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G I filed for US patent 3890161A titled DIODE ARRAY in 1973. It was granted in 197… ytc_Ugy6vSx83… G Imagine that robot would've turn towards the human from a glitch,, he would've b… ytc_UgzQYMLn3… G Can we all downvote this ai bullshit. Every responde op is doingis ai generated.… rdc_n0fcv0j G I am an artist and now can't even get commission because of AI It truly hurts m… ytc_UgzF4_WEh… G This is scary now with technology you can make a robot exactly like a person or … ytc_UgyyKatQw… G Copyrighting AI art could kill it faster than any poison or nightshade or whatew… ytc_UgyG7SODn… G Artificial INTELLIGENCE!!?? High technological machine, yes. Intelligent, no. Re… ytc_UgwdluUMl… G Nope it’s not Good! Human connection is needed!AI is being pushed and it’s not g… ytc_UgxSjqvWk…
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@horizon-th2392 Believe me, I've watched his entire four part series many times, and I know about how the weights are continuously updated with gradient descent. It's a beautiful piece of math, no doubt, and as Mathematics enthusiast it is a miracle this technology was discovered. But the interpretability of such models is incredibly difficult for anyone. Additionally, I think a major flaw in machine learning is the absence of a strong theory of distributions as a foundation. This makes them more flexible, but it also makes it so you can't run vigorous tests of significance. Coming from a statistical background, it is standard that when you design a model that tests for the significance of parameters in your model. If you add parameters that are insignificant into your model, these tests will tell that you should remove them. This helps prevent overparameterizing a model. No such formal tests exist in a neural network. More simply, people rely on minimizing a criterion, like mean squared error. These are useful metrics, but so much of the rigor that exists in traditional statistical models is absent from these neural networks. When you cannot test if a neuron's presence is significant within a neural network, then you have to guess and check. Same with adding additional hidden layers. This is so unscientific it hurts. It's shame and neural networks need so much more research behind them before we can consider using them for tasks that have such serious implications.
youtube AI Harm Incident 2021-05-11T17:4… ♥ 1
Coding Result
DimensionValue
Responsibilitynone
Reasoningunclear
Policynone
Emotionmixed
Coded at2026-04-27T06:26:44.938723
Raw LLM Response
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