Artificial Intelligence
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Learn how retrieval models, embedding vectors and retrieval-augmented generation are combined in modern AI systems. This article covers semantic search, the role of embeddings in supporting generative models, and the practical trade-offs of embedding-based retrieval.
An overview of how generative models produce text, images and code in modern AI systems. We look at how next-token prediction works in practice, why generative models can sound fluent without truly understanding, and how generation is typically combined with retrieval.
An overview of how generative models produce text, images and code in modern AI systems. It explains how next-token prediction works in practice, why generative models can sound fluent without truly understanding, and how generation is typically combined with retrieval and tools to produce reliable
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