I didn't write that very clearly. Google doesn't have a problem with non-Play and sideloaded apps being installed in general. They do have a problem with malicious apps, regardless of source.

No... I'm pretty sure it's not that. Android does protect against malicious non-Play and sideloaded apps, and Google doesn't have a problem with those being installed. (Context: From 2014 until late last year I worked on the Android security team. I have pretty good knowledge of what they do and don't care about.)

I'd like to understand exactly what this part of the Google response is talking about. Maybe it's just throwaway FUD, not referring to anything in particular, but it could also be something the EU is demanding that is actually bad for users.

You do know that insults where the other side has strong proof they are not true do not work, right? Well, probably that is already beyond you. ;)

In my experience, that's Rust. Or maybe Haskell. The more guardrails the AI has, the better.

I don't think you know what model collapse is either. I don't mean that pejoratively, the whole concept is a muddled mess from the name on.

"Model collapse" isn't anything unique to AI. Any model will drift if it's repeated trained on its own output. Models are all imperfect fits and that imperfection compounds if they're not anchored to actual data. Put a different way, the data processing inequality says you can't create information through computation. It's not "collapse," it's drift.

Once upon a time I was registering images to each other. One of the techinques is to create an average across all of the images, register each individual to the average, and repeat. If you just do that naively though, the average (i.e. the model) will drift farther and farther from the mean of the original images, or even anything recognizable as being related to the original images.

"Model collapse" isn't a problem you fix. If you want to model human language you train on human language. If you want a self-evolving language model then you train on successive generations and see where you end up. Humans don't "get a form of model collapse" we experience exactly the same thing. We call it "languge evolving", accents, fads, "why are the kids so weird," etc.

People talk about model collapse as if AI generated training data is some kind of poison because it's AI generated. It's not. If you train on human vetted data, whether or not it's AI generated, you'll get something that humans are okay with. If you train on SEO optimization web pages that have never been read or written by any human, particularly if you do it generationally, then you're going to get drift, whether or not the stuff is AI generated, random, or whatever.

Yup. This is precisely the situation. The investment bubble is undeniable. It is, however, not a given that it will collapse. Not all bubbles do.
But beyond the investment bubble- AI itself is very real.
When the dotcom bubble burst, it's not like e-commerce went away.
All the datacenters that were built- they didn't go away.
2 of my organizations datacenters were dotcom datacenters that were abandoned by Verio and picked up by us on the cheap, where we utilized them profitably for going on 2 decades now.

You're not an academic. You're a wannabe.
An academic doesn't deny reality in order to soothe their own cognitive dissonance.

Look at you- lol.
You construct this fantasy bubble around yourself where you did not just insult me while offering zero refutation of actual factual points I made (bun Rust rewrite)
And you continue to act as if that is not how we got here.
You are so fucking deluded. Again- if you teach anyone, it's a fucking crime for that institution to still employ you. But I'm betting it's not actually true. I'm betting maybe it was true at some time, and you can't get past the fact that they let you go long ago.

Your alzheimers seems to kick in just a few sentences after you start writing- it's incredible.

Can you breathe better with your head buried in the dirt?

I honestly don't care about OnStar or "Super Cruise" subscriptions... and some level of subscription is reasonable.

OnStar probably has thousands of employees and significant hardware/infrastructure expenses. Those expenses likely go up annually. A subscription is reasonable for this service. Also, if you don't even want OnStar in the first place, don't get it.

Super Cruise is Chevy's hands-free-but-eyes-on-the-road cruise control (basically level 3 Autonomous Vehicle). That's an extremely complex system requiring consistent and on-going software updates and backend development. I think it would be cool to have one for a month or so... or maybe to help take the edge off of a very long drive, but I don't want to pay the lifetime expense of it upfront as part of my automobile purchase unless I plan to use it. Again, a subscription here seems rational.

16kloc is a small project.

I should soften what I said before: You can get away with seat-of-the-pants work if one or more of: (a) your projects are small, (b) your projects are non-critical or (c) you invest in massive testing and validation.

In my old job, if I made one kind of mistake it could prevent three billion Android devices from being able to boot. If I made a different kind, it could result in the same number of devices being insecure against data extraction and other attacks (of course, OEMs often made those mistakes for me). In my new job, if I make mistakes vehicles can crash and people can die.

I want all the help the tooling can give me, and I spend a fair amount of my time building additional tools to prevent mistakes. None of it eliminates the need for testing, of course, especially when lives are on the line, but bugs that get caught by the compiler cost almost nothing. Bugs that get caught by QA, or, far worse, in the field, are very expensive.

Note that there are big systems built in Python. Instagram has millions of lines of Python code. They also mandate explicit type declarations everywhere and they built their own static typechecker, Pyre. Lots of other people have built typechecking libraries and tools for Python, trying to fix that problem. Maybe the next time I write Python I should try some of those tools.

Though I probably won't ever write any Python again. I really only use it for quick and dirty scripts, and these days I tell AI to write those for me, and I don't even bother to read the code. If it works, fine. If it doesn't, I tell the LLM to figure out why, and fix it.

lol- I know you are but what am I?
Your sub-100 IQ never ceases to amuse me.

So you have no refutation whatsoever to what I said... you could have just said that ;)

Well, that explains why the world is getting dumber.

You don't know shit. If you do indeed teach people, you are doing them a harm.

Sure there are. Some bug reports, you look at them and dig in and say "Damn, that's obscure. It depends on subtly-wrong but arguably-correct-in-isolation mistakes in four different places. How the hell did they even find that?".

Granted that it's more common to glance at it and just be ashamed, or to look at it and say "Really? You think an attacker can do A, B, C, D, and E, all at the same time? Oh, and to do B or D they'd already have to have the system mostly compromised. Okay, I'll fix it, but no way in hell is that actually exploitable."

Sorry, but you're wrong.

Maybe... if the projections are in formal filings I don't think they can do that without risking SEC penalties. They can be optimistic about revenues or falling costs or things, because who can tell? But straight up ignoring things, probably not.

Heyyyyy, we agree on something.