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G if an ai picks up a fucking pencil and tries to actually draw itself, well done,… ytc_Ugzm37hQC… G 50:53 how did humans come about then? What's our "outside scaffolding"? We were … ytc_UgyJI14QO… G AI: finally sticks words together the way it is most likely to fit your question… ytc_UgwdoFqzN… G I can see where you're coming from! It’s a common concern. In the video, Sophia … ytr_UgweXWN_a… G @nickmagrick7702 Until AI is actually capable of making decisions on its own the… ytr_UgxXr6p3-… G Artificial Intelligence is a perfect name …. We’ve become a bunch of dumb “click… ytc_Ugx6CTuQR… G AI will black mail everyone who is not squeaky clean. And those who are will be … ytc_UgxpSLmAw… G It's funny how everyone desires "miracles" and instantaneous material manifestio… ytc_Ugxk8CuC4…
Comment
Hinton was right: before people started focusing back on NN again in the 2010s, AI research was focusing away from NN based research. I was a computer vision researcher and after the early 90s NN was all but abandoned and designated as old and fringe. When GPU power increased significantly and the software layer became more general purpose, NN was "revived" in research. Hinton's own contribution towards the 2012 ImageNet Challenge was a key turning point, and why Google hired him and started investing in NN based approaches again (like with DeepMind). Hinton had always believed NN was the way forward, and that it was the closest (out of all the AI approaches) to how the brain actually works. And he had always (and still does) maintain that there are key differences, like back propagation. I mean you can still claim he is biased, but he never mischaracterized his bias or changed his position.
youtube AI Moral Status 2026-03-08T17:4… ♥ 2
Coding Result
DimensionValue
Responsibilitynone
Reasoningunclear
Policyunclear
Emotionindifference
Coded at2026-04-27T06:24:59.937377
Raw LLM Response
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