When an AI model generates confident-sounding but factually incorrect or completely fabricated information.
When an AI model generates confident-sounding but factually incorrect or completely fabricated information. Language models don't 'know' things — they predict likely next tokens. This means they can smoothly produce plausible-sounding nonsense. One of the biggest challenges for deploying AI in production.
Connecting an AI model's outputs to verified, factual information sources.
Retrieval-Augmented Generation.
A mathematical function applied to a neuron's output that introduces non-linearity into the network.
An optimization algorithm that combines the best parts of two other methods — AdaGrad and RMSProp.
Artificial General Intelligence.
The research field focused on making sure AI systems do what humans actually want them to do.
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