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OpenAI raises $110B on $730B pre-money valuation

techcrunch.com

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Re: OpenAI raises $110B on $730B pre-money valuation

#601

Post by danielparsons »

duped wrote: post #413
danielparsons wrote: post #410

Earlier quoted context omitted.

google search definitely has a moat. people build their websites to optimize for google's algorithm, therefore google users see better results -> google gets more users -> websites optimize for google -> repeat. Personally I never bother with 'bing SEO' or 'bing ppc ads'.

Google backfilled their moat with sponsored results and crappy AI summaries

the AI has gotten good enough that click-thru-rate on informational searches has fallen off a cliff. I have some blog posts for SEO, their CTR is like 0.1% now.

Re: OpenAI raises $110B on $730B pre-money valuation

#602

Post by danielparsons »

sigmoid10 wrote: post #593
danielparsons wrote: post #407

Earlier quoted context omitted.

you're looking at nearly the entire curve of the tech's development. that's like saying lightbulbs became 99% more energy efficient and therefore will become another 99% more energy efficient. but most techs follow an S curve.

>you're looking at nearly the entire curve of the tech's development That's a pretty strong statement that would need some data or at least a mathematical argument to back it up. Otherwise it's like saying in the 1980s that PCs with 640kB RAM have reached their pinnacle in terms of what users can expect in real life benefits and there's no reason to keep pushing the tech.

*entire curve to-date (I should have clarified). Yes it will get better for a long time, but where we are on the curve is harder to say. Lots of metrics to choose from, like "well it's incorrect 90% less often than a year ago, so that's a 10x improvement!". But the real metric that matters is how useful it is to people, and based on user data it looks like the only area it's getting exponentially more useful YoY is for programming. Lot of coders using it 10x more than before to code 10x faster. Not sure any other profession uses it for more than a juiced-up search engine / proofreader.

Re: OpenAI raises $110B on $730B pre-money valuation

#603

Post by simonebrunozzi »

7777777phil wrote: post #287

$730B pre-money for a company where each model is roughly 2x profitable on its own, but each next model costs 10x the last. The whole thing only works if scaling keeps delivering. Research (Sara Hooker et al.) is not encouraging on that front, compact models already outperform massive predecessors on downstream tasks while scaling laws only predict pre-training loss reliably. Wrote about both the per-model math and t…

> EDIT: Removed the dot after et; bc apparently it's an entire word (the more you know..)

From latin "et alia", abbreviated as "et al." - it's not a single word but an expression.

Re: OpenAI raises $110B on $730B pre-money valuation

#604

Post by sph »

laserlight wrote: post #539
toraway wrote: post #462

Earlier quoted context omitted.

A classic hype merchant sales pitch: believe me, I was a doubter just like you, but I saw the light thanks to [insert latest model] ! (Which for anyone familiar with your long comment history as a regular HN poster, is comically absurd to imply. You've been reliably adamant that AI will demolish this or that entire industry overnight for years at this point).

GP commenter got my attention during the last few days. Judging by their claims of productivity, they should have been a billionaire already. I'm curious to know their motivation behind making such outrageous claims.

I’ve seen their outrageous comments so often I wonder if it’s Sam Altman’s alt account. Probably the biggest AI snake oil merchant on the forum these days, with a sadistic pleasure at seeing people losing their job to AI.

Re: OpenAI raises $110B on $730B pre-money valuation

#605

Post by engineer_22 »

putlake wrote: post #479
engineer_22 wrote: post #303

Earlier quoted context omitted.

Will they maintain an edge over other AI companies long term? With so many market participants will it become a race to the bottom? This valuation puts their P/E around 40. Anthropic $380B valuation on $13B ARR. P/E around 30. 5 years ago Uber was in similar territory. Tesla... Well we won't mention Tesla.

That's not P/E. That's Price to Sales. P/E is price to earnings ratio. Earnings is profit. Since neither of these companies is profitable, they don't have a P/E ratio today.

Nice, thank you for the correction

Re: OpenAI raises $110B on $730B pre-money valuation

#606

Post by ThrowawayR2 »

echelon wrote: post #538
Aperocky wrote: post #267

Earlier quoted context omitted.

