HighGoldstein

> but I also assume that there is very little training data available for Smalltalk.

Is this actually an issue? I was under the impression that the conclusion was that LLMs will invariably be terrible at writing good, working code (since their training sets are 90% garbage produced by humans), hence why agentic development now is heavy on verification tools and other software that can signal to the LLM whether the code works and has any code smells. Also why AI agents nowadays seem to write and execute scripts for a lot of tasks instead of spitting code directly. Hence, the volume of training data shouldn't be as relevant as it used to be.

"I prefer Claude Code, so it must be the best"

Truly a developer mindset.

Software engineers in a good chunk of Europe/US/Canada/Australia make 6 figure salaries, of course they can easily afford an iPad Mini.

Wasn't the whole point of Fable that it's Mythos but with all the cybersecurity stuff lobotomized out of it?

They also took the correct path for hundreds of other problems, where they didn't have a user that already did.

> Our TranslatePod Pros will automatically translate every language in real-time.

Wasn't this the utopian ideal of the Star Trek Universal Translator? Is it good when Gene Roddenbery writes it as utopian sci-fi, but bad when the AI people make it a reality?

> What benefit are AI generated images to an AI?

Apparently quite a bit as long as you're not indiscriminately feeding random slop back in. An AI-generated artifact deemed "high quality" or somehow desirable by humans is a good training input depending on what you're trying to do. Humans don't train exclusively on external inputs either.

This may look intuitively obvious, but the current shortform video situation probably would've looked like dystopian sci-fi to someone in 2010.

"Do people really want to be seen making using Java part of their personality?"

Has it? The i7-5960X was 8C/16T, Ryzen 9 9950X (and variants) are 16C/32T. Even the Threadripper PRO 9000 WX is 96C/192T and supports a staggering 2TB of RAM.

How so? Memory bandwidth and capacity has been steadily increasing. On desktop for example, 10 years ago an i7-5960X was the absolute top of the line and it had a limit of 64GB, with most motherboards in practice being limited to 32-48GB, and this was an unthinkable amount of RAM at the time for desktop. Now the top end desktop chips support 192-256GB, and a year ago (before the RAM price spike) you could realistically buy that much if you wanted for a reasonable price.

Watch as memory manufacturers learn nothing from the car industry, and cry for tariffs when the Chinese inevitably annihilate them.

I think we are still far from nailing down good LLM benchmarks, because the more general-purpose your software the harder the question of what makes it good becomes. Is Python a good programming language? Is Java? Is C? I think it's a similar class of problem. You can benchmark rudimentary things like execution speed similar to how you can benchmark tokens/second, but these metrics don't tell the whole story.

The average person already does this with obvious AI slop.

> In practice, KYC does little to stop any of that

Source? The fact that it's not infallible doesn't mean that it's ineffective.

Not every tech worker is making top-tier US salaries. For some (I suspect not few) people on HN that $20,000 Mac is almost a year's salary.

"You say we should improve society yet participate in it, curious"

I find it somewhat funny that the author starts by talking about how Moore's law enabled inefficient software and that we then had to make it more efficient, when almost all software today is horrendously inefficient compared to even 10 years ago, let alone 20-30. We've somehow even achieved a state where it doesn't matter how fast your CPU and memory are, the software will just perform horribly on any machine.

Inefficient allocation of work aside (where you end up with people doing nothing, despite I suspect a substantial amount of work in the backlog), I think the mindset of "just reduce devs so there's not so much context switching/they can own more" is short-sighted from a business perspective.

Even in projects that could objectively be owned by 1-2 people but are allocated to a 5-10 person team instead, I've encountered cases where velocity gets absolutely obliterated by a sub-domain "owner" dev being on vacation. Now imagine this is not a fairly small sub-domain but half the project, and instead of a vacation your one-of-two dev gets hit by a bus.

Can you elaborate?

Do you believe half the human population should have the same rights as the other half? I'd say this is rather basic, yet the subject of much disagreement.

The EU isn't monolithic, you could probably do this fairly easily in someplace like Poland where there isn't a bureaucratic hell and a large supply of skilled workers and engineers. But of course, Poland and co. are the "lessers" in Europe where you outsource for cheaper labor, a prestigious thing like a cutting-edge chip fab would need to be built somewhere like Germany or the Netherlands, and so it never shall exist.

Decade? We're 4 years in since ChatGPT released publicly and have gone from "Wow this thing is stupid" to running coding agents on auto mode, and the Chinese labs have been around for even less time. The US providers may lose dominance in 1 or 2 years.

> Do. Not. Buy. LG.

> There are a lot of decent alternatives.

Can you name them? Dell and Samsung are the main competitors for displays as far as I'm aware, Dell tends to be hit-or-miss when it comes to monitor features and quality, Samsung's high end displays come preloaded with a whole OS. The monitor market is really in the toilet.

The PS5 (which is realistically the main competitor) has the caveat that to get even something as basic as multiplayer you need to pay a $10-20 monthly subscription, so you can multiply that by however many months you plan to own it and add it to the price.

At some point I was thinking that maybe I am too hard on the AI and that humans routinely produce exceptionally stupid code, however after a while I've realized that this is only partially true. AI produces a class of mistakes that humans would almost certainly not make because creating even the context of the mistake would require a level of skill that would preclude such mistakes. It's like if you took a mid/senior engineer and randomly lobotomized them mid-task.

Yes, which goes in line with the argument that claiming that it's "the most deployed" as proof of superiority or suitability for any use case is equivalent to claiming the same for Internet Explorer. It's the most deployed because it's bundled in a lot of systems, not because people are purposefully using it as a DBMS.

The reason SQLite is the most deployed is that it's used by Android.

Sandboxing doesn't necessarily mean isolating the extension from all potentially dangerous functions, you can have a permission system so that for example a color theme extension can't modify files.

Considering how many AWS and non-AWS services go down at least partially when us-east-1 fails, this reads somewhat like "Don't worry that the steering wheel and pedals aren't working, your engine is still running on cruise control".