They still have those? I would have thought that everything was sent electronically by now, and nobody hand-entered anything except for bank tellers and other people who are dealing face-to-face with customers.

Then again, I remember how hard it was to do an international wire transfer a few months back, and how my bank faxed paperwork back and forth to their back office, so I guess that's plausible.

The unfortunate thing, though, is that for the most part, any use of AI to do that stuff is a mistake, because you should be shifting the burden of data entry (and thus the burden of correctness) to the customer by doing everything electronically to the maximum extent possible. The fact that banks use paper forms in the first place is the flaw, and replacing the person who types the contents of the form with AI is just replacing one error-prone, bank-at-fault process with another, when they should be shifting the liability for error to the customer. This also has the advantage of reducing the likelihood of error, because the customer had to fill all that info in on the form in the first place, so you have one opportunity for error instead of two. This also has the advantage of usually making it easier for the customer, because the customer doesn't have to do stuff in person. And so on.

Show me this software that you consider usable enough to replace more than about 5% of what a software engineer does.

Depends on what you mean by AI. If you mean specialized trained models that do very specific things (e.g. optimizing just-in-time component purchases or using computer vision to make robots work more effectively, making stock picks, spotting tumors on scans, and optimizing ad spend to get the best results), then yes. If you mean LLMs, I think you missed the mark with your list (except maybe ad creation; that's plausible).

LLMs are great for automating trivial work as long as there's no high financial cost for mistakes. Chat bots to help you search for products on a website better are a great example. Or LLMs to help you write the skeleton for new code or help you write unit tests (as long as you check the results). Or LLMs to help you look for bugs in code or review code before submission. Or LLMs to help you create prototypes of new software while deciding what approach you want to take. Or LLMs to quickly create artwork for fun, where you don't care if there are extra fingers.

LLMs are not great when there is high risk. Chat bots for airline customer service are a great example. Turning LLMs loose writing code without a competent programmer looking over its shoulder is another good example.

In between are the use cases where it functions adequately, but may not save much time, because the overhead of reviewing its work adequately is a sizable percentage of the time required to do the work by hand. Writing real-world production code is a great example.

Presumably it will get better over time. But whether it will ever reach a level of trust where we can turn it loose to write code and not carefully scrutinize that work, I couldn't say. Right now, there's too much risk of it saying that tests pass when they actually haven't been run, or worse, when the AI has decided to delete the tests so that they won't fail. There's too much risk of gaslighting across the board. There's too much risk of AI subtly misinterpreting prompts in extremely creative ways to give you results that look like they are correct but are actually wrong. And so on.

I'm going to assume for the moment that the C-suite at Meta are not complete and utter morons. So from this, we can conclude that Meta is firing people not because they actually believe AI will do their jobs, but rather because they don't have enough revenue to pay for their AI hardware costs, and they're hoping that they can get away with counting on their near-monopoly on social media to let them safely unstaff large parts of Facebook, Instagram, and other services in the short term so that they can build their data centers.

And while that might be true (because the DOJ let Facebook get way, way too big), that's a stock price disaster waiting to happen. It's risking throwing away the whole company to spend more money on Facebook's LLM technology, which might still never be good enough for them to actually make money at it. It made sense to do that work up to a point, because they could benefit from it internally for things like abuse detection. But trying to productize it without adequate rounds of funding is a mistake. If they truly think their tech is up to snuff, they should spin it off into a separate subsidiary and do rounds of financing to pay for the cost, with separate stock offerings.

Except it's not a concerning issue. Hantavirus doesn't spread well from human to human except when in close quarters (e.g. cruise ships). When you do the math based on the number of people on the ship, the likely R_0 would be *way* less than one out in the real world. So realistically, if they had evacuated the cruise ship after the first case, most of the people who got sick wouldn't have gotten sick, and you'd have at most maybe one or two cases in people who weren't on the ship, and that's about the realistic limit to its spread.

I don't remember the exact numbers I came up with, but it was something laughable like an R_0 of 0.15 or something.

It's a human interest story, because folks felt for the people trapped on that ship, but it was not a meaningful public health threat given the numbers involved.

It of course works to some extent. It doesn't work to an extent that it can replace a meaningful part of engineer time, though it can certainly be used for rapid prototyping and other special cases.

Most of engineers' time isn't spent writing code. It is spent reviewing code and understanding the code. When a person writes code, they are doing this while they write the code. When AI writes the code, that time is spent on the back end while reviewing the code. This is actually more mentally intensive than writing the code to begin with, because you're having to concentrate much more continuously. This means it takes longer, on average, and you're much more likely to make mistakes and miss critical errors during the review process, because you're trying to shove all of that mental effort into a much smaller amount of time. So you save a lot of time up front, and you pay back nearly all of that time at the end.

Until such time as AI can write perfect code that doesn't require human review, the review process will continue to be the bottleneck, and I'm not seeing any evidence that AI is approaching that point.

AI is great for creating demos that you're going to throw away and rewrite a dozen times. Teams that are playing with ideas for new features can potentially generate a lot more prototypes quickly by using AI. But they're saving time precisely because it's throwaway code. As soon as you're trying to use it for production code, the savings evaporate. Or at least this is what I have seen pretty consistently.

This is not to say that AI is useless for coding. When used as a glorified autocomplete engine, it can save you from a lot of tedious busywork. When used for code review, it at least has the potential to catch interesting bugs before they make it into production. And so on. But the notion that this will suddenly allow for cutting a large percentage of programmers is utterly naïve. Given their previous cuts, they've already exceeded the expected payoff from AI. So blaming this on AI savings isn't realistic.

So the real question is whether they'll be able to get their AI tech up to the quality and scalability level where they can survive on only that revenue before their social media platform craters from inadequate resourcing.

It's the dream of sociopathic greedy billionaires everywhere. Too bad for them that it's a pipe dream.

Here's the harsh reality: AI doesn't work. You can spend days cajoling AI into doing something correctly and spend days reviewing the bad code over and over until it gets it right or you can spend days writing the code. On average, the time savings are minimal, and the cost in terms of code understanding is enormous, resulting in less and less maintainable code over time until you eventually end up having to throw the whole thing away and rewrite it from scratch at an enormous cost.

Mind you, Meta was probably at the point where their whole code base needed to be thrown away and rewritten from scratch at least five years ago, given the level of bugginess that I've seen, so maybe AI lets them extend the long tail of badly written code a bit longer before they completely implode, but that's hardly a position for other execs to aspire to.

They won't. They'll have a bumpy few months followed by mass attrition from the complete destruction of employee morale, followed by panic when they realize that they don't have enough remaining employees to keep the lights on adequately, followed by even bigger panic when they realize qualified candidates aren't even bothering to apply for their open positions.

Nobody wants to work for a dying shell of a company that laid off a third of their workers over only a couple of years. As a company, if you're not innovating and growing, you're dying. Meta is dying. Their AI is basically worst-in-class at this point, and everything else is getting shoved aside to make more money for that latest boondoggle, because their execs don't know how to recognize a sunk cost fallacy.

It would take a literal miracle to save Meta from the death spiral that this will cause. If I owned Meta stock, I'd be selling in a hurry right now, or at least selling covered calls to buy protective puts to limit my losses. Stick a fork in it. They're done.

They drag them to school, but at that point, there's a record, and if it keeps happening, it becomes a legal problem for the parents, who have a responsibility for making sure their kids go to school.

To a school that is under-funded in part because kids aren't meeting the minimum attendance for the school to get paid.

All of those things are the responsibility of their parents. Those are adult problems for adults to solve. Kids can't realistically solve them, and can't reasonably be expected to solve them. And as soon as you let kids try to solve them, you're reinforcing the cycle of poverty by preventing them from getting the education that would enable to them to break that cycle. I'm not saying it's fair or good, just that preventing such things is better than the alternative, where we have child labor who grow up to be adults who earn minimum wage or worse.

Too bad they couldn't both lose. OTOH, Musk is as big a liar as Altman, so neither of their testimonies should be believed. Which make it hard to come to a just decision.

"drone"? What year are you talking about?

They weren't peaceful, but they were introverted. Now, as a matter of survival, they're doing their best to try to drag down everyone else.

So, yes, Damn Trump for provoking this.

That design assumed a dispersed network. The networks have gotten increasingly concentrated. If there's only one connection, you can't route around it.

OTOH, SpaceX might reap large increases in business, because they would be the only route that wasn't broken. (I don't think Iran has orbital capability.)

You're assuming that everyone is one extreme or the other. And not only is this wrong, there aren't only two sides, no matter what the news says.

OTOH, Flock *seems* to be an example of the "benefits of the surveillance state". I.e., we only hear about the generally approved of uses. If you were to believe that those were the only uses, I'd think you a simpleton. And it's impossible for me to make a decision that they're a good thing without knowing what those other uses are.

Chronic illness is rare, and at some point, you try to figure out a way to get the kid tutoring.

I see what you did there.

If half your kids are chronically sick, there's something wrong with your school — environmental issues like mold, social issues like bullying, or senioritis like Bueller.

Chronic absenteeism? When/where I was a kid, this was called truancy, and the police could pick you up for it. How is this still a thing?

Meh. If that is about their hiring practices, on principle I'd rather they be inclusive, but it isn't likely to destroy the quality of the product if they aren't. If it is a more general statement however — "We make our product available to everyone" — then that is a much bigger concern, because it could be an indication that the software might become a lot less available.

Personally, if I used their software, I'd be more worried about the transparency -> trust change. A company like that must be transparent, because if they aren't, you can't trust them. When I see a change like that, I read it as "Trust us. We aren't sending your passwords to the NSA."