Raw LLM Responses

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@ruthfowler390it still wouldn’t fail, because they already started building and integrating AI even in the jobs that we do over the last 25 years. Even AI researchers were only aware almost by accident around 2004 that the legendary microprocessor chip its GPU cousin and its sidekick memory chips had scaled and developed enough (since the microprocessors invention in 1971) to enable practical use of AI algorithms that were actually designed in the 1970s and 80s but were mothballed and forgotten. It was the huge desktop computer, internet, mobile/smartphone biz that drove the microprocessor hardware side. If you’re old enough to remember the Pentium Processor popularity in IBM compatible desktops in the 1990s you will have some idea. Once AI researchers started delving into what and GPU could do for them and NVIDIA saw an opportunity, hedged bets and focused their biz in AI around 2006 that was it. More research unearthed even more clever AI algorithms on even more powerful machines. By 2017 A complete Symbiosis relation one benefit the other and v.versa was in full swing. Now there is Photonics to replace electronics and also the Quantum computing era is a whole massive industry by itself and likely merge with AI by 2030 as well to revolutionise the very computer architectures that kicked everything off since the days of Turing before WW2.
youtube 2026-04-19T12:2…
Coding Result
DimensionValue
Responsibilitynone
Reasoningunclear
Policynone
Emotionindifference
Coded at2026-04-27T06:26:44.938723
Raw LLM Response
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