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G Surveillance Capitalism is an OXYMORON made up bullshit like social democrat. L… ytc_Ugxj76qMa… G This is the same for almost every job, not only PM. If you know how to use AI, l… ytc_UgyD5s557… G As someone who always has to hear that jobs with art or design will be substitut… ytc_UgxAZbWsB… G It's not about losing faith but discarding ego. In order for humanity to expand … ytr_UgwvDHozC… G Creating manufacturing jobs is certainly the way of the future. How else can you… rdc_denk4qt G I asked if given enough time could AI teach humans to bend time. Answer: apple… ytc_Ugwfza5AC… G I think it can make sense. AI to me is alot like photography, the vast majority … ytc_UgwwlJ-Ua… G We need lot of hardware support for AI growth, how would that be achieved? There… ytc_UgzW16A6N…
Comment
​ @ProfessorDaveExplains I think you misunderstood that Lex Fridman's guest's statement. A deep neural network consists of hundreds of hidden layers (or dozens of transformer blocks) that are trained (weights are learned iteratively through gradient descent/other techniques) to fit the model to the training data. However, it is not impossible to know or visualize what these inner layers do. While we cannot point to individual/groups of neurons and say that "this neuron detects the language or this neuron sees the color red", we can sort of point to certain structures and say "oh this is responsible for some amount of reasoning" or "this is responsible for something else". There is an entire field of study called interpretability research that attempts to uncover some structure in how networks represent concepts. It is the equivalent of a neuroscientist trying to figure out what each neuron does in the human brain; we know that that is not possible but we can make educated guesses based on neuron activity as to what regions of the brain are activated when we do certain tasks. It's possible it was just him being sensationalist and mysterious but eh, who knows
youtube AI Governance 2025-08-26T15:3… ♥ 3
Coding Result
DimensionValue
Responsibilitynone
Reasoningmixed
Policynone
Emotionindifference
Coded at2026-04-27T06:24:59.937377
Raw LLM Response
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