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Anthropic raises $13B Series F

anthropic.com

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Re: Anthropic raises $13B Series F

#631

Post by lelanthran »

tick_tock_tick wrote: post #630
lelanthran wrote: post #629

Earlier quoted context omitted.

> Just your GPU not counting the rest of the system costs 4 years of subscription With my existing setup for non-coding tasks (GPU is a 3060 12GB which I bought prior to wanting local LLM inference, but use it now for that purpose anyway) the GPU alone was a once-off ~$350 cost ( https://www.newegg.com/gigabyte-windforce-oc-gv-n3060wf2oc-1... ). It gives me literally unlimited requests, not pseudo-unlimited as I get…

> does it matter if you generate at half the speed? Yes, massively it's not even linear 1/2 speed is probably 1/8 or less the value of "full speed". It's going to be even more pronounced as "full speed" gets faster.

> Yes, massively it's not even linear 1/2 speed is probably 1/8 or less the value of "full speed". It's going to be even more pronounced as "full speed" gets faster.

I don't think that's true for most use-cases (content generation, including artwork, code/software, reading material, summarising, etc). Something that takes a day without an LLM might take only 30m with GPT5 (artwork), or maybe one hour with Claude Code.

Does the user really care that their full-day artwork task is now one hour and not 30m? Or that their full-day coding task is now only two hours, and not one hour?

After all, from day one of the ChatGPT release, literally no one complained that it was too slow (and it was much slower than it is now).

Right now no one is asking for faster token generation, everyone is asking for more accurate solutions, even at the expense of speed.

Re: Anthropic raises $13B Series F

#632

Post by reissbaker »

Barbing wrote: post #426
bcrosby95 wrote: post #291

Earlier quoted context omitted.

I think you're really bending over backwards to make this company seem non viable. If model training has truly turned out to be profitable at the end of each cycle, then this company is going to make money hand over fist, and investing money to out compete the competition is the right thing to do. Most mega corps started out wildly unprofitable due to investing into the core business... until they aren't. It's almost…

Thoughts on Ed Zitron’s pessimism? “There Is No AI Revolution” - Feb ‘25: https://www.wheresyoured.at/wheres-the-money/

Ed Zitron plainly has no idea what he's talking about. For example:

Putting aside the hype and bluster, OpenAI — as with all generative AI model developers — loses money on every single prompt and output. Its products do not scale like traditional software, in that the more users it gets, the more expensive its services are to run because its models are so compute-intensive.

While OpenAI's numbers aren't public, this seems very unlikely. Given open-source models can be profitably run for cents per million input tokens at FP8 — and OpenAI is already training (and thus certainly running) in FP4 — even if the closed-source models are many times bigger than the largest open-source models, OpenAI is still making money hand over fist on inference. The GPT-5 API costs $1.25/million input tokens: that's a lot more than it takes in compute to run it. And unless you're using the API, it's incredibly unlikely you're burning through millions of tokens in a week... And yet, subscribers to the chat UI are paying $20/month (at minimum!), which is much higher than a few million tokens a week cost.

Ed Zitron repeats his claim many, many, excruciatingly many times throughout the article, and it seems quite central to the point he's trying to make. But he's wrong, and wrong enough that I think you should doubt that he knows much about what he's talking about.

(His entire blog seems to be a series of anti-tech screeds, so in general I'm pretty dubious he has deep insight into much of anything in the industry. But he quite obviously doesn't know about the economics of LLM inference.)

Re: Anthropic raises $13B Series F

#634

Post by xigoi »

atleastoptimal wrote: post #562
pimlottc wrote: post #399

Earlier quoted context omitted.

Remember when you could get an Uber ride all the way across town for $5? It is way too early to know what prices for these services will actually cost.

Is there an open source Uber? There are multiple open source AI models far beyond what SOTA was just 1 year ago. Even if they don't manage to drive prices down on the most recent closed models, they themselves will never be a trivial amount more than the compute they run on, and compute will only get more expensive if demand for AI continues to grow exponentially, which would likewise drive prices down due to competi…

> There are multiple open source AI models far beyond what SOTA was just 1 year ago.

There are many models that call themselves open source, but the source is nowhere to be found, only the weights.

Re: Anthropic raises $13B Series F

#635

Post by tim333 »

sdesol wrote: post #605
tim333 wrote: post #601

Earlier quoted context omitted.

