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Why OpenAI's $157B valuation misreads AI's future (Oct 2024)

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31–40 of 138 posts

Re: Why OpenAI's $157B valuation misreads AI's future (Oct 2024)

#31

Just playing devil's advocate: VCs (esp those who missed out on OAI) are heavily incentivized to root for OAI to fail, and commoditize the biggest COGs item (AI models). This guy is just talking his book.

That doesn't make any sense. A lack of investment is not an investment against by any means, unless this VC invested in the concept of less spam or more workers.

VC's raise money from investors. Investors want to put their money with good VCs. If OpenAI is huge, and you missed it, that seems bad. If OpenAI flops and you strategically held off - that seems good.

Re: Why OpenAI's $157B valuation misreads AI's future (Oct 2024)

#32
post #4

A year ago Sam Altman was going around trying to convince people we all needed to drop 7 trillion dollars to build hundreds of fabs and nuclear power plants to fuel his AI ambitions. Only a week ago he was triumphantly announcing 500 billion dollar deals with our new President. The (regrettably temporary) ousting of Sam Altman looks like the right call, in hindsight. Of course some amount of showmanship is expected,…

Or Elizabeth Holmes....

Re: Why OpenAI's $157B valuation misreads AI's future (Oct 2024)

#33

AI is still a fad.

How so? There are so many tangible applications already: reduced customers service costs, legal research, analysis of medical records or imaging, self-driving Waymos, and so on. Just the things I listed will have profound impacts on cost savings, productivity, and quality of life.

Re: Why OpenAI's $157B valuation misreads AI's future (Oct 2024)

#35
post #6

> But while Facebook’s costs decreased as it scaled, OpenAI’s costs are growing in lockstep with its revenue, and sometimes faster And here comes DeepSeek and takes the steam out of this and the cost arguments that follow it.

It's lose-lose for their valuation regardless. This scenario might if anything be worse for them. Now they have massive sunk capital investments that the second mover might be able to avoid. If the open source models get small enough and high enough quality, the rationale for runing them in the cloud in the first place start to evaporate.

How does OpenAI get paid for a use case that can easily be run locally on an iPhone?

Re: Why OpenAI's $157B valuation misreads AI's future (Oct 2024)

#36
post #8

Earlier quoted context omitted.

Until now we know only what the they claim what that costs are.

Inference costs can't be faked though, since the model can be run locally by anyone with capable hardware. Even if the whole story about the training cost was fake, R1 and the distilled models are still very efficient at inference.

The shock for the industry was the claimed training costs and used hardware.

Re: Why OpenAI's $157B valuation misreads AI's future (Oct 2024)

#37
post #8

Earlier quoted context omitted.

Until now we know only what the they claim what that costs are.

Inference costs can't be faked though, since the model can be run locally by anyone with capable hardware. Even if the whole story about the training cost was fake, R1 and the distilled models are still very efficient at inference.

unless OAI has all the optimization tricks already, which they probably do

Re: Why OpenAI's $157B valuation misreads AI's future (Oct 2024)

#39
People are announcing the death of foundational models too early. Don’t people realize that the big AI players will take all of the proprietary things they’ve been building up behind closed doors and simply layer onto them all the winning techniques everyone else is publishing (like what DeepSeek has used)? DeepSeek itself is taking ideas that have proven out in various other papers and stacking them up to produce their gains (which they’ve been transparent about in their papers).

I also still don’t believe their cost figures, and think they’re leaving out the capital to acquire their secret GPU stash and the cost of pre training their base model (DeepSeek-V3-base). I also suspect their training corpus, which they’ve only vaguely described, would reveal the savings came from working off other foundational models’ work without counting those costs in their figure.

For now, I treat the cost claim as simply a calculated strategy for China to not look like they’re behind in the most important race, to prevent investors from continuing to boost US technology by causing them to doubt the ROI, and to take value out of the US stock market as they did today.

Re: Why OpenAI's $157B valuation misreads AI's future (Oct 2024)

#40
post #8

Earlier quoted context omitted.

Until now we know only what the they claim what that costs are.

Inference costs can't be faked though, since the model can be run locally by anyone with capable hardware. Even if the whole story about the training cost was fake, R1 and the distilled models are still very efficient at inference.

Is the model architecture actually that different from anything else? Or are you just saying that you can get away with smaller models now?
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