Hallucination, When the AI's "probability" is wrong and it makes things up., What do we need for good AI, Large amounts of high-quality data + massive processing power., Artificial Intelligence, Systems modeled on neural processing and machine learning to mimic human cognitive functions., Weights & Biases, Adjustable parameters within a model that determine the strength and influence of input data., Probability Output, The final result generated by a model, representing the likelihood of a specific classification or response., Societal Risks, Job displacement, algorithmic bias, deepfakes., Layered Processing, The structural method (Feature Extraction) where data passes through multiple levels to identify patterns., The Feedback Loop, The iterative process of refining model accuracy based on the delta between output and target results.

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