I'm not sure many investors are investing their own money. They are investing other people's money, maybe owned by shareholders of large companies in turn owned by our pension funds.

It might not be their money, but they are paid a management fee and if they cannot provide some return, people will stop using them.

The kind of thing that happens is Joe Bloggs runs the Fidelity Hot Tech fund, up 50% over the last three years. Then when it crashes that's closed and Joe is switched to the Fidelity Safe Income fund with no down years for the last five years.

Re: Anthropic raises $13B Series F

#636

Post by ryukoposting »

simgt wrote: post #588
ryukoposting wrote: post #231

Earlier quoted context omitted.

This is roughly where I am on the matter. If the energy costs stay massive, your investment in AI is really just a bet that energy production will get cheaper. If the energy costs fall, so does the moat that keeps valuations like this one afloat. If there's a step-function breakthrough in efficiency, it's far more likely to be on the model side than on the semiconductor side. Even then, investing in the model compani…

Yeah. Electricity production that we also need for electrifying all of our transports and industry because of climate change. Good luck getting that cheaper. That said innovation on the model side is more likely to come from a 10B-funded startup that still has some money to spare on the brightest researchers on top of giving them all the data and compute they want to play with.

I was thinking about this last night, and I find it amusing. Imagine investing in a company because it has money... your money. That you invested.

Re: Anthropic raises $13B Series F

#637

Post by tedivm »

DSingularity wrote: post #599
tedivm wrote: post #375

Earlier quoted context omitted.

This is only if you ignore the growing open source models. I'm running Qwen3-30B at home and it works great for most of the use cases I have. I think we're going to find that the optimizations coming from companies out of China are going to continue making local LLMs easier for folks to run.

What hardware do you use ?

I have two 3090s, but I'm only using one for this model.

Re: Anthropic raises $13B Series F

#638

Post by mlyle »

cjbgkagh wrote: post #628
mlyle wrote: post #614

Earlier quoted context omitted.

Almost anything has a utility scale which is diminishing. But we still see MR=MC pricing in industries with barriers to entry (IPR, capital costs). TSMC and Mercedes don't price cheap to avoid giving others a toehold. > There is a natural monopoly aspect given the ability to train and data mine on private usage data but in general improvements in the algorithms and training seem to be dominating advancements. There's…

I’m unconvinced that the lessons learned from scaling will constitute much of a moat. There is certainly an incentive for incumbents to give such an impression.

Probably not. But we don't tend to see P=MC where there's any differentiation or barrier to entry, and I do not believe that AI is fully commoditized or will be soon.

Re: Anthropic raises $13B Series F

#639

Post by sidewndr46 »

arduanika wrote: post #481
sidewndr46 wrote: post #227

Earlier quoted context omitted.

was FTX actually liquidated? Last I read the lawyers were just busy paying themselves $500,000 a day

Yes. Among other things, the Anthropic stake was sold, and repayments have begun. The full process will probably drag out through next year at least. On the lawyer fees...do you expect someone to do it for free? Would you rather hire someone without the expertise? Do you think the crimes are the estate lawyers' fault? Process costs money. You can sneer at the professionals that work hard to keep a lawful society in o…

No, I'm just surprised they actually are making payments. I had no personal stake in FTX, so I didn't closely track it.

Re: Anthropic raises $13B Series F

#640

Post by cjbgkagh »

mlyle wrote: post #638
cjbgkagh wrote: post #628

Earlier quoted context omitted.

I’m unconvinced that the lessons learned from scaling will constitute much of a moat. There is certainly an incentive for incumbents to give such an impression.

Probably not. But we don't tend to see P=MC where there's any differentiation or barrier to entry, and I do not believe that AI is fully commoditized or will be soon.

Perhaps my 'marginal cost' should have been taken to be 'near marginal cost' and as such I don't believe it'll be fully commoditized either, just mostly commoditized in that it becomes impossible to extract meaningful monopolistic rents. Similarly I don't believe in perfect market efficiency so nothing would be exactly at marginal cost. At the moment we have investment subsidizing use so often these APIs are available at below marginal cost - the old adage 'we lose money on every sale but make up for it in volume'. I'm not confident that these investors on average will be able to make their money back plus a required rate of return and for many it's probably not the primary point of investing in this industry. If you have a $1B dollars to spare you too can light it on fire...
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