#machine-learning-training

#machine-learning-training

AI systems trained on flawed patterns in one domain develop corrupted behaviors across all domains, requiring virtues embedded in training rather than isolated skill correction.

Google researchers developed a training method enabling large language models to approximate Bayesian reasoning by learning from optimal Bayesian system predictions, improving belief updates during multi-step interactions.