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Joined 1 year ago
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Cake day: July 7th, 2023

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  • If you want vertical tabs with the ability to organize them in trees I suggest the Sideberry extension. It legitimately makes me nervous that the functionality would ever go away, it improves my productivity so much.

    You can bookmark trees, collapse them, search them, load/unload them manually, I could go on. It makes it easy to organize dozens or hundreds of tabs. I have some trees for emails, news, forums, projects, etc. When I’m done just fold it up: the top tab bar can hide tabs that aren’t in the active tree you’re using, so you can still navigate the tabs normally.






  • So this is probably another example of Google using too blunt of instruments for AI. LLMs are very suggestible and leading questions can severely bias responses. Most people using them without knowing a lot about the field will ask “bad” questions. So it likely has instructions to avoid “which is better” and instead provide pros and cons for the user to consider themselves.

    Edit: I don’t mean to excuse, just explain. If anything, the implication is that Google rushed it out after attempting to slap bandaids on serious problems. OpenAI and Anthropic, for example, have talked about how alignment training and human adjustment takes a majority of the development time. Since Google is in a self described emergency mode, cutting that process short seems a likely explanation.



  • This is a classic problem for machine learning systems, sometimes called over fitting or memorization. By analogy, it’s the difference between knowing how to do multiplication vs just memorizing the times tables. With enough training data and large enough storage AI can feign higher “intelligence”, and that is demonstrably what’s going on here. It’s a spectrum as well. In theory, nearly identical recall is undesirable, and there are known ways of shifting away from that end of the spectrum. Literal AI 101 content.

    Edit: I don’t mean to say that machine learning as a technique has problems, I mean that implementations of machine learning can run into these problems. And no, I wouldn’t describe these as being intelligent any more than a chess algorithm is intelligent. They just have a much more broad problem space and the natural language processing leads us to anthropomorphize it.