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A deep-dive list of ten major breakthroughs expected from scaling AI compute to ~150 million H100-equivalents by 2028, including advances in mathematics, drug discovery, materials science, biology, fusion, and climate modeling.
A discussion on the sources of recent AI advancements, noting that post-training, fine-tuning, and reinforcement learning have become key, and asking about future directions beyond scaling.