Indeed, and with the technology plateau-ing, being 6-12 months late with less debt is just long term thinking.

Also, Europe being in the race is a big deal for consumers.

Why would the debt matter when you have $60 billion in ad revenue and are generating $20 billion in op income? That's OpenAI 5-7 years from now, if they're able to maintain their position with consumers. Once they attach an ad product their margins will rapidly soar due to the comparatively low cost of the ad segment.

The technology is closer to a decade from seeing a plateau for the large general models. GPT o3 is significantly beyond o1 (much less 3.5 which was just Nov 2022). Claude 4 is significantly beyond 3.5. They're not subtle improvements. And most likely there will be a splintering of specialization that will see huge leaps outside the large general models. The radical leap in coding capabilities over the past 12-18 months is just an early example of how that will work, and it will affect every segment of human endeavour.

> Once they attach an ad product their margins will rapidly soar due to the comparatively low cost of the ad segment.

They're burning through computers and capital. No amount of advertising could cover the cost of training or even running these models. The massive subscription costs we've started seeing are just a small glimpse into the money they are burning through.

They will NOT make a profit using the current methods unless the models become at least 10 times more efficient than they are now. At which point can Europe adapt to the innovation without much cost.

It's an arms race to see who can burn the most money the fastest, while selling the result for as little as possible. When they need to start making money, it will all come crashing down.

You're describing Google Gemini on any Android phone, that's today, sans the ads.

>with the technology plateau-ing

People were claiming that since year 2022. Where's the plateau?

The pre-training plateau is real. Nearly all the improvements since then have been around fine tuning and reinforcement learning, which can only get you so far. Without continued scaling in the base models, the hope of AGI is dead. You cannot reach AGI without making the pre-training model itself a whole lot better, with more or better data, both of which are in short supply.

> with more or better data, both of which are in short supply

Hmmm. It's almost as if a company without a user data stream like OpenAI would be driven to release an end-user device for the sole purpose of capturing more training data...

While I tend to agree, I wonder if synthetic data might be reaching a new high with concepts like Google's AlphaEvolve. It doesn't cover everything, but at least in verifiable concepts, I could see it produce more valuable training data. It's a little unclear to me where AGI will come from (LLMs? EBMs - @LeCun)? Something completely different?)

Could it be that at least for the "lowest" fruits, most amazing things that can one can hope to obtain from scraping the whole web and throw it at some computation training was already achieved? Maybe AGI simply can not be obtained without some relevant additional probes sent in the wild to feed its learning loops?

If you can't see it you're blind.

LLMs haven't improved much. What's improved is the chat apps: switching between language model, vision, image and video generation and being able to search the internet is what has made them seem 100x more useful.

Run a single LLM without any tools... They're still pretty dumb.

There's frequent discussions about how sonnet-3.5 is in the same ballpark or even outperforms sonnet-3.7 and 4.0, for example.

Being the best European AI company is also a multi billion business. Its not like China or the US respects GDPR. A lot of companies will choose the best European company.

A similar sentiment existed for a long time about Uber and now they're very profitable and own their market. It was worth the burn to capture the market. Who says OpenAI can't roll over to profitable at a stable scale? Conquer the market, hike the price to $29.95 (family account, no ads; $19.95 individual account with ads; etc etc). To say nothing of how they can branch out in terms of being the interaction point that replaces the search box. The advertising value of owning the land that OpenAI is taking is well over $100 billion in annual revenue. Amazon's retail business is terrible, their ad business is fantastic. As OpenAI bolts on an ad product their margin potential will skyrocket and the cost side will be modest in comparison.

Over the coming years it won't be possible to stay a mere 6-12 months behind as the costs to build and maintain the AI super-infrastructure keeps climbing. It'll become a guaranteed implosion scenario. Winning will provide the ongoing immense resources needed to keep pushing up the hill forever. Everybody else - except a few - will fall away. The same outcome took place in search. Anybody spot Lycos, Excite, Hotbot, AltaVista around? It costs an enormous amount of money to try to keep up with Google (Bing, Baidu, Yandex) in search and scale it. This will be an even more brutal example of that, as the costs are even higher to scale.

The only way Mistral survives is if they're heavily subsidized directly by European states.

> It was worth the burn to capture the market.

You cannot compare Uber to the AI market. They are too different. Uber captured the market because having three taxi services is annoying. But people are readily jumping between models using multi-model platforms. And nobody is significantly ahead of the pack. There is nothing that sets anyone apart aside from the rate at which they are burning capital. Any advantage is closed within a year.

If OpenAI wants to make a profit, it will raise prices and be dropped at a heartbeat for the next cheapest option. Most software stacks are designed to be model-agnostic, making integration or support a non-factor.

Three cab apps are a lot less annoying than three LLM apps each having their piece of your chats history.

The winner-take-all effect is a lot stronger with chat apps.

That’s the exact opposite of the way it is right now (at least for me). I don’t like having multiple ride hailing apps but easily have ChatGPT, Claude, Gemini on my phone (and local LLM at home). There is zero effort cost to go from one to the other.

Professional tip - you can save your prompts somewhere else, you don't need "the cloud" for storing them. It's just text.

I interface with AI models using a single website where i can select between models. Code IDEs are doing the same. Companies that facilitate cross model integration are doing doing great (cursor as a famous example). This trend is spreading.

> now they're very profitable and own their market.

No they don't. They failed in every market except a few niche ones.

I think the jury is still out on Uber. They first became profitable in 2023 after 15 years of massive losses. They still burned way more money than they ever made.