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bnfcl

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Circumstantial tacit knowledge can probably be approximated through examples and feedback. But that is not quite the same as truly acquiring it. Bridging that gap would likely require a fundamental breakthrough. And sure, there is no objective right judgement, but that is the same for a lot of things the models already do.

The bottom line of the article:

    Intelligence is being automated. Judgment is not.
This is true. Like with a lot of similar takes on AI, tacit knowledge is not easy to add to the AI’s training set.

Understanding the fundamentals of anything will always be a valuable skill, and that only comes from hard work and experience. And much of the experience lies in tacit knowledge, not easily added as AI training data.

That, combined with knowing what to build, and more importantly what NOT to build, I don’t think AI ever will take away from us.

Quote of the main point in the article:

    In other words, the hard part moves from recall (“How do I write this?”) to judgment (“Does this actually make sense?”)
This is very true. But to evaluate if it makes sense, you first need experience writing the code. I am glad I learned software development over 15 years ago, and not today. AI is a super power, but without the experience to guide it, it can go horribly wrong really quickly.

Had the same though. The gap between open-source and the frontier is closing in, especially with Kimi K3, but that is like >2T parameters. The Gemma 4 and other models you can actually run on an average Mac, is not in the same league.

Kimi Work 2 days ago

Pretty shameless copy, but also shows how easy it is to do so. OpenAI and Anthropic had first-mover advantage, but easy come, easy go.