Big tech businesses are convinced that there must be some profitable business model for AI, and are undeterred by the fact that none has yet been found. They want to be the first to get there, raking in that sweet sweet money (even though there's no evidence yet that there is money to be made here). It's industry-wide FOMO, nothing more.
Typically in capitalism, if there is any profit, the race is towards zero profit. The alternative is a race to bankrupt all competitors at enormous cost in order to jack up prices and recoup the losses as a monopoly (or duopoly, or some other stable arrangement). I assume the latter is the goal, but that means burning through like 50%+ of american gdp growth just to be undercut by china.
Imo I would be extremely angry if I owned any spacex equity. At least nvidia might be selling to china in the short term... what's the upside for spacex?
Again, different markets, because I'm not going to do either of those things—if I'm ordering online amazon has better selection, and if I want to walk somewhere to pick something up I'm not going to wait for shipping.
taxi apps, delivery apps, social media apps—all of these require a market that's extremely expensive to build but is also extremely lucrative to exploit and difficult to unseat. You see this same model with big-box stores displacing local stores. The secret to making a lot of money under capitalism is to have a lot of money to begin with.
Taxi apps—uber & lyft. They moved into an area (often illegally); spent a shit-ton of money to displace local legal taxis, and then jacked up prices when the competition ceased to exist. Now I can't hail a taxi anymore if I don't have a phone.
> None of the big-box stores have created a monopoly.
They do in my region. Mom and pop shops are gone.
> Amazon unseated behemoth Walmart with a mere $300,000 startup capital.
We've been over this—they occupy different markets.
> Musk founded his empire with $28,000.
Sure. It would have been far easier to do with more capital.
People keep saying this but it's simply untrue. AI inference is profitable. Openai and Anthropic have 40-60% gross margins. If they stopped training and building out future capacity they would already be raking in cash.
They're losing money now because they're making massive bets on future capacity needs. If those bets are wrong, they're going to be in very big trouble when demand levels off lower than expected. But that's not the same as demand being zero.
those gross profit margins aren't that useful since training at fixed capacity is continually getting cheaper, so there's a treadmill effect where staying in business requires training new models constantly to not fall behind. If the big companies stop training models, they only have a year before someone else catches up with way less debt and puts them out of business.
Only if training new models leads to better models. If the newly trained models are just a bit cheaper but not better most users wont switch. Then the entrenched labs can stop training so much and focus on profitable inference
Well thats why the labs are building these app level products like claude code/codex to lock their users in. Most of the money here is in business subscriptions I think, how much savings would be required for businesses to switch to products that arent better, just cheaper?
Stop this trope please. We (1) don't really know what their margins are and (2) because of the hard tie-in to GPU costs/maintenance we don't know (yet) what the useful life (and therefore associated OPEX) is of GPUs.
> If they stopped training and building out future capacity they would already be raking in cash.
That's like saying "if car companies stopped researching how to make their cars more efficient, safer, more reliable they'd be more profitable"
