The history of machine learning is of proclaimed barriers dissolving inside the big blob of compute.

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• Machine learning is a shallow field compared with mathematics: even its most important ideas can be explained in a couple of minutes. RGRyan Greenblatt11 Aug 2026similar wording
• Models are enormous only because the internet is bad: most of that capacity does memory work, and a better dataset would need far less of it. AKAndrej Karpathy17 Oct 2025similar wording
• Current AI struggles even to rediscover old laws of physics from data, and when it does, contamination from training is the first suspect. TTTerence Tao14 Jun 2025similar wording
• The knowledge a model soaks up in pre-training is holding it back; what we actually want is the intelligence with the knowledge stripped out. AKAndrej Karpathy17 Oct 2025similar wording
• The dangerous concentration of power in AI comes from who can afford the compute, not from who holds the model weights. ASAravind Srinivas19 Jun 2024similar wording

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