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- Hacker News
- Deepseek is 90% cheaper, and nearly as good for coding tasks as claude/codex, and as good given the right plan.
The only moat OpenAI and Anthropic have is regulation. If the Chinese really eant to hammer us, they could realse the full training data and pipeline.
by a34729t - nearly as good but not nearly enoughby dango369
- Even without doing that the Chinese are already going to impact our labs presence everywhere else in the world. With Fable getting pulled, any model coming out of the US is now unreliable and untrusted. No one in any other country would in their right mind choose OpenAI or Anthropic for anything.
The big push for regulation and export controls is only going to ensure OpenAI & Anthropic are more like the automakers. Only in business because of protectionism, left to screw over US consumers meanwhile the rest of the world gets to enjoy cheap EVs
by thewebguyd - I don't have a crystal ball, but based on similar historical scenarios, I think that one or two of these companies will win--probably because of some unique application, delivery or trade secret that will drive 80% of their revenue.
Consider Google, Apple, Amazon, etc.
It's still early days...
by jschveibinz - I'm sure investors thought one or two of the ISPs laying all that fiber would be collecting fat rents on them until the sun burnt out. I'm glad they got so much in the ground before there was a reckoning. I hope this industry ships more very expensive models, ASAP.by kajman
- I'd guess Anthropic will probably win, and LLMs will probably still be with us and be much better in 10 years time.
But next year we could be in the middle of a massive $600B/yr capital-spending bubble deflating hard with unemployment accelerating towards 10% (or higher).
The internet never failed, but the telcom/dotcom collapse still happened in 2001.
by dualvariable - We're seeing the first 20 years of the dot-com cycle, but compressed into two years, and trying hard not to fall into the tar pit of ad-supported services.by sowbug
- So long as Chinese labs keep writing white papers, trade secrets aren't going to win the day.
Having growth up in the 90s, it is weird seeing companies share their technology secrets publicly.
by com2kid - The US govt is going to ban foreign models and foreign providers, and frontier labs are still cooked, because US companies will RLwash Chinese models to try and get in on the captive market. The frontier labs have already lost the war for coding, their next play is custom models for specific domains... Anthropic Galen for biomedical research, Anthropic Locke for legal analysis, etc, and you won't see _ANY_ intermediate work on the model, you will put in query, maybe get some questions fired back during work, and get a "final report."
Eventually the frontier labs will try to cut out the middle man once these models prove themselves and start doing partnerships with big firms in the domains, so they can take a % of the profits in perpetuity rather than just taking a one time payment. For example, after Anthropic Galen, they'll do a partnership with Pfizer to generate Ozempic-Superjacked and take 20% royalties on global sales.
by CuriouslyC - > Sales and Marketing: $5.73 billion .. That is, OpenAI spent 44% of their revenue on sales and marketing!
Anyone know what they are spending this on? Can't remember seeing one OpenAI ad.. Is it just pr and influencers? Ads in the US?
by gizzlon - Bribes and subsidies is my guessby chillfox
- I've easily gotten (low) hundreds of OpenAI youtube ads. More recently they've been pushing 'Free OpenAI Image generation' to me, in the past they pushed Codex more, but I have a sub for that now, so I guess it works.by shaewest
- Likely free tokens to attract customersby zyuiop
- If it actually was spent on ads, it seems to me OpenAI would have to be one of the single biggest ad buyers in the world. Almost certainly they are using a somewhat broad definition of sales and marketing to cram a bunch of expenses into it to make some other category look better.by 9cb14c1ec0
- The estimate that AI companies need to replace 27% of jobs to service their debt is interesting. But at least Anthropic and Meta seem to have their eyes on replacing software engineers.
There are ~1.6M software engineers on the US [0], earning a bit under 150k/year on average [1]. If AI companies captured all of that spend, that amounts to about 250B/year. The article assumed that they need around 300B/year to keep up with their debt.
At least based on Meta's recent behavior, forcing 30-50% of developers to switch to data labeling, it looks like that is actually their game plan.
[0] https://en.wikipedia.org/wiki/Software_engineering_demograph...
[1] https://www.indeed.com/career/software-engineer/salaries
by qnleigh - obviating software engineers is effectively AGI-complete and entails obviating most labor in existence .by whimsicalism
- The over investment by VC means that yeah, they are offering all of this below market rate. It's like Enron where they have to keep the scheme going, and dumping on retail investors is the only thing they can do now.
So we are going to go through a big IPO period. Everything will fall apart because VCs already extracted the growth value, and that will show up after the bag has been passed. Things will implode. What survives afterwards is what we will have.
by androiddrew - When we say below market rate, what do we mean? The token economics are definitely such that they are charging more than it costs to serve these models with reasonable assumptions on param/activated size.by whimsicalism
- Shouldn't we know a better answer to these questions once Anthropic's IPO materials surface publicly? I understand, and maybe even expect, SpaceX's materials to be all over the place and skate on by any discussion of unit economics, but the nerds over at Anthropic might just be forthright enough to just tell us what their margin is on tokens as part of their IPO.by knuckleheads
- Well it probably doesn't help that Dario is going around on podcasts saying things like "frontier labs need $1T of revenue or they will go bankrupt" lol.by steveBK123
- To be honest, making sense of finances of fully public companies is often hard, because in practice, accounting is hard. How you account for depreciacion, cost, investment, fixed vs marginal costs is in practice fluid, companies have an incentive to make it look attractive, while also optimising for tax and shifting revenue around to narrowly beat analyst recommendations.
Here's a concrete example. Does some random AI company make operating profit on inference? I.e. if you only kept marginal costs, would you make a profit?
Well, depends what you account as your costs. If you're using hand-me-down hardware from previous generation's training, how much do you charge yourself internally for it? Maybe you show less, so investors take solace in profitable inference, even if you're losing money overall. How exactly are you accounting for electricity costs between training and inference? Is your army of SREs mostly servicing training new models (R&D expenditure) or inference (operating cost)?
This even has a name, and is called the "big bath" approach. If investors expect one part of your business to be a fiscal black hole, just shove all your costs there. They are accepting of it, and you make the rest of the business look better.
I'm not accusing AI companies of cooking the books, rather I'm trying to highlight you could see all the cash flows and still not know how much money is made or lost where.
by rich_sasha - Lol I feel like no one has any attention span here. Tech shit is expensive in the beginning when it's new. It gets cheaper with time. This is a tech forum, don't we know this? Of course people overreact in both directions on both sides of the issue. It's a very fast technology, wait for things to settle before making grand declarations.by chermi
- Lots of stuff in the zirp era was cheap when it was new and increased in price over time though. Look at grubhub fees or etc.by nemomarx
- > Lol I feel like no one has any attention span here. Tech shit is expensive in the beginning when it's new. It gets cheaper with time.
The funniest comment here. Have you seen the prices of the technical shit for the past two years? Dang, GPUs are not getting any cheaper, but more expensive with each year.
by akazantsev - Yeah, but in the short-term there's $600B/yr of debt-financed depreciating capital investments waiting to financially blow up.
If you zoom out to the year 2100, it becomes a little pimple on the economy that is ready to pop, but in the here and now it can cause a lot of damage to real people's wages and finances over the next 3 years.
by dualvariable - The unit economics might be just fine. We'll know more after IPO.
The drug dealer analogy has a darker side to it, however.
Once your dependent, they can drive up the price just because. It doesn't need to be for existential reasons.
by fny - It's a really different market, though. New entrants can easily undercut them if they price too highby airstrike
- I'm finding it challenging to believe they wouldn't just cannibalize anything dependent on them in that way or at minimum launch a directly competing product.by chrismarlow9
- AI is a worker for me. That i pay for. Basically i am in the same game now to reduce the prizes i have to pay for my workers. Just like the employers are, that seek to reduce costs for employees, as we are simply too expensive. We need more competition among the workers. Let's introduce more chinese workforce! ;)by okr
- The dependent idea is questionable- when your boss tells you to not use the most expesive models-you just dont
I would assume when price hikes happen either 1) less non technical people would vibecode as it doesnt impact the work that much 2) people use the cheaper chinese models 3)we're jamming ai into everything because were exploring. We will just niche down into use cases that provide high roi
by JimsonYang