The power of AI is its ability to turn unstructured data into structured data

There is so much more structure in the world than we tend to believe. And LLMs and other AI models are structure discovery machines.

The real power of AI lies in its capability to reclaim vast quantities of data at unknown speeds. This enables AI to identify perceptivity and make assumptions that would be unattainable for humans to achieve individually. This data-driven approach provides significant advantages across various industries, leading to further informed decision-makin

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There is also active research into understanding whether AI can pretrain on its own content. This is what chess-playing AIs already do, learning by playing games against themselves, but it is not yet clear whether it will work for LLMs. Because of the variety of data sources used, learning is not always a good thing. AI can also learn biases, error

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When it comes to identifying where generative AI can make an impact, we dig into challenges that commonly:

• Involve analysis, interpretation, or review of unstructured content (e.g. text) at scale


• Require massive scaling that may be otherwise prohibitive due to limited resources


• Would be challenging for rules-based or traditional ML approaches

language models are not intelligent in the ways that even small children are intelligent, but they are already superhuman at tasks like summarization, translation (both linguistic and conceptual), and association. And when you apply those skills to artfully curated source material written by equally, but differently, gifted humans, magic can happen... See more

Foundation models like GPT and Claude now serve as the index funds of language. Trained on enormous corpora of human text, they do not try to innovate. Instead, they track the center of linguistic gravity: fluent, plausible, average-case language. They provide efficient, scalable access to verbal coherence, just as index funds offer broad exposure ... See more