This article and discussion is specifically about massively upscaling LLMs. Go follow the links and read OpenAI’s CEO literally proposing data centers which require multiple, dedicated grid-scale nuclear reactors.

I’m not sure what your definition of optimization and efficiency is, but that sure as heck does not fit mine.

Don’t look for statistical precision in analogies. That’s why it’s called an analogy, not a calculation.

No, this is the equivalent of writing off calculators if they required as much power as a city block. There are some applications for LLMs, but if they cost this much power, they’re doing far more harm than good.

https://arstechnica.com/health/2023/11/ai-with-90-error-rate-forces-elderly-out-of-rehab-nursing-homes-suit-claims/

Exactly this, and rightly so. The school’s administration has a moral and legal obligation to do what it can for the safety of its students, and allowing this to continue unchecked violates both of those obligations.

Electronic voting is an absolute security nightmare. As a software engineer, the relevant XKCD sums up my position nicely: https://xkcd.com/2030

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.

Biblically accurate appetizers

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.