I agree that LIDAR or radar are better solutions than image recognition. I mean, that’s literally what those technologies are for.

But even then, that’s not enough. LIDAR/radar can’t help it identify its lane in inclement weather, drive well on gravel, and so on. These are the kinds of problems where automakers severely downplay the difficulty of the problem and just how much a human driver does.

You are making it far simpler than it actually is. Recognizing what a thing is is the essential first problem. Is that a child, a ball, a goose, a pothole, or a shadow that the cameras see? It would be absurd and an absolute show stopper if the car stopped for dark shadows.

We take for granted the vast amount that the human brain does in this problem space. The system has to identify and categorize what it’s seeing, otherwise it’s useless.

That leads to my actual opinion on the technology, which is that it’s going to be nearly impossible to have fully autonomous cars on roads as we know them. It’s fine if everything is normal, which is most of the time. But software can’t recognize and correctly react to the thousands of novel situations that can happen.

They should be automating trains instead. (Oh wait, we pretty much did that already.)

That may be part of it, but Saudi Arabia also has a long track record of being incredibly abusive and generally just not giving a shit about worker’s rights.

Even talking about it this way is misleading. An LLM doesn’t “guess” or “catch” anything, because it is not capable of comprehending the meaning of words. It’s a statistical sentence generator; no more, no less.

He can give himself whatever titles he likes, that doesn’t mean he makes any positive technical contribution.

Machine learning has many valid applications, and there are some fields genuinely utilizing ML tools to make leaps and bounds in advancements.

LLMs, aka bullshit generators, which is where a huge majority of corporate AI investment has gone in this latest craze, is one of the poorest. Not to mention the steaming pile of ethical issues with training data.

Very nice writeup. My only critique is the need to “lay off workers to stop inflation.” I have no doubt that some (many?) managers etc… believed that to be the case, but there’s rampant evidence that the spike of inflation we’ve seen over this period was largely due to corporate greed hiking prices, not due to increased costs from hiring too many workers.

You can very safely remove the “probably” from your first sentence.

I mean, there is a hard limit on how much info your brain can take in. It’s time. Every hour spent learning one thing is an hour not spent learning everything else.

Libre Office

There is no way that arming Taiwan results in Taiwan starting a war of aggression against China.

What arming Taiwan does is make it an increasingly bad idea for China to invade Taiwan. It’s a deterrent to make sure the nuclear power who constantly threatens Taiwan (read: China) doesn’t think they can just go and take what they want without consequence, and probably commit a little genocide on the side.

You know, like Ukraine.

*Thinnest and yet roughest. Not thick enough to be a barrier, and it can rub you raw to provide an entry point at the same time!

“Sealed” is also a vague suggestion with HVAC. Every ducting join, every piece of equipment, all of it leaks. I shudder to think how much heating/cooling is wasted that way.

This. Satire would be writing the article in the voice of the most vapid executive saying they need to abandon fundamentals and turn exclusively to AI.

However, that would be indistinguishable from our current reality, which would make it poor satire.

The issue with “Human jobs will be replaced” is that society still requires humans to have a paying job to survive.

I would love a world where nobody had to do dumb labour anymore, and everyone’s needs are still met.

What part of “we paid these guys and they said we’re fine” do you not? Why would they choose and pay and release the results from a company they didn’t trust to clear them?

I’m not saying it’s rotten, but the fact that the third party was unilaterally chosen by and paid for LMG makes all the results pretty questionable.

It’s hard to trust a firm that is explicitly being paid by the company they’re investigating. I could be convinced that they are actually a neutral third party and that their investigation was unbiased if they had a track record of finding fault with their clients a significant portion of the time. (I haven’t done the research to see if that’s the case.)

However, you have to ask yourself - how many companies would choose to hire a firm which has that track record? Wouldn’t you pick one more likely to side with you?

The way to restore credibility is to have an actually independent third party investigation. Firm chosen by the accuser, perhaps. Or maybe something like binding arbitration. Even better, a union that can fight for the employees on somewhat even footing with the company.

The fundamental difference is that the AI doesn’t know anything. It isn’t capable of understanding, it doesn’t learn in the same sense that humans learn. A LLM is a (complex!) digital machine that guesses the next most likely word based on essentially statistics, nothing more, nothing less.

It doesn’t know what it’s saying, nor does it understand the subject matter, or what a human is, or what a hallucination is or why it has them. They are fundamentally incapable of even perceiving the problem, because they do not perceive anything aside from text in and text out.

I kind of disagree with you, in that when I think about the standalone meanings of the words in each phrase, I think they do say the same thing.

The meaning of the words “You are welcome [to the help I gave you]” implies, to me, that there wasn’t actually anything to offer thanks over. You’re acknowledging their thanks, but telling them that they are welcome to take/use whatever it is you’re talking about. [EDIT: normally when someone tells me I’m welcome to something, I feel less compelled to ask and thank in the future. “You’re welcome to anything in the fridge”, for example.]

It does not imply, to me, that I would appreciate them returning the favour. That might be implied meaning in the phrase, but it’s definitely not what those words mean by themselves.

In any case, “You’re welcome”, “no problem”, “no worries”, etc… are all idioms that mean something different than what their individual words mean. The phrases as a whole carry a different meaning than the words themselves suggest.