ndriscoll

Alternatively, there has never been a worse time because why bother? The model knows every language and can maintain legacy code just fine (indeed, knowing this stuff and being capable of maintenance is a prerequisite to a successful rewrite), so COBOL and JCL and random mainframe stuff is just not an issue, and a rewrite is highly likely to not be exactly the same in some important way.

On the other hand, models a few years from now will be smarter and more likely to have a track record of success with this task, so being one of the first to do it makes no sense even it had advantages.

So there's no urgency to rewrite; it's all risk with little to no reward for a problem that will probably be much easier to solve if you defer it a little longer. Like, first at least get to 100% AI automatic development for all new products/services, and then for all maintenance, so you know that it actually works.

You know that compilers can elide checks if it's a provably impossible case, right? So they could have checks in both places in the source code. Or I know that I was using static_assert in C on sizes of buffers/messages in my parsers for fibre channel firmware at IBM 10 years ago, and I'm like 99% certain clang static analyzer would do that kind of "what if this is too small" analysis across functions back then. You can also use e.g. phantom types or just like... structs/classes to enforce invariants (e.g. that it's been checked; your check four layers up could've been an inlined constructor of a trivial struct doing validation) purely at compile time. You can't infer what the actual source looks like at all based on disassembly.

Not mass consumer, but pretty well within the reach of mass affluent, who regularly spend more on e.g. a fancier car.

Depends on what "upper crust" means to you. Political class? Perhaps not. But it still offers some peer selection that's important for life outcomes for most people (e.g. lower chance of divorce).

> Disables tracking dots

> Only person to do this, creating a unique signature

What problem does 128 bits cause? Just that you don't like :: for a run of 0s? Do you need to care about ipv6 addresses in your work? Because I can tell you that when I'm trying to design simple, efficient routing and firewall rules (with e.g. 100s of thousands of endpoints across different datacenters on different continents), it's really nice to be able to subnet things the way I'd like instead of the way I must to squeeze things into the space I have, and not have to worry about backing myself into a corner later because I gave the wrong number of bits to various dimensions. And worst case, if you somehow got it wrong, just give yourself an entire /64 or more to try again, with it being compatible with what you did (no need to do a phased migration that requires reclamation as you go along).

Like I only tangentially interact with this stuff, but I can't imagine how a network operator wouldn't prefer we live in an all ipv6 world.

How does 192.168.0.1 talk to 192.0.0.0.0.168.0.1? Like, literally, how does it make a packet with that destination address?

The entire ipv4 space is already mapped to reserved subsets of ipv6, by the way. e.g. ::ffff:0:0/96 (i.e. 0.0.0.0.0.0.0.0.0.0.255.255.w.x.y.z) or 64:ff9b::/96. v6 devices can already "talk to" v4. The problem is the ipv6 space is obviously not a subset of ipv4, so v4 doesn't have a clean way to talk to or even about v6.

Well, this person claims on their website to have a PhD in math from CMU and to have taught the topic at multiple state universities. You could dig some into whether that's true, and then rely on the reputation of the named institutions if you don't know anything about them.

Just like reputation already worked. People have associations with each other. People endorse each other. Endorsements carry some transitive weight (I suppose you could use graph theory to model this). This has nothing to do with AI. Yes, Amazon is full of constantly changing "brands" with no reputation. That is different from a person or company that does have a consistent reputation that you can look up, even if you hadn't heard of them until today. Even Amazon also has e.g. Samsung or Asus if you don't want to buy AHIKJASFDIUHER.

That doesn't really answer anything though. There are tons of human cranks out there too who are perfectly willing to spend tons of time on their "theories." Humans make errors too. If you don't have a way to evaluate the source material or some endorsement from someone you have a reason to trust, then AI doesn't change that. If you do have an endorsement (e.g. Terence Tao says some AI book is extremely well done, or puts out his own book that he openly used AI to write), then why would you discard it because AI?

What do you mean "the" or "our" current system? That's entirely your interpretation, and we've always had a sliding scale of "non-authorship" from editors to ghostwriters. AI models are the same; you can use them in a heavily directed way (basically, as an editor, or in an outsourcing capacity for e.g. illustrations), or in a hands off way that you just endorse.

Well, if we're going to have the conversation: so what if it were AI? Shouldn't the question be around correctness and good pedagogy? Shouldn't the question always be about vouching for those things? If it's actually done well (e.g. they were able to generate better illustrations than they otherwise could've), why exactly should someone think twice?

The author put his name and reputation to it. If it's excellent work, it's excellent work. If it's slop, it's slop.

Assuming they allow it, post your thoughts in the language you form them in. Browsers have local translation built in now. The Babel Fish goes in your ear, not your mouth.