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This fact flew under the radar because all the attention is on war and oil. No one made a post about it. People are still not seeing AI stock growth potentials. AI stocks are still hugely under appreciated in terms of growth.
Anthropic added $6 billion ARR in February alone. ([Source](https://finance.yahoo.com/news/anthropic-arr-surges-19-billion-151028403.html)) February only had 28 days.
$6 billion is:
* 1x Palantir annual revenue
* 5x Figma
* 1.34x Snowflake
* 1.3x Intuit
* 1x Atlassian
* .25x Adobe
* .17x of SAP
* .14x of Salesforce
In a single short month, Anthropic added 1x Palantir annual revