81–90 of 557 posts
HN is no longer a reliable place for the truth. Quite frankly, unless you are utterly self educated, you are terribly vulnerable to this place. At this rate, I’d almost prefer to talk on a private mailing list with vetted resumes.
"No longer?" It never was.
Especially with AI boosters being allowed to degrade the comments section and shilling their paid blogs and violating the HN guidelines.
Earlier quoted context omitted.
If they shut down all training today they’d be absolutely printing money for the next couple quarters and then die with a bang once the other lab releases the next frontier to the public.
How? They're already burning $2 bills to make $1, court documents shown that Anthropic has already been lying around revenue (claimed to have made $19 billion when it's actually $5 billion to date [1]). Not hard to believe they're lying about other things when they've been lying about the capability of their products since inception. [1] https://www.reuters.com/commentary/breakingviews/anthropic-g...
It’s incredible how polarizing the AI rush is. I keep the perspective that the technology is an absolute step change but I have no idea where the cards will fall. I take a lot of issue with these style of articles. I get a sense that the authors are being overly defensive. The cost to serve tokens is absolutely profitable today and that’s been true for at least a year. What’s unclear is how R&D and capex fit into the…
> The cost to serve tokens is absolutely profitable today and that’s been true for at least a year. > For the data center build outs, demand for tokens is still exceeding supply. Can you provide any numbers for this?
> RAM prices are crashing because new models won’t need as much Reality begs to differ [0] and following the link for that text goes to an article [1] where they talk about Google's TurboQuant which supposedly will lower the RAM requirements. Now if that means RAM prices come down (as speculated, not reported on, in the link) or the AI companies just do more things with their extra ram is yet to be determined. The fa…
The recent blog post from Google announcing TurboQuant does not change anything regarding RAM planning for the big labs.
TurboQuant itself is already a year old! So even smaller labs have probably seen and implemented it.
From the beginning of this I’ve wondered the same question: how do these companies justify spending such massive amounts now (and 3 or 4 years ago) when software and hardware efficiencies will bring down the cost dramatically fairly soon? They basically decided that scaling at any cost was the way to go. This only works as a strategy if efficiency can’t work, not if you simply haven’t tried. Otherwise, a few breakthr…
You cannot find the efficiency if you haven't been experimenting at scale, this is true personally as well.
If someone haven't been burning a few B tokens per month, everything coming out of their mouth about AI is largely theory. It could be right or wrong, but they don't have the practice to validate what they're talking about.
Not everyone scaling to that degree would have the right answer or outcome, many would be wrong and go bust. But everyone who didn't will not have the right answer.
I just dont understand why it justifies so much spending!
It’s incredible how polarizing the AI rush is. I keep the perspective that the technology is an absolute step change but I have no idea where the cards will fall. I take a lot of issue with these style of articles. I get a sense that the authors are being overly defensive. The cost to serve tokens is absolutely profitable today and that’s been true for at least a year. What’s unclear is how R&D and capex fit into the…
> The cost to serve tokens is absolutely profitable today and that’s been true for at least a year. > For the data center build outs, demand for tokens is still exceeding supply. Can you provide any numbers for this?
This is why switching to local open weight models saves a lot of money. (Even though it’s not apples to apples.)
History doesn't have to repeat. There's barely anything else going on in terms of innovation, and AI is a real step function technology. We might be overspending but there's no way we're getting another AI winter like last time (remember last time investment in 90s AI had to compete for resources with the internet boom).
This is high up there on the list of things people say before, you know, it does
> RAM prices are crashing because new models won’t need as much Reality begs to differ [0] and following the link for that text goes to an article [1] where they talk about Google's TurboQuant which supposedly will lower the RAM requirements. Now if that means RAM prices come down (as speculated, not reported on, in the link) or the AI companies just do more things with their extra ram is yet to be determined. The fa…
Honestly you're both wrong. RAM prices spiked speculatively, and they're going down for the same reason. Market people always want to argue in fundamentals, when in practice *ALL* the high frequency components of the signal are down to a bunch of traders trying to guess where it's going in the short term.
At best those guesses are informed by ground truth ("AI needs a lot of RAM!" "Sam cornered the marked!" "TurboQuant needs less RAM!"), but they remain guesses, and even then you can't tell the difference between that and random motion.
It's a winner-takes-all market and everyone wants to be the next Google and not the next Lycos or AskJeeves etc. It'd be interesting to see what they spend all the money on though as we seem to be hitting diminishing returns and I'm not sure if the typical enterprise user really cares about small improvements on benchmarks. It seems like it'd probably be better to spend all that on marketing, free trials, exclusivity…