...in the hands of a competent, careful and passionate programmer like Linux Torvalds.

What I worry about is when Bob in the junior software dev team, who does his job to put food on the table, and just good enough to keep his job, uses it to vibe-code company data as his day job.

Well, to get technical, they switched from using the Discrete Cosine Transform algorithm to the Obese Conspicuous Fattening algorithm.

I'm not an information theory guy, but I thought compression were supposed to make things smaller. Sounds like JPEG ate a bunch of donuts instead. Get it on Wegovy/GLP-1 inhibitors ASAP.

Though already CI/CD pipelines were choking on the unit tests. So they aren't *free*.

Had an LLM generated request that was pretty straightforward, and the LLM generated 272 unit tests for a very simple function. Can't really afford that.

Also, despite the 272 unit tests, when I tried to try it out in the way a human would, it immediately failed. All the mocking the AI generated never actually properly imitated the real world. However, the submitter was *quite* proud of having hundreds of unit tests, despite them being, in this scenario, utterly worthless.

Like always, more code != more valuable software behavior.

So you have the AI doing overtly silly things. Someone asked to adjust layout to fix a gap in a webpage. Eventually they submitted their pull request, hundreds and hundreds of lines of CSS. Often the exact same rule repeated 5 times, which I'm guessing is how many rounds the operator went with the system before the gap actually closed. The lines were *mostly* just '!important'ing already existing rules, which had no impact, but hey, worth a shot right? Ultimately I discarded the merge request and made the one-line css tweak that was actually relevant.

Then you have the AI doing... well arguably slightly silly things. Like protecting against an invalid value redundantly throughout a call stack. Arguably defensible, as maybe one day the deep function will be called from somewhere else and passing through the error might not present it with the most informative context.

Finally the AI doing... well things the human should have been doing. With the advent of a lot of code scanning, this is less likely, but things like calling functions in C and charging ahead without ever checking the status of the call. functions that, practically speaking, will likely never fail, however you really *should* be being more defensive about the possibility.

The 'human review as a bottleneck' isn't really the angle I would fixate on. Completely unfettered AI usage also stalls out in many situations. If the AI can't get there on its own trivially, then it's going to leave an almost-correct looking mess that isn't quite there but is very hard to get across the finish line. If the AI can get it, then it's probably not 'software being shipped', because while perhaps slightly better than a generic off-the-shelf existing procedure, probably not worth the trouble to 'ship' a solution that largely overlaps with a lot of generic stuff.

Lift the tariffs you morons.

Everyone knows that pretty much by definition volumes are low, that's the whole definition of a shortage.

The vendors may still be happy, perhaps even happier if the sky high prices produce at least as much revenue at high margin.

https://www.youtube.com/watch?...

I'm with you, but realistically speaking, if the mindset is already there, the material was likely already at high risk of plausible nonsense, not as thought out as the reality, but something to satisfy a check box for someone else. And the hope for process improvement is frequently not there, as raising a "do we really need to do this" invites "you must not care about safety/security/whatever". In many scenarios *no one* wants to be potentially on the hook for approving a process optimization that ends up biting them because they didn't understand why those things were in the process. Even if it is patently obvious to all involved there's no point, or if there was it was already failing. Frequently process dictated by someone that has no *real* stakes in anything involved, but needs to be performative.

The GenAI approach is the way to pay lip service and skip the debate. And if something messes up? "Ooops, well you know how AI just does that sometimes". I've seen that *so many times* and people just laugh it off and keep slopping and no one is holding folks accountable for failing to audit the AI results adequately. So they get credit when the slop works, and they deflect blame when it doesn't.

It *sounds* like they are using it for generating bureaucratic material.

Certainly comparatively speaking the stakes are just so much lower, but I've seen a bit of that in my company.

In my case, it's material that generally no one reads, or maybe someone that doesn't matter. GenAI has become a way for people to tick the checkboxes that they think don't matter without trying to debate the reason for the checkboxes.

Suppose the question is whether or not some token gesture facilitated by the GenAI *actually* matters but it's easier to "AI it away" than actually hash out that detail. Does it facilitate people who "I know what I'm doing, just let me do what I know is right" proceed without adequate and accurate oversight. Or is it the case that these situations were already ineffective at oversight, but effective at having whatever would have happened either way just happen in slow motion.

Buy a Tesla instead. Full self-driving is amazing.

Great idea!

Just one small question, what thing else?

In three years, we should allow AI to become the largest supplier of military computer systems.

Once all nuclear power plants, along with stealth bombers are upgraded with AI computers, make them fully unmanned.

Afterwards, let's see if they have a perfect operational record.

Then, pass the AI funding bill.

The system can go online, maybe on August 4th, 2037. Human decisions can then be removed from all control of nuclear assets and strategic defense. The AI can then be free to learn at a geometric rate.

If it does become self-aware at, say 2:14 a.m. Eastern time, August 29th. We can in a panic pull the plug.

64 seconds ought to be good for anybody. Especially if the website is running node JS the certificate can expire midway during library download.

The problem isn’t how bright headlights are. It’s how concentrated that brightness is.
Think about the sun behind a cloud. The day is still bright. You can see everything. You can even stare directly at the cloud without your retinas filing a formal complaint. That’s because glare isn’t about total light output — it’s about how much light is crammed into a tiny area. Spread the same amount of light over a bigger surface and it stops feeling like an assault.
You could cover an entire car’s front end with LEDs and use a light diffuser panel/sheet to spread out brightness and light up the road just fine, and it wouldn’t feel like someone’s aiming a laser at your face. The issue is when all that light is squeezed out of two little headlight-sized holes. At that point it stops being illumination and starts being a portable sun that only comes out at night and specifically hates your eyes.