Raw LLM Responses

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G They should have AI art shows and award the computer’s processor or program as b… ytc_UgyCScZmD… G UBI.  We can keep playing this stupid semantics game but unless we agree that h… rdc_n5h2mn7 G 0:10 Let's be real. Everyone said robots were going to take everyone's job but i… ytc_UgyCKRNUL… G As a developer, I assure you, AI is completely utterly moronic compared to human… ytc_Ugz-pQ126… G Gonna be honest, wasn't paying attention till I saw the pukie >3> But to be fai… ytc_Ugza_HDz4… G Back in 1998–99 in Romania, I used to study from Xeroxed copies of their book! … ytc_UgwhnOb8b… G That robot looked at her like girl what are u making a video of use for like bro… ytc_UgymQJk6V… G You remeber the cartoons where the overlord bad ai tried to kill humanity while … ytc_UgwSYuMzH…
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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