Alex Tamkin on Self-Supervised Learning and Large Language Models
The Gradient: Perspectives on AI
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The Power of Practice
"I find that I'm like often just very skeptical of, you know, especially, you should never be over after mistake," he says. "If it does work over sort of a broad range of different environments, if it sort of opens up maybe new things you're thinking about, then I think that's something we believe in."
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