To be fair, both local and cloud models are a boon and danger simultaneously to society.

I'm all for open weights, but I haven't yet figured out a way for the model to be sustainable. How do we finance the training of these open models? Are we assuming that eventually anyone will be easily able to create a near-frontier open model like open source hobbyists?

I guess I don't understand the business model of "open weights". Who pays for the training? Who pays for the datasets? Who pays for the reinforcement?

People used to say that if you aren't paying for the product then you are the product. How do we think open weights will be different?

if llm agents can code most current software for significantly cheaper than tradisional software development and open llms can replace a good chunk of that work alot of software moats of today disappear or at least have significant pressure on margins putting alot of the pressure on the "value" propping up the stock market. good for society bad for 401ks.

The "most intelligent intelligence" based on what?

On AA? Until yesterday there was another vendor on top. Anyway, even if your assumption is true, the difference between vendors is so little that the only thing that really matters is the cost. And they are far behind here.

The ANT bet is them become "systemic" and get protected by the government.

> enterprise customers paying for this advantage

If better would always mean "economically expedient", we all would fly on hypersound commercial jets.

If $2 model in the hands of good engineer can do the same as $20 model, anthropic will be soon killed by self-hosted open-weight models.

Fill your boots. I'll buy some when it totally tanks. :)

There are two moats protecting the big AI companies: the model and the hardware.

It is generally believed that the frontier models are 6-9 months ahead of the best open weight models. That's not really a moat. It's a creek.

Hardware is more of a moat for now but faces long-term issues such as:

1. Local hardware is rapidly improving. By 2030 I think you'll be able to run pretty hefty models on relatively cheap hardware and there's a business case for this too. For example, it's unclear if law firms using cloud models violates attorney-client privilege. The easiest solution is local models;

2. New NVidia hardware is going to immediately halve the value of billions in GPUs. We've got the R100/200 coming out now. What about the generation after that? What will it do to the B100/200s? I believe that hardware will ultimately come down to performance-per-Watt (or token-per-Watt if you prefer). I believe the depreciation time frame is going to be a lot shorter than some of these companies have factored in; and

3. By 2030 you'll probably have China making EUV chips commercially (IMHO) on homegrown tech. This will fundamentally change the AI hardware landscape as China rapidly catches up.

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What's 200B between friends?

Their S1 has GAAP information. I haven't seen if it's been audited by a third party, but generally trying to fudge these numbers before an IPO is a great way to get yourself into a ton of legal trouble. The bigger risk is that the numbers in it are a bit old. We'll get more information once they're public and need to report quarterly earnings.

Nope. You see clearly, but the current system sees at best 2 quarters ahead. Or the system sees that we need to make open models illegal and our oligarchs are the only provider all vying for the spoke goal of creating 40% unemployment.

It's always been based on confidence/emotions

They kind of are part of that timing, no?

spaceX doesnt have P/E since they dont make profit and are not going to for a very long time.

Good use of price anchoring.

How does that compare to a swag of Anthropic’s P/E?

It is wildly over valued

> Anthropic doesn't even own data centers, rockets, a social media platform, or a profitable internet service.

On the flip side, their valuation isn't mostly based on one person who could leave or go (more) insane at any time.

The SpaceX valuation was kind of funny because the space launch business and mobile broadband were viewed as irrelevant side businesses. The Total Addressable Market from the S-1 (IIRC) had space launches at ~$380B, mobile broadband at ~$1.4T and "AI" at ~$25T.

As for not owning data centers, I think this might be Anthropic's saving grace actually. It seems like the price paid for renting is particularly cheap, possibly too cheap. And the meteor headed for all the hyperscalar investment is what happens when NVidia releases a new series of chips and the token-per-Watt numbers halve?

The big companies have very different views on the effective lifetime of GPUs, ranging from 4 years to 8 and possibly 10? years. I think 8+ is wildly optimistic. 10 year old AI chips already sell for scrap and I think that's going to get worse.

400B maybe

"to seek" and "to get" are not the same, no.

Well said. We already had to deal with SpaceX.