@jun_song I don't understand why somebody would like to run an llm on device, the laptop runs very hot, fans blazing and battery goes faster lower, when I just can connect my spark or something else via Tailscale.
@TheAhmadOsman GPUs are a: "I can predict the future and its all gonna be fucked up, but im actually having the balls to act on my own advice so im buying that stuff" crises.
@dhh Human adoption rate is to slow and the media spreading fear instead of showing capabilities fu*ing people over because they can't jump on a train they never hear coming.
The people that argue that AI can't never be conscious because all they do is predict the next token: You confuse the optimization objective with the mechanism produced by optimization.
Human evolution only selects for reproduction and survival. Somehow, out came vision, language, mathematics, music, art, love, philosophy, self-reflection — and consciousness.
The objective does not specify the internal solution!
And with task-level RL, the argument becomes even weaker: the objective is no longer merely “predict the next token,” but increasingly “solve the task” or “achieve the desired outcome.”
The model may still act through tokens, but those tokens are now part of a policy optimized over entire trajectories: plan, act, observe, correct, succeed. Sounds familiar? No coincidence!
Saying “it’s still just predicting tokens” is a bit like saying humans are “just activating muscles.”
The people that argue that AI can't never be conscious because all they do is predict the next token: You confuse the optimization objective with the mechanism produced by optimization.
Human evolution only selects for reproduction and survival. Somehow, out came vision, language, mathematics, music, art, love, philosophy, self-reflection — and consciousness.
The objective does not specify the internal solution!
And with task-level RL, the argument becomes even weaker: the objective is no longer merely “predict the next token,” but increasingly “solve the task” or “achieve the desired outcome.”
The model may still act through tokens, but those tokens are now part of a policy optimized over entire trajectories: plan, act, observe, correct, succeed. Sounds familiar? No coincidence!
Saying “it’s still just predicting tokens” is a bit like saying humans are “just activating muscles.”
Technically true at one level but useless as an explanation of the creation it has produced.