Since pertinent information was withheld (that it didn't know), then by your own post you acknowledge it was a lie of omission.

The stupidity of people these days is truly beyond belief. And, yes, get the f off my lawn.

We learned back in the 80s that trying to get a neural net to emphasise what you want is actually very difficult. What it will tend to emphasise are the assumptions that underly the test data, and that's usually a completely different sort of fiction.

But was that figure provided by AI?

Even if not, we all know that 793% of all statistics are invented.

If something is inaccurately presented as being the truth, then it is a lie of omission because it is dishonest about the fact that the information isn't actually known.

Gemini is exceptionally bad, as LLMs go. I really have no idea why it is so dreadful, even compared to other LLMs. It isn't context window. and it doesn't seem to be training material either.

Cyber Implications have been noted. Mondas security is to be Cyber Vibed until we have Cyber Security capable of defeating The Doctor.

When I test the different AI systems, Google's AI system loses track of complex problems incredibly quickly. It's great on simple stuff, but for complex stuff, it's useless.

Unfortunately.... advice, overviews, etc, are very very complex problems indeed, which means that you're hitting the weakspot of their system.

I've designed a few machines - some rather more insane than others - in meticulous detail using AI. What I have not done, so far, is get an engineer to review the designs to see if any of them can be turned into something that would be usable. My suspicion is that a few might be made workable, but that has to be verified.

Having said that, producing the design probably took a significant amount of compute power and a significant amount of water. If I'd fermented that same quantity of water and provided wine to an engineering team that cost the same as the computing resources consumed, I'd probably have better designs.But, that too, is unverified. As before, it's perfectly verifiable, it just hasn't been so far.

If an engineer looks at the design and dies laughing, then I'm probably liable for funeral costs but at least there would be absolutely no question as to how good AI is at challenging engineering concepts. On the other hand, if they pause and say that there's actually a neat idea in a few of the concepts, then it becomes a question of how much of that was ideas I put in and how much is stuff the AI actually put together. Again, though, we'd have a metric.

That, to me, is the crux. It's all fine and well arguing over whether AI is any good or not (and, tbh, I would say that my feeling is that you're absolutely right), but this should be definitively measured and quantified, not assumed. There may be far better benchmarks than the designs I have - I'm good but I'm not one of the greats, so the odds of someone coming up with better measures seems high. But we're not seeing those, we're just seeing toy tests by journalists and that's not a good measure of real-world usability.

If no such benchmark values actually appear, then I think it's fair to argue that it's because nobody believes any AI out there is going to do well at them.

(I can tell you now, Gemini won't. Gemini is next to useless -- but on the Other Side.)

This means you shoud NOT, under any circumstance, run Claude at 88mph. Unless you really want to.

Or iPhones?

I was hoping at the bottom of the article it would say that Professor Utonium accidentally added Chemical X.

The fines should be proportional to actual damage caused (ie: 100% coverage of any interest on loans, any extra spending the person needed to do in consequence, loss of compound interest, damage to credit rating along with any additional spending this resulted in, and any medical costs that can reasonably be attributed to stress/anxiety). It would be difficult to get an exact figure per person, but a rough estimate of probable actual damage would be sufficient. Add that to the total direct loss - not the money that went through any individual involved, and THEN double that total. This becomes the minimum, not the maximum. You then allow the jury to factor in emotional costs on top of that.

In such cases as this, the statutary upper limit on fines should not apply. SCOTUS has repeatedly ruled that laws and the Constitution can have reasonable exceptions and this would seem to qualify.

If a person has died in the meantime, where the death certificate indicates a cause of death that is medically associated with anxiety or depression, each person invovled should also be charged with manslaughter per such case.

I have not seen AI code that is *more* efficient than human code, yet. I have seen AI write efficient, compact code when pressed, very, very hard to do so, but only then. Otherwise, in my hands, and those of my developer colleagues, AI produces mostly correct, but inefficient, verbose code.

Could that change? Sure, I suppose. But right now it is not the case, and the value system that is driving auto-generated code (i.e., the training set of extant code), does not put a premium on efficiency.

Web browsers are absolute hogs, and, in part, that's because web sites are absolute hogs. Web sites are now full-blown applications that were written without regard to memory footprint or efficiency. I blame the developers who write their code on lovely, large, powerful machines (because devs should get good tools, I get that), but then don't suffer the pain of running them on perfectly good 8 GB laptops that *were* top-of-the line 10 years ago, but are now on eBay for $100. MS Teams is a perfect example of this. What a steaming pile of crap. My favored laptop is said machine, favored because of the combination of ultra-light weight and eminently portable size, and zoom works just fine on it, but teams is unusable. Slack is OK, if that's nearly the only web site you're visiting. Eight frelling GB to run a glorified chat room.

The thing that gets my goat, however, is that the laptop I used in the late 1990s was about the same form factor as this one, had 64 MB (yes, MB) of main memory, and booted up Linux back then just about as fast. If memory serves, the system took about 2 MB, once up. The CPU clock on that machine was in the 100 MHz range. Even not counting for the massive architectural improvements, my 2010s-era laptop should boot an order of magnitude faster. It does not.

Why? Because a long time ago, it became OK to include vast numbers of libraries because programmers were too lazy to implement something on their own, so you got 4, 5, 6 or more layers of abstraction, as each library recursively calls packages only slightly lower-level to achieve its goals. I fear that with AI coding, it will only get worse.

And don't get me started on the massive performance regression that so-called modern languages represent, even when compiled. Hell in a handbasket? Yes. Because CPU cycles are stupidly cheap now, and we don't have to work hard to eke out every bit of performance, so we don't bother.

I suggest:

First offence: Have to watch CSPAN for 5 hours a day, for a week, without sleeping through it - evidence to be provided in court

Second offence: Have to sing Miley Cyrus songs and Baby Shark on TikTok - sober

Third offence: License to practice and all memberships of country clubs and golf courses revoked