Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

OpenAI's H1 2025: $4.3B in income, $13.5B in loss

techinasia.com

Post reply on HN
Print view View original

131–140 of 720 posts

Re: OpenAI's H1 2025: $4.3B in income, $13.5B in loss

#131

Post by dcchambers »

I definitely don't "get" Silicon Valley finances that much - but how does any investor look at this and think they're ever going to see that money back?

Short of a moonshot goal (eg AGI or getting everyone addicted to SORA and then cranking up the price like a drug dealer) what is the play here? How can OpenAI ever start turning a profit?

All of that hardware they purchase is rapidly depreciating. Training cost are going up exponentially. Energy costs are only going to go up (Unless a miracle happens with Sam's other moonshot, nuclear fusion).

Re: OpenAI's H1 2025: $4.3B in income, $13.5B in loss

#132

Post by gmerc »

simonw wrote: post #58

I think the most interesting numbers in this piece (ignoring the stock compensation part) are: $4.3 billion in revenue - presumably from ChatGPT customers and API fees $6.7 billion spent on R&D $2 billion on sales and marketing - anyone got any idea what this is? I don't remember seeing many ads for ChatGPT but clearly I've not been paying attention in the right places. Open question for me: where does the cost of ru…

Stop R&D and the competition is at parity with 10x cheaper models in 3-6 months.

Stop training and your code model generates tech debt after 3-6 month

Re: OpenAI's H1 2025: $4.3B in income, $13.5B in loss

#133

Post by whizzter »

avbanks wrote: post #126
Havoc wrote: post #34

I'd be pretty worried as a shareholder. Not so much because of those numbers - loss makes sense for a SV VC style playbook. ...but rather that they're doing that while Chinese competitors are releasing models in vaguely similar ballpark under Apache license. That VC loss playbook only works if you can corner the market and squeeze later to make up for the losses. And you don't corner something that has freakin apache…

I don't think people fully realize how good the open source models are and how easy it is to switch.

My input to our recent AI strategy workshop was basically:

- OpenAI,etc will go bankrupt (unless one manages to capture search from a struggling Google)

- We will have a new AI winter with corresponding research slowdown like in the 1980s when funding dries up

- Opensource LLM instances will be deployed to properly manage privacy concerns.

Re: OpenAI's H1 2025: $4.3B in income, $13.5B in loss

#134

Post by lossolo »

stephc_int13 wrote: post #75

Everyone is trying to compare AI companies with something that happened in the past, but I don't think we can predict much from that. GPUs are not railroads or fiber optics. The cost structure of ChatGPT and other LLM based services is entirely different than web, they are very expensive to build but also cost a lot to serve. Companies like Meta, Microsoft, Amazon, Google would all survive if their massive investment…

The funniest thing about all this is that the biggest difference between LLMs from Anthropic, Google, OpenAI, Alibaba is not model architecture or training objectives, which are broadly similar but it's the dataset. What people don't realize is how much of that data comes from massive undisclosed scrapes + synthetic data + countless hours of expert feedback shaping the models. As methodologies converge, the performance gap between these systems is already narrowing and will continue to diminish over time.

Re: OpenAI's H1 2025: $4.3B in income, $13.5B in loss

#135

Post by gmerc »

munk-a wrote: post #27
darth_avocado wrote: post #20

Earlier quoted context omitted.

They have to compete with Zuckerberg throwing $100M comps to poach people. I think $830k per person is nothing in comparison.

Both numbers are entirely ludicrous - highly skilled people are certainly quite valuable. But it's insane that these companies aren't just training up more internally. The 50x developer is a pervasive myth in our industry and it's one that needs to be put to rest.

Zuck decided it's cheaper than building another Llama

Re: OpenAI's H1 2025: $4.3B in income, $13.5B in loss

#136

Post by potatolicious »

mattmanser wrote: post #123
Analemma_ wrote: post #100

Earlier quoted context omitted.