> write 20kloc of Rust code every day (and I review all of it) Only one of this can be true. It's not a shame to say you don't bother reviewing it, in the future that may well be the norm.

This isn't agentic coding. I haven't even tried that yet. I'm prompting every change set, reviewing the outputs, then reviewing the total changes. I'm sitting at my PC all day doing this - I used to be productive in short bursts, now I'm productive all the time. It's addictive.

You are reviewing 20kLOC per day, which is about 0.7 LOC per second in an 8 hour working day, assuming literally doing nothing else but reviewing? Pardon me but I don't find that very believable.

Re: OpenAI raises $110B on $730B pre-money valuation

#607

Post by enos_feedler »

cylemons wrote: post #568
tarsinge wrote: post #522

Earlier quoted context omitted.

Uber and Airbnb have network effects. You cant increase price when there is no cost in switching.

I dont see how network effects applies to Uber/Airbnb because nothing stops drivers/hosts from listing their property in multiple such apps

Do you understand network effects? It’s not hand cuffs. I can also sell my rare baseball cards outside of ebay. But…

Re: OpenAI raises $110B on $730B pre-money valuation

#608

Post by harry8 »

drivebyhooting wrote: post #533
harry8 wrote: post #511

Earlier quoted context omitted.

not seeing anyone at all suggesting the work of the c++ committee is going to radicaly alter the efficiency of labour.

My point is that C++ is a tarpit, famous for nerd sniping and leading otherwise intelligent people into Wild goose chases. Have you read Alexandrescu’s “modern c++”? It’s like a piece of modern art but completely not self aware. There’s just something about C++ that lures intellectuals in; like ice age mammoths to a tar pit. Small wonder LLMs also fall victims to C++’s deranged ways.

I don’t love c++ but can get things done in it. The tarpit is Haskell ;-)

Re: OpenAI raises $110B on $730B pre-money valuation

#609

Post by generallyjosh »

intrasight wrote: post #560
vidarh wrote: post #463

Earlier quoted context omitted.

> Wrong. They will use the model that gives them an edge. If they are using a PhD but their competitors are using Einstein, they will lose. For some tasks that matters. But for a lot of tasks, "good enough but cheaper" will win out. I'm sure there will be a market for whichever company has the best model, but just like most companies don't hire many PhD's, most companies won't feel a need for the highest end models e…

Models will get smarter and cheaper. For those that are burned directly into silicon, there will be a market for old models - as the alternative is to dump that silicon in a landfill. For models that run on general-purpose AI hardware, I don't know why the vendors would waste that resource on old models.

Larger models need more hardware resources to run

And, depending on effort settings, they do more 'thinking', i.e., use more rounds of inference to generate longer internal chains of thought

Both very good reasons to prefer a smaller model, if the small model is good enough for the task

Re: OpenAI raises $110B on $730B pre-money valuation

#610

Post by sigmoid10 »

danielparsons wrote: post #602
sigmoid10 wrote: post #593

Earlier quoted context omitted.

>you're looking at nearly the entire curve of the tech's development That's a pretty strong statement that would need some data or at least a mathematical argument to back it up. Otherwise it's like saying in the 1980s that PCs with 640kB RAM have reached their pinnacle in terms of what users can expect in real life benefits and there's no reason to keep pushing the tech.

*entire curve to-date (I should have clarified). Yes it will get better for a long time, but where we are on the curve is harder to say. Lots of metrics to choose from, like "well it's incorrect 90% less often than a year ago, so that's a 10x improvement!". But the real metric that matters is how useful it is to people, and based on user data it looks like the only area it's getting exponentially more useful YoY is f…

Tbf that sounds like a strong bias from someone who works exclusively in software development and simply hasn't found other uses. But I have worked with integrating LLMs across quite a few applications and departments by now and I can comfortably say that programming is not the only thing where we see extreme benefits. I wouldn't even say it's the area that has seen the most benefit so far. There used to be a lot of mundane work outside of software development that was easy prey even for early models. And with the current cutting edge models I'm pretty sure that you could replace >75% white collar jobs if you just get the context engineering right. That's the hard part right now, not the raw intelligence necessary for arbitrary data processing. But frameworks are getting there fast.
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