Dude, I've been writing code for 40 years. I've used so many different tools, stacks, libraries and APIs that at this point I don't remember any of them, and I haven't remembered them for years, and it doesn't matter at all. Sure, I have to look everything up, but that's fine, that doesn't matter. What matters is that I know when something looks wrong, or hard to maintain, or inefficient, or insecure, or... pick the axis. And I can dig in and find the problem. Anyone can tell if code works, that's easy. Understanding when and why it might break or otherwise impose additional costs, that's the real skill.

Which, as it happens, is exactly the skill you need to use an LLM effectively. Also the skill you need to understand legacy code, review colleagues' commits, etc., etc., etc. I used to say that the ability to read and understand code is an underrated skill, but an old friend corrected me at lunch a couple of weeks ago, saying that the ability to read and understand code is the most important software engineering skill, and always has been. Upon reflection, I agreed. And LLMs make this clearer than ever before.

I'm confused by all of these posters who've never heard of "the curve". I wonder if it's because they're all young'uns who went to school during an interval when progressive educators had decided to abandon it... with the inevitable grade inflation that was totally predicted.

When I was in college 40 years ago every class that had more than ~30 students in it was graded on the curve, and even some of the smaller ones (though in a smaller class it becomes statistically questionable). I used to love the groans when a buddy and I walked in the first day of class, because they knew we were going to "bend the curve". :D

Though in all seriousness, the whole point of using a curve is that in a sufficiently large class, it's statistically guaranteed (to very high probability) to be "unbendable". Inserting a couple of students at the top would mean that students who might be just above a cutoff might fall just below it, but it's not going to make a difference to many.

College isn't like tee-ball, where every player gets a participation trophy, and it shouldn't be. Especially not at elite schools. Part of the purpose of a university education is to act as a filter, and not just to filter out those who can't cut it at all, but to rank all of the students by performance, so graduate schools and potential employers can make use of that information.

Don't be so sure about the "shipped off". Google is heavily investing in on-device AI that runs in a trusted enclave (e.g. TrustZone on ARM). I left the company in August of last year but I doubt this has changed since it's been a major area of focus for quite some time.

What questions that they asked, for which he said the answers were on the web site, can he not legally answer?

He clearly had an axe to grind with CNBC, given his multiple passive-aggressive mentions of how they predicted his downfall.

The one interviewer appeared to strike a body blow when she asked if his motivations were tied to a performance-based compensation package. All of GameStop's flailing malarky makes sense through that lens: the CEO was trying a hail mary, 'cause otherwise he gets didly-squat. Part of that malarky is claiming to own 5% of eBay when, as the main interviewer pointed out, most of that so-called ownership was through derivatives. This guy's a fraud. Time to short GameStop.

The interview shows the CEO is kind of a jerk. He probably shouldn't be put in situations where communication is a requirement, like public interviews that are intended to help achieve an aggressive goal.

It's like he didn't understand he was on air during the conversation, despite the host clearly calling out that there was an audience listening.

The stark response from eBay is certainly understandable, having seen the interview.

Forget legal power ... HOW? What technical mechanism does the FCC have that can block firmware updates over the public internet? Are we proposing a China-style "Great Firewall" for U.S. consumers?

The most concerning part should be that the utility isn't auditing it's service. The most basic check is to compare water pumped or otherwise brought into the system against water usage billed to customers. Those two numbers should be equal, any discrepancy indicates leaks or other unaccounted-for draws. Any discrepancy should also be relatively stable, with any large variations correlated to known main breaks. You especially audit things immediately after a major change like bringing smart meters on-line to catch problems like this.

I don't need 1000 miles. 600 (unencumbered) is definitely sufficient, and 500 might be okay. The thing is that I'll lose half to 2/3 of that range when towing my camp trailer, and that's not even considering that I'm typically towing it up into the mountains, gaining ~5000 vertical feet. I also need minimum 12k pounds of towing capacity and I'd like a little headroom, so call it 16k, and the bed payload has to be able to take at least 2000 pounds, because that's how much the trailer puts on the fifth-wheel hitch.

I'm anxiously awaiting an EV pickup that can do this. I'd love to have essentially unllimited electricity to buffer cloudy days (I have 1 kW of solar panels on the trailer and on sunny days they generate way more than enough, but consecutive cloudy days can leave be difficult).

3/4 ton and 1-ton gas and diesel pickups typically have oversized fuel tanks that provide about 600 miles of range, because that's what you actually need when you start hauling or towing significant loads. I don't think an EV pickup needs to have more range, but it needs to be comparable, and to be able to tow and haul comparable loads.

I'm not anti-EV by any means. I bought my first EV in 2011, and have had electric cars ever since. Trucks are a different sort of problem, though.

That's getting there, though I'd like to see some driving tests with a good-sized fifth wheel at highway speeds. The towing capacity is probably okay, though it provides very little headroom for when I'm towing both my camp trailer (~8k) and my boat (~3.5k), which I actually do several times each summer. But I think the payload capacity is too small to tow the trailer, which puts about 2000 points on the truck.

On the contrary, evidence seems to suggest that AI has long been very good at generating zero-day vulnerabilities. It has a little more trouble with identifying and avoiding them.

Agreed that the Mach-E is a terrible name. But how did they screw up such a guaranteed out-of-the-park home run with an electric Mustang? I mean the whole image of the Mustang is a sporty performance vehicle for the young and stupidly lead-footed. Mustangs are classically known for acceleration and EVs are wickedly good at that. I mean, if Ford were to create a 1965-styled electric Mustang, I shudder to think how many boomers would buy them. They were the dream car of an entire generation.

Ford, are you listening?

Agreed. My sedan has been electric for nearly a decade now, but I'm still driving a diesel pickup (1-ton, though a 3/4 ton would be sufficient) because EV pickup range is inadequate -- and I think it may be inadequate for a while. I need 250 miles of range when towing a trailer, which means I need ~500 -- maybe 600 -- miles of range without.

I'm not generally a fan of hybrids, but I think plug-in hybrids with large-ish batteries may be the sweet spot for a while with pickups. The Dodge Ramcharger is looking really good to me, though I'd like to see them make a 2500.

Can we have examples of the AI slop that couldn't possibly be human created?

When it goes wrong, how bad can it get, and what's it trying to do?

A fine paid by the business will not change behaviour of managers -- who just profited (got bigger bonuses) from this. The decision makers need life changing fines or prison time. Managers in other companies will see this, decide that they do not want the same and so behave.

It is effective at reducing staff cheaply, but it has a huge downside, shared with most attrition-based schemes for reducing payroll: The best employees are also the ones who find it the easiest to leave. The worst employees are also the ones who will grit their teeth and hold on to the bitter end.

It's harder and more costly (in the short term) to do targeted layoffs which allows the company to target low-performers, or those who are low performers relative to their cost. It's the better choice, though.

Lots of the top performers will.