Exactly: when was the last time you used ChatGPT-3.5? Its value deprecated to zero after, what, two-and-a-half years? (And the Nvidia chips used to train it have barely retained any value either) The financials here are so ugly: you have to light truckloads of money on fire forever just to jog in place.

But is it a bit like a game of musical chairs? At some point the AI becomes good enough, and if you're not sitting in a chair at the time, you're not going to be the next Google.

Not necessarily? That assumes that the first "good enough" model is a defensible moat - i.e., the first ones to get there becomes the sole purveyors of the Good AI.

In practice that hasn't borne out. You can download and run open weight models now that are spitting distance to state-of-the-art, and open weight models are at best a few months behind the proprietary stuff.

And even within the realm of proprietary models no player can maintain a lead. Any advances are rapidly matched by the other players.

More likely at some point the AI becomes "good enough"... and every single player will also get a "good enough" AI shortly thereafter. There doesn't seem like there's a scenario where any player can afford to stop setting cash on fire and start making money.

Re: OpenAI's H1 2025: $4.3B in income, $13.5B in loss

#137

Post by falcor84 »

Analemma_ wrote: post #100
wood_spirit wrote: post #89

Earlier quoted context omitted.

Unlike railroads and fibre, all the best compute in 2025 will be lacklustre in 2027. It won’t retain much value in the same way as the infrastructure of previous bubbles did?

Exactly: when was the last time you used ChatGPT-3.5? Its value deprecated to zero after, what, two-and-a-half years? (And the Nvidia chips used to train it have barely retained any value either) The financials here are so ugly: you have to light truckloads of money on fire forever just to jog in place.

I would think that it's more like a general codebase - even if after 2.5 years, 95% percent of the lines were rewritten, and even if the whole thing was rewritten in a different language, there is no point in time at which its value diminished, as you arguably couldn't have built the new version without all the knowledge (and institutional knowledge) from the older version.

Re: OpenAI's H1 2025: $4.3B in income, $13.5B in loss

#138

Post by ath3nd »

hgomersall wrote: post #96
throwacct wrote: post #48

At this point, every LLM startup out there is just trying to stay in the game long enough before VC money runs out or others fold. This is basically a war of attrition. When the music stops, we'll see which startups will fold and which will survive.

Will any survive?

[dead]

Re: OpenAI's H1 2025: $4.3B in income, $13.5B in loss

#139

Post by spiderice »

layoric wrote: post #121
wood_spirit wrote: post #89

Earlier quoted context omitted.

Unlike railroads and fibre, all the best compute in 2025 will be lacklustre in 2027. It won’t retain much value in the same way as the infrastructure of previous bubbles did?

> Unlike railroads and fibre, all the best compute in 2025 will be lacklustre in 2027. I definitely don't think compute is anything like railroads and fibre, but I'm not so sure compute will continue it's efficiency gains of the past. Power consumption for these chips is climbing fast, lots of gains are from better hardware support for 8bit/4bit precision, I believe yields are getting harder to achieve as things get…

Unfortunately changing 2027 to 2030 doesn't make the math much better

Re: OpenAI's H1 2025: $4.3B in income, $13.5B in loss

#140

Post by __turbobrew__ »

munk-a wrote: post #27
darth_avocado wrote: post #20

Earlier quoted context omitted.

They have to compete with Zuckerberg throwing $100M comps to poach people. I think $830k per person is nothing in comparison.

Both numbers are entirely ludicrous - highly skilled people are certainly quite valuable. But it's insane that these companies aren't just training up more internally. The 50x developer is a pervasive myth in our industry and it's one that needs to be put to rest.

The ∞x engineer exists in my opinion. There are some things that can only be executed by a few people that no body else could execute. Like you could throw 10000 engineers at a problem and they might not be able to solve that problem, but a single other person could solve that problem.

I have known several people who have went to OAI and I would firmly say they are 10x engineers, but they are just doing general infra stuff that all large tech companies have to do, so I wouldn’t say they are solving problems that only they can solve and nobody else.

Post reply on HN