141–150 of 461 posts
The most likely danger with AI is concentrated power, not that sentient AI will develop a dislike for us and use us as "batteries" like in the Matrix.
For a real world example of the challenges of harnessing LLMs, look at Apple. Over a year ago they had a big product launch focused on "Apple Intelligence" that was supposed to make heavy use of LLMs for agentic workflows. But all we've really gotten since then are a couple of minor tools for making emojis, summarizing notifications, and proof reading. And they even had to roll back the notification summaries for a w…
https://9to5mac.com/2025/09/22/macos-tahoe-26-1-beta-1-mcp-i...
> AIs will get more reliable over time, like old software is more reliable than new software. :) Was that a humam Freudian slip, or artificial one? Yes, old software is often more reliable than new.
Holy survivorship bias, Batman. If you think modern software is unreliable, let me introduce you to our friend, Rational Rose.
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Agreed. Or debuggers that would take out the entire OS. Or a bad driver crashing everything multiple times a week. Or a misbehaving process not handing control back to the OS. I grew up in the era of 8 and 16 bit micros and early PCs, they where hilariously less stable than modern machines while doing far less, there wasn’t some halcyon age of near perfect software, it’s always been a case of things been good enough…
Remember BSODs? Used to be a regular occurrence, now they're so infrequent they're gone from windows 11
It's why I don't play the new trackmania.
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Neither, you’re reading it wrong. Think of it as codebases getting more reliable over time as they accumulate fixes and tests. (As opposed to, say, writing code in NodeJS versus C++)
I’ve always called this “Work Hardening”, as in, the software has been improved over time by real work being done with it.
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It shows up at https://boydkane.com under the link "Why your boss isn't worried about advanced AI". Must be some kind of sub-heading, but not part of the actual article / blog post. Presumably it's a phrase you might hear from a boss who sees AI as similar to (and as benign/known/deterministic as) most other software, per TFA
It's a sci-fi thing, think of it along the lines of "What do you mean Skynet has gone rogue? Can't you just turn it off?" (I think something along these lines was actually in the Terminator 3 movie, the one where Skynet goes live for the first time). Agreed though, no relation to the actual post.
McKittrick: General, the machine has locked us out. It's sending random numbers to the silos.
Pat Healy: Codes. To launch the missiles.
General Beringer: Just unplug the goddamn thing! Jesus Christ!
McKittrick: That won't work, General. It would interpret a shutdown as the destruction of NORAD. The computers in the silos would carry out their last instructions. They'd launch.
For a real world example of the challenges of harnessing LLMs, look at Apple. Over a year ago they had a big product launch focused on "Apple Intelligence" that was supposed to make heavy use of LLMs for agentic workflows. But all we've really gotten since then are a couple of minor tools for making emojis, summarizing notifications, and proof reading. And they even had to roll back the notification summaries for a w…
I'm happy they ate shit here because I like my mac not getting co-pilot bullshit forced into it, but apparently Apple had two separate teams competing against each other on this topic. Supposedly a lot of politics got in the way of delivering on a good product combined with the general difficulty of building LLM products.
> AIs will get more reliable over time, like old software is more reliable than new software. :) Was that a humam Freudian slip, or artificial one? Yes, old software is often more reliable than new.
Holy survivorship bias, Batman. If you think modern software is unreliable, let me introduce you to our friend, Rational Rose.
Earlier quoted context omitted.
This is not necessarily a problem. Any programming or mathematical question has several correct answers. The problem with LLMs is that they don't have a process to guarantee that a solution is correct. They will give a solution that seems correct under their heuristic reasoning, but they arrived at that result in a non-logical way. That's why LLMs generate so many bugs in software and in anything related to logical t…
> The problem with LLMs is that they don't have a process to guarantee that a solution is correct Neither do we. > They will give a solution that seems correct under their heuristic reasoning, but they arrived at that result in a non-logical way. As do we, and so you can correctly reframe the issue as "there's a gap between the quality of AI heuristics and the quality of human heuristics". That the gap is still shrin…