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Joined 3 years ago
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Cake day: June 14th, 2023

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  • With this definition, it’s not different from before. Pretty much any smartwatch or smartphone or noise cancelling earbuds record by this definition. The new thing is the automatic summaries. But for example, all modern Apple devices can listen for Hey Siri constantly, and other brands have something similar. Noise cancelling earbuds record and process the noise they’re cancelling (and Apple’s can listen for Hey Siri). Laptops do it too.



  • Part of it is that EU countries charge VAT on digital sales and prices must include it, while in the US there’s sales tax instead, which depends on the state and is only added at checkout time (and also often lower or even zero for digital goods). For example if I pay 80 Euro in Germany, then Steam gets to keep 67 because those 80 Euro include 19% VAT.

    The other part is that in a market economy, prices are determined by what generates the most profit, and not necessarily related to cost or based on fairness. EU customers apparently pay 80 Euro often enough that it makes more money than 60 or 100 Euro so developers set their price to 80 Euro.


  • I think the plateau might not necessarily be in terms of LLM capability, and we might even see LLM based tools keep improving at a high rate in the fields where they currently work well, but still have a plateau where we can’t expand their use to other fields.

    There’s a very large gap between how well LLM based coding assistants work, and how well LLM based tools work in areas where we can’t easily create a harness that can do dozens or hundreds of LLM turns between human interactions via tool use. As a result, LLMs are much less useful at tasks where there is no agent loop that can drive iterative changes and automatic verification until the final result is much better than a one-shot generation would have produced. If we can’t come up with a way to make these agent loops for more tasks then AI will plateau even if LLMs keep improving.

    Now, I think people who use coding assistants a lot and also don’t interact much with other humans who don’t might easily arrive at a conclusion like that AI running everything is inevitable. I can see this with myself too, a lot of what I do I can get Claude Code to do. Not just work stuff like actual coding or running kubernetes clusters or debugging IT problems. Also many of the random things I do at home that are not strictly coding, e.g. I’ve had Claude design 3D printed tools, or electronics circuits, entire concepts for physical toys for me to build if I get around to it. But there is a key observation to make here that keeps me from valuing its abilities too highly: I’ve been programming since I was a little kid, for almost 40 years now, and my work and my hobbies all are coding or coding-adjacent, exactly the kind of thing agent loops make good.

    One look at even just my wife’s typical day though and there’s almost no AI involved. And when it is it’s ChatGPT hallucinating nonsense when she tries to get it to research something for work etc., that or other things where there is no harness that can auto-correct errors. So I don’t have a very high opinion of AI tools for general purpose tasks right now even though I, on an almost daily basis, see Claude pull something off that I had no hopes for it to get right and that would have taken me half of an eternity to do it myself.

    But if my environment was mostly developers/engineers/nerds similar to me then I would have a much higher opinion of AI. I’d be hearing about impressive things an AI tool did constantly. I believe these kinds of environments are where most of the hype comes from, and there is no control, because people who don’t have AI tools for their tasks that work as well as modern coding tools mostly aren’t even aware of the conversation and certainly not too interested in participating.



  • The comment I replied to said it was different from recording audio because when recording, they can tell it when to record instead of listening all the time, so that’s the only part I’m arguing with.

    In this regard nothing changed:

    • You can still tell it when to record, because you can turn the feature off
    • If you didn’t turn off other Siri features before, it was already listening all the time

    I feel like half this thread doesn’t understand what their devices are doing. Latching on to a new way in which it can record all the time, while dismissing all the existing ways it can already record all the time. How are you going to protect yourself from anything if you can only recognize this when there’s something like a transcript that you can see that makes it super obvious? Most people here are probably already carrying two or three devices around that can record them but just don’t produce a transcript.



  • It’s a matter of framing. If you compare them to older datacenters they are atrocious because they’re bigger and consume more energy. But in the grand scheme of things all things IT pale in comparison to e.g. producing beef. Now with that framing you can’t sell AI hate though because people like beef, so it’s always just comparing large datacenters to smaller datacenters with the obvious results.


  • People don’t really understand this yet. There are LLMs that can do useful work running locally on 5 year old laptops (ok, only if it’s a Macbook Pro, but still). Qwen on consumer hardware isn’t close to Claude Code using cloud models, but it can do real work and this is the floor, the absolute minimum of AI we will have going forward. No matter what happens to the industry and the bubble, it will not go away. With any other outcome other than a total collapse of the bubble, AI will be more powerful than that.