16,689 karma · joined October 20, 2010
One would imagine Meta can readily quantify how much AI-generated content is consumed across its properties.
Meta's play is simple: more engagement means more money for Meta, and this can be done by "slop" as you called it, or alternatively expanding the audience of high quality human-generated content, say via translation. A funny video in Albanian is probably still very funny after being translated to English.
Their day-jobs at other various Musk enterprises.
>> which distro(es) would be available?
> None
Me: there's Ubuntu 24.10 build specifically for Snapdragon X Elite ARM computers
You: that distro is buggy
Me: but it exists, because Qualcomm mainlined code to Linus' kernel tree.
1. https://discourse.ubuntu.com/t/ubuntu-24-10-concept-snapdrag...
You were - and are - wrong. Qualcomm mainlined enough drivers for in the same window (past 6 months) so one can boot and install the latest Linux kernel on several Snapdragon X laptops from different OEMs. There are people running Fedora and an Ubuntu Experimental[1] builds. Its still rough, depending on ones device tree, the peripherals line microphone, webcam, and/or fan control may not work right now, but it's a platform that's actively being developed for.
1. https://discourse.ubuntu.com/t/ubuntu-24-10-concept-snapdrag...
I'm grateful the kernel still supports MIPS, which means an old appliance of mine still works perfectly fine and is upgradable. I would be cery sad if someone were to rip-out support of an old MIPS arch, just because it's old and unwieldy
Don't get high on your own (industry's) supply. This foward-looking BS is targeted at clueless investors, Level 5 self-driving cars have been a "few years away" for almost 2 decades now, and here we are, still having to deal with ADAS like cavemen, and looking back at the trail of dead companies that believed they could solve self-driving.
Are the current economics viable indefinitely? I think not. This AI investment exuberance will be curbed as soon as investors start demanding returns, and we've already seen harbingers of that (the Deep Seek market scare). What appears to be a quadratic growth curve inevitably turns out to be sigmoid.
Right now, the Hype train is at maximum speed and seems unstoppable. Despite the early hype, the Internet didn't replace colleges or brick and mortar stores[1], iPads didn't kill computers[2], and AI won't replace software engineers. This is not to say there will be no impact, but it's being oversold.
1. Khan academy and Amazon notwithstanding. But physical retail stores are still here and doing okay, and have adjusted to leveraging the new paradigm.
2. Leading up to peak iPad, it was believable that the iPad would kill PCs - it was an unstoppable juggernaut lifting Apple profits to record heights https://www.bloomberg.com/news/articles/2012-03-21/ipad-the-...
They do not - not definitively [1]. This cat-and-mouse game is stochastic at higher levels, with bots doing their best to blend in with regular traffic, and the defense trying to pick up signals barely above the noise floor. There are diminishing returns to battling bots that are indistinguishable from regular users.
1. A few weeks ago, the HN frontpage had a browser-based project that claimed to be undetectable
Additionally, the US has been vociferous about limiting access to foreign tech companies with "military links" in China, so perhaps Google should be placed in that category by all non-Five-Eyes countries.
I feel the same
> That’s very painful for me. At that point I’d rather just write the code once, correctly.
I use AI tools augmentatively, and it's not painful for me, perhaps slightly inconvenient. But for boiler-plate-heavy code like unit tests or easily verifiable refactors[1], adjusting AI-authored code on a per-commit basis is still faster than me writing all the code.
1. Like switching between unit-test frameworks
Only when someone discovers another paradigm that matches or exceeds the effectiveness of LLMs without being a language model.
...and yet with it's flaws, it's the most flexible in conveying meaning. A Ted Chiang interview was on the HN frontpage a few days ago, in it, he mentions that humans created multiple precise, unambiguous communication modes like equations used in mathematical papers and proofs. But those same papers are not 100% equations, the mathematicians have to fall back to flawed language to describe and provide context because those formal languages only capture a smaller range of human thought compared to natural language.
This is not to say chat has the best ergonomics for development - it's not, but one has to remember that the tools are based on Large Language Models whose one-trick is manipulating language. Better ergonomics would likely come from models trained or fine-tuned on AST-tokens and diffs. They'd still need to modulate on language (understanding requirements, hints, variable names,and authoring comments, commits and/or PRs).
If it wasn't, he made it real. Elon is the deep state. An unelected individual who has set up a no-oversight machinery with hands on the levers of state power, and using them to his own ends, independent of public benefit. Every accusation is a confession.
Save tens of hours in one commit?! No model is this good yet[1] - especially not Aider with its recommended models. I fully agree with parent - current SoTA models require lots of handholding in the domains I care about, and the AI chat/pairing setup works much better compared to the AI creating entire commits/PRs before a human gets to look at it.
1. If they were, Zuckerberg would have already announced another round of layoffs.
He thought raking forests would prevent fires. His off-the-cuff solution to physical barriers would be long hoses and a bunch of water pumps.
Yes. Humans can also self-evaluate about their state, and have culpability. It not surprising that non-humans are held to a different standard.
Not very. For safety-critical systems, you probably want something deterministic, and doesn't break when faced with novel situations.
Solvers are probably a better solution than ML approaches, but they can't capture every possible constraint, such as airplane that can only make left-handed turns because of equipment failure.