These numbers seem insufficiently detailed to really evaluate anything. They’re had $13bn in gross revenue in 2025, and they cost of that revenue was $7.5bn. Both are growing fast (we assume) and the ratio ought to stay roughly constant. But : how are they calculating the cost of revenue? Do they have rapidly depreciating assets that are also needed to produce that revenue? (Starlink has this issue.) Will their cost…
I am also curious what fraction of that revenue is government contracts. If they got say $N billion in government contracts, that is not going to have meaningful growth in the future.
> just a matter of finding 5 billion people willing to pay US prices This is how you know ads are inevitable. YouTube is probably a good indicator of how BigLabs will operate for free users.
I'd be cool with that. YouTube premium is one of the best value subscriptions I have. Steering people toward paying instead of ads-by-default is a net good imo
Seeing that R&D costs are the lion's share, I wonder if we are at a point where the focus can shift to improving the cost of inference. Unless we are genuinely pushing to find AGI, at which point nothing matters, LLMs in their current form don't replace knowledge workers but are an effective force multiplier. How good is enough? For instance, I pay about $1-2 a month for DeepSeek. It's not as sophisticated as Claude,…
A thousand 90 IQ cannot do what a 145 IQ can do.
Similarly, some bosses might believe that they can hire 100 cheap, unmotivated SWEs to replace Linus Torvalds or Fabrice Bellard and achieve something slightly worse. But in certain areas, it doesn't work like that.
The fact that people here are looking at these numbers and saying "this is fine" is absolutely bonkers. Basically, it's a company that's not sustainable for two separate reasons. The first one is that they have an extremely high overhead. SG&A of 55% is really bad. The seconds reason is that their R&D costs are truly astronomical. They could probably cut those costs to some extent, but they're not going to cut them t…
Not here to entirely disagree its bonkers, but Tesla lost about 6b until 2022 when it got profitable and has since returned a healthy multiple of its prior losses as profits.
Tesla's losses were always a small fraction of annual revenue. OpenAI loses multiples of annual revenue.
Let's put it this way, how much is 5% productivity bump worth to you? If you're in the US and you're making 100k a year, that's worth 5k or $416/m. So you can buy two of the most expensive plans on the frontier models. This focus on cost optimization is insane. Just use the frontier models. Even a marginal bump is worth whatever the hell they're charging, at least for now.
Companies aren't paying for tokens so that their employees can capture the gains.
The one man and the dog at the Carolina spinning factory earn far more than their equivalents in Birmingham.
The fact that people here are looking at these numbers and saying "this is fine" is absolutely bonkers. Basically, it's a company that's not sustainable for two separate reasons. The first one is that they have an extremely high overhead. SG&A of 55% is really bad. The seconds reason is that their R&D costs are truly astronomical. They could probably cut those costs to some extent, but they're not going to cut them t…
Petitioning the corrupt head of state to force Anthropic out of business seems to be part of the business model.
Seeing that R&D costs are the lion's share, I wonder if we are at a point where the focus can shift to improving the cost of inference. Unless we are genuinely pushing to find AGI, at which point nothing matters, LLMs in their current form don't replace knowledge workers but are an effective force multiplier. How good is enough? For instance, I pay about $1-2 a month for DeepSeek. It's not as sophisticated as Claude,…
> Unless we are genuinely pushing to find AGI, at which point nothing matters I think the third coming out Jesus Christ in closer than AGI. Seriously, I dread how much of Silicon Valley is wrapped in this narrative of AGI and Singularity. How can all these "rationalists" fail to see that this is what religion looks like: Faith and promises of heaven and hell.
These "rationalists" understand that beliefs should be evaluated on whether they match what we observe, rather than preconceptions about which buckets certain ideas fall into. If the Southern Baptist Convention had announced a theological breakthrough in 2022 that lets them map out the precise calendar dates of the events in Revelations, and using this map they made a series of specific predictions that ended up coming true, it would be rational to start studying End Times Christianity in more detail and irrational to say that it's religious so you're not going to worry too much about it.
Paying a thousand a month for a car is also very stupid.
Is it smarter to totally cheap out and have an unreliable car that breaks down, stranding you, causing you to miss work though? If you're in a line of work that's customer facing, where having a beater of a car is going to hurt your job prospects? Without knowing the rest of the context, absolute statements based on absolute numbers is also dumb. How many months is this car loan? What was the down payment? What's the…
Cheap car =/= unreliable car. Expensive car =/= reliable car.
They aim to undercut labor. For now, businesses are getting addicted to cheap tokens. As the screws get turned, business will debate whether they should spend budget on humans or tokens. What's further devastating is that humans are also becoming addicted to cheap tokens. Much human output is nowadays a token slopfest. People are becoming dumber too. So the real business question will be spending budget on token monk…
> They aim to undercut labor. Which doesn't work the same way at all. With taxis, making them unprofitable leads to a long-lasting lack of taxis. When lots of jobs are lost, it actually becomes easier to hire someone with the right experience.
It might work very much the same. Discourage a cohort of CS grads into following another career path. Give businesses enough time to fully commit to “agentic workflows” such that they don’t have the expertise for in-house engineering anymore. Completely spaghettify every code base such that only AI would be willing and able to implement new features in it. Let customers lower their expectations of quality to meet what AI can product. By the time they crank up the token price, it may be hard or impossible for businesses just to switch back to human engineers.