Raw LLM Responses

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G Common sense. It's so bloody rare --- It's a super power now. The 3 laws of R… ytc_UgxvtYgsl… G 2 things, house buyers like that are the worst. Scum, I hope they never have goo… ytc_UgxuvJcz1… G The video really nails the fear that if everyone’s automated out of a job, nobod… ytc_UgyGcBuEI… G Beautiful. AI isn't art. It's just an image. Don't lose hope artists... Man-made… ytc_UgwbGgUOD… G First, you’re an old lady, what’s with the facial piercings? Does not improve yo… ytc_UgzPmhEf8… G You said exactly what’s been on my mind. Thank you so much for speaking up and f… ytc_Ugw8SSfKa… G I wonder what AI would do if more and more people flooded the internet search en… ytc_UgwbNXKpB… G Why would you be mad about the ai getting poisoned, if it’s so great then it wou… ytc_Ugy1J_bzF…
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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