That's stupid. EVs might not be a 100% perfect fix, but they will dramatically improve air quality. (Including a reduction in o3, a major component of smog). That's a good thing.

EVs are an essential and important step towards a cleaner future. Walkable cities and high-speed rail are ultimately better, but we're not going to see that in the US in our lifetime.

Name one thing I've said that isn't an established fact.

You're way out of your depth here. Pathetic.

Try to resist the impulse to anthropomorphism these things. They are not independent entities that learn and grow on their own. Neither are they capable of things like consideration, reason, or analysis. This isn't speculation. These are simple facts, things we know with absolute certainty.

Is also nonsense, which he should know. He's lost his mind. Neural networks do not have "experiences" in any meaningful way. That's insane. Try this link. That should dispel any absurd notions you might have picked up.

This is just 'god of the gaps'. I don't know what it is you think we don't understand, but I can assure you that it's a lot less than you think. We design and build these things, after all. We don't just do random things and hope it works.

These are basic facts, not nonsense speculation like you've been posting.

You must be illiterate as well. Why are you here? Just to waste everyone's time with pointless bullshit?

If you weren't a complete moron, you could actually evaluate the claims on their merit.

Sorry, kid, your hero has gone senile. Get over it.

I've explained this in depth countless times over the past few years. At this point, if you still believe ridiculous nonsense like that, you're either incapable of understanding how these things work or your ignorance is willful.

That doesn't make what he's said any less stupid.

You are correct. The training data is not stored verbatim in the model. Neither is the model some sort of compression tool. Still, occasionally, you'll see it produce verbatim text. The reason is usually because that text was included in the training data hundreds of times. Remember that these are generating text probabilistically on the basis of the training data, making the model more likely to get verbatim text as output even though the training text isn't stored in the model.

Which is obviously impossible. Again, there is not actual understanding here, which is what you'd need to identify and correct mistakes. (Of course, the basic structure and function of these models means that kind of evaluation is impossible, so whatever hand-wavy ad-hoc definition of "understanding" you want to use doesn't really matter.) So-called "hallucinations" are exactly the kind of output you should expect, given how these models function.

Take some time to learn about what LLMs are and how they function. It'll put a very quick and decisive end to all this silly nonsense.

Why does every layperson believe they know better than actual experts? As though their ignorance was some kind of superpower. "Those dumass experts couldn't possible have thought of obvious thing! They need my outside perspective!" It boggles the mind.

If LLMs are increasing your productivity, you must be among the worst developers on the planet.

This is how we know you don't have a clue.

You obvious didn't read or understand the paper. That claim depends on infinite precision reals, which are proven to be impossible to realize in physical systems.

You're wasting everyone's time with your unimaginable ignorance. Go away.

That's because that's not a possibility, it's silly nonsense.

Take some time and learn about how LLMs work. This fact will become obvious very quickly.

He was 75 when he left Google. I won't say that senility was a factor, but he's been spouting nonsense ever since.

It's true. LLMs can't code. All they can produce is text that looks like code, just like any other text the produce. They lack the ability to consider, reason, and analyze. This is an indisputable fact.

Try not to take sensationalist headlines at face value just because they affirm your silly delusions.

In 2004? The z80 was still going strong. The ez80 was just a few years old, after all. That product line is not being discontinued, only the z84C00 line [pdf].

So, no, it would absolutely not have been considered NRND back then. Even today, as a platform, the z80 is as stable as ever.

Old does not mean "obsolete". It's been around for ages and a lot of people are familiar with it. Finding software and developers isn't an issue. There's a lot of value to be had from the kind of stability the z80 offered. Again, I'll point out that Zilog will still be making binary-compatible chips, just not ones you can drop into your Colecovision. You'll need to make a simple adapter. That's pretty damn amazing.

Those mental gymnastics could win an Olympic gold medal.

That seems unlikely given the absurdly high false-positive rate you get out of these things. You wouldn't have any students left by the end of the semester!

How it works everywhere I've been involved, students submit their work though an online portal which provides them with a plagiarism score a few minutes later. They can then review their work to see what the system flagged. Above a certain threshold, the system (or policy, depending on the institution) won't allow the assignment to be graded, requiring a human review if the assignment isn't resubmitted with a lower plagiarism score before the deadline. That's just how bad these tools are at detecting actual plagiarism.

That said, it would be very difficult to catch instances of intentional plagiarism without them. Yes, despite how simple it might appear to you at first to game the system, it's not nearly as simple as you think.

If you think AI is going to replace developers, you're in for quite a surprise.