You might as well be asking a tape recorder why it said something. Why are we confusing the situation with non-nonsensical comparisons?
There is no internal monologue with which to have introspection (beyond what the AI companies choose to hide as a matter of UX or what have you). There is no "I was feeling upset when I said/did that" unless it's in the context.
There is no ghost in the machine that we cannot see before asking.
Even if a model is able to come up with a narrative, it's simply that. Looking at the log and telling you a story.
Sperry's experiments makes it quite clear that the comparison is not nonsensical: humans can't reliably tell why we do things either. It is not imbuing AI with anything more to recognise that. Rather pointing out that when we seek to imply the gap is so huge we often overestimate our own abilities.
It is non-sensical because you're simply bringing in comparisons without anything linking the two. You might as well be talking about how oranges, and bicycles think as well as that is just as relevant as how humans think in this discussion.
In fact, talking about "thinking" at all is already the wrong direction to go down when trying to triage an incident like this. "Do not anthropomorphize the lawnmower" applies to AI as much as Larry Ellison.
Humans at least have a mental state that only they are privy to to work from, and not just their words and actions. The LLM literally cannot possibly have a deeper insight into the root cause than the user, because it can only work from the information that the user has access to.
Well I think the story is that they didn't ask it or trust it. They were caught by its ability to fuck up everything because a key was in the codebase.
Beyond that, isn't it just going to make up a narrative to fit what's in the prompt and context?
I don't think there's any special introspection that can be done even from a mechanical sense, is there? That is to say, asking any other model or a human to read what was done and explain why would give you just an accounting that is just as fictional.
The author is deeply AI-pilled — to the point the whole article is written with AI. Slop begets slop.
A similar cohort are discovering, in myriad painful ways, that advances in agentic coding — the focus of a lot of pre and post training — does not translate into other domains.
You can call async methods without immediately calling await. You can naively await as late as possible. They'll run in parallel, or at least how ever the call was configured.
In Javascript, promises are eager and start executing immediately. They return control back to the caller when they need to wait. So in practice, all of your promises are running concurrently as soon as you create them.
In Rust, futures are lazy don't start executing until they are awaited. You have to use various features of your chosen runtime to run multiple futures concurrently (functions like `spawn` or `select`). But that interface isn't standardized and leads to the the ecosystem fragmentation issue discussed in the article. There was an attempt to standardize the interface in the `futures` crate, but none of the major runtimes actually implement the interface.
Maybe they only ever get Samsung devices. Dex is almost a decade old.
A desktop mode was recently added for base Android tho. And you could always mod your Android device to open termux when you connected an external monitor, that sort of thing.
ZIRP and Moore have helped the cloud build up with a promise of profits and ever increasing performance. The future is likely different.
"Power will be cheap" is hope you can hang any hat on. We've been increasing compute per watt but again that's on Moore. I don't think it makes sense to bank on a new energy surplus.
And they didn't come to the same conclusion then. They changed their behavior, don't like the new behavior and are extrapolating that beyond the new behavior.
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