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Exploring the scaling challenges of transformer-based LLMs in efficiently processing large amounts of text, as well as potential solutions, such as RAG systems

Large language models represent text using tokens, each of which is a few characters.  Short words are represented by a single token …

Ars Technica Timothy B. Lee

Discussion

  • @flargh@mastodon.social Peter Cohen on mastodon
    This is a *really* good deep dive into AI - not just to understand the question begged by the headline, but with a history of how and why GPUs (like Nvidia products) are so essential.  —  https://arstechnica.com/...
  • @brehmel BA Rehl on x
    Some confirmation of the exponential learning problem. Hint: this is why Tesla will never have autonomous driving. 🤔 “Compute costs scale with the square of the input size.” https://arstechnica.com/...
  • @bdkoepke @bdkoepke on x
    “Compute costs scale with the square of the input size” RAG is a workaround, but scaling compute at O(n^2) is not great... https://arstechnica.com/...