Foundation models are large AI models trained on massive datasets. They’re versatile and powerful because they can be fine-tuned for various tasks. This fine-tuning leverages transfer learning: the model first learns general patterns from a broad dataset, then is adapted with smaller, domain-specific datasets for specific problems like translation or image recognition. This saves time and data, letting organisations use advanced AI without starting from scratch.

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