This graph is the biggest update to the AI alignment discourse since GPT-3

For those of you unfamiliar with the lore, prior to GPT-3, the feeling was that AGI would rapidly foom based on recursive-self improvement.

After GPT-3, it became clear that the first AGI would in reality be built in a large lab using a multi-billion dollar supercomputer and any idea that it simply "copy itself to the internet" is nonsense.

Under the GPT-3 regime, however, it was still plausible to assume that the first AGI would be able to simulate millions of human beings. This is because the training cost for models like GPT-3/4 is much higher than the inference cost.

However, COT/o1 reveals this is not true. Because we can scale both training and inference, the first AGI will not only cost billions of dollars to train, it will also cost millions of dollars to run [...]

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