向之一。文中引用观点指出，通往AGI的预训练工作高度集中于OpenAI、Google、Meta等巨头，算力差距的残酷现实是，AGI关键路径上的问题现需巨大算力门槛。
Something that's squashed in this is that other things impact the evolution of AI than just the few labs with mega compute.
There are many social dynamics， policy， diffusion， etc and there's a substantial unaddressed opportunity for impact here. Open science/models one way.
If you want to work on pretraining-for-AGI, join OpenAI, Google, Meta or the Anthropic/XAI/Cursor supergroup. The bitter truth of the widening compute gap is th...