twelve40

> doing so well right now

lol quantitatively well

This is really a matter of taste, but i (personal opinion) think that Zuck, Karp, Thiel and others who (partly by sucking the inauguration dick) have the ear of the current powers that be, produce much more demented shit than Musk. But the exact personalities really don't matter, the whole jolly crew running the show does not seem very humanistic in their writings or actions.

weird bias by authority aside, do you really think that the daily decisions in this world today, and anytime soon, will be made based on the "let humanity flourish axiom"?

the author right in that post pitches his ideas as generalizable way beyond math, so why the snobbery?

> We (humans) should help humanity flourish. I understand that not everyone agrees. I have been called a “speciesist” for being “too human-centric”.

this is insane. the "speciesist" people aside (the best way for all other species to flourish is for humans to eradicate themselves right now, which is completely mad), i have the opposite problem: the _axiom_ seems to be: we should help ME flourish. "Me" as in people who are raking in trillions for their own very special selves right now, at the cost of everyone else's future, while none of them can be trusted to hold my cell phone for a second.

> if an industry commits to the axiom of helping humanity flourish

where does he see such industries, outside of maybe nonprofits?

the problem is these things are meant to eventually be run everywhere by everybody, so what good does air-gapping do? If they air-gapped the model but still logged it trying to do some craziness - that makes the test safer but not the model.

there is hype for sure, but i don't get what is the goal here? to get a presumably foolish senator to "ban" the Chinese models? how can you "ban" something you don't control to begin with?

side note, i'm very curious why the Chinese companies currently give those away (some handwavey conspiracies like getting the world hooked on evil Chinese tech don't really explain that, and they also don't make any money off that stuff)

> gives the military a way to cover

it's not like they didn't just sweep crap under the rug before AI.

did Colin Powell go to jail for lying to the UN? of course not. did Colin Powell go to jail for smuggling anthrax into a UN meeting? of course not. he just blamed it on "being misled by bad intelligence". Did anyone go to jail for that bad intelligence? of course not.

But we had to pay through the nose for decades of this shit in Iraq and Afghanistan (hundreds of billions), all for absolutely nothing. Did anyone even explain why the fuck, or was held responsible? of course not. They don't need AI to just ignore shit.

Yes, that's going on optimism. It's also possible that we're 80% there and the rest will take forever, while the loans and investments were taken out now.

the decision i have to make dozens if not hundreds times a day: do i actually look at this crap or trust it blindly and let it slide? I'm honestly reading maybe 20% tops of what "I" produce (and what other people post for my review) I think you do lose skills and understanding that way. Sure, you can always ask the robot to do the tldr for you, but.... yeah, something is still lost, not in a good way.

yes, but at that point even open weight models are not free. Can someone set up the best open-weight model for free and charge pretty much just for GPU usage+operations+margin for inference? yes. But they would have to keep up with how good the private models are. The bet is private models would sell in a similar way at a premium and invest in staying ahead. Is this bet going to work? no idea, don't shoot the messenger.

but this crap may take forever to play out even if the outcome is well-known. Self-driving is "here", it's obvious that once it's cheap enough having a human behind a car wheel or a freight truck wheel is an absurd waste of human life (kinda like digging canals with bare hands instead of an excavator), yet truckers and uber drivers are still employed. But everyone knows the writing is on the wall for them.

coding on a laptop is only one use case

you can't create a new drug by running a model on a laptop. You can't serve a customer support bot running on a laptop. You can't generate video in bulk for many users on a laptop. So there is still a case for paying others for inference.

Does it justify the valuations? No idea, but some major use cases are still there. That's why they are rushing to implement, OpenAI creating a "deployment company", Anthropic having some pharma rumors, etc.

It seems like the endgame is to amass absurd amounts of hardware and produce something that will replace you the baker entirely

everything else we see today is just preparing for it.

> Who pays for that? Not the data center

uh... how? they do pay for what they use.

data center = girlfriend bots = meth lab is a pretty wild connection to make.

this is really something. They claim (no idea if true) to have patched 4,000+ signals in 550+ C++ files in Chromium. coveryourtracks.eff.org uses like what, 25 signals?

it's a very handwavey way to "explain" anything. Yes, they make money. But they have competition. And if someone runs out of tokens and switches to deepseek or just goes for a friggin hike in the woods, that does not benefit them. If they get a public image of a ripoff that burns all shit on trivial tasks, that does not do them good either. So there is a limit to this "companies make money" thing.

but then you end up with a clusterfuck of classes?

So the federal government industrial policy is the thing that supposedly will keep the prices on "A and O" high in the US while the rest of the world will get comparable AI competing to get cheaper and cheaper?

> why should someone pay that business to solve whatever problem it solves instead of also getting the AI to solve it?

well because presumably even in that brave new world, solving the problem with AI is still not trivial, even if it requires just one person. If a potential customer wants to solve it themselves instead of buying, they would have to find the right person, invest in his time and tokens, and end up with a custom solution they'd have to support.

this is a bit... general? there are companies with bullshit executives for sure, then there are companies who slay it.

i hate to list the details because people start picking on details, but in my mind MS under Satya made a 180 from crap to relevant. All the while i realize what kind of shit goes on inside and if you read Blind your eyes will bleed. Yet Satya took it from a pure 100% bullshit executive and made it relevant. So not all executives are equal.

isn't it an attempt to give structure to something that surely would have existed illegally otherwise? banning something doesn't automatically stop it.

well, there _is_ this:

https://en.wikipedia.org/wiki/Outer_Space_Treaty

"bars states party to the treaty from placing weapons of mass destruction in Earth orbit, installing them on the Moon or any other celestial body, or otherwise stationing them in outer space"

but 1. today's sentiment is: to hell with these treaties-schmeaties, and 2. what you mentioned is not yet a weapon of _mass_ destruction, so we're all good!

well China debate aside, where are they? i've been dabbling in electrics for over a decade now, on the lower range they are still 30% more expensive than gas cars. Surely someone, anyone outside of China could have done one cheaper by now? Leaf came out 16 years ago and they still can't get it under $30k?

no idea how spotify ai specifically works (i don't use that service) but:

> fitting the track into the set as a whole. It’s not a random music discovery process

there have been plenty of attempts to analyze music and to automate track matching like the music genome (going back to '99) and while human DJ's definitely have their place (i actually listen to lots of those) it's not inconceivable that a lot of modern music could also be mixed and matched automatically with at least half-decent (to a human) results.

P.S. found the article itself pretty funny - like a nerdy, methodical complaint, just funny to read

there are plenty of amazingly lucrative businesses that do really well, like online casinos, tobacco companies, etc. that happily milk their users and don't bother with improving human condition. You can call that "successful product strategy" i guess, but to me that's still pretty repulsive. You can also call this hyperbole, but i really am very much repulsed at this: increasing addictiveness for the weak minds to extract more revenue.

yeah my teammates seem to enjoy checking in endless walls of MD texts of "documentation" generated by llms after it's done adding a feature. So even if that's an extreme and your documentation is more thoughtful, there is still a problem of:

* redundancy with the code: if code samples can be generated from the code, why bother duplicating them? what do they add? can they not be llm-generated later? and possibly kept somewhere out of the way (like, a website) so as not to clutter the codebase with redundancy

* if you do go for this duplication, then you are on the hook for ensuring it's always up-to-date otherwise it becomes worse than duplicate: misleading

So my preference is, when adding something to the repo, think very hard whether this information is redundant or not. Handcrafted docs, notes, comments that add more context like why was this built that way after a ton of deliberation - yes. Anything that is trivially derived from the code itself - no.

i don't know what i'm doing wrong but my mac has terrible time recognizing any USB-C headphones. First, it takes a while to recognize, then it never switches over by default so i often end up blasting on speakers if i forget that it's oh, USB-C headphones. Same confusion on Zoom. At the same time, Mac's 3.5mm just works, instantly.

But i realize that it might be hard to have 3.5mm on phones due to insane amount of size optimizations on these sophisticated devices we kind of take for granted by now.