8 Comments

Thanks Alejandro! That was one of the most lucid, clear, and approachable primers on how machine learning in general and LLMs in particular do what they do. Even though I already had a bit of top-level understanding of what's behind LLMs, your coverage of machine learning paradigms, N-grams and other building blocks was very helpful!

Also, well done Nick on connecting the dots as to what this means for education going forward. You two completment each other perfectly here.

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Thanks man, as usual, the merit goes to Nick for asking the right questions ;)

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I've been looking forward to this article all week, and Alejandro you did not disappoint! Thank you for a wonderfully clear article. It was a pleasure.

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Thank you! You're too kind ;)

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Nicely done, as usual, Nick and Alejandro. I especially like the clear account of experience as a key difference between foundation models and humans. I could not agree more that "examining the limitations of AI models in this regard" is fundamental to our work as educators.

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Thanks Rob. Yeah, we must be careful not to draw lazy conclusions from machine learning, it's too easy to fall prey to subtly incorrect analogies.

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Nice deep dive.

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Thanks, Rob. I am finding this work extremely fruitful for my own thinking. Greatly appreciate Alejandro sharing his time and knowledge!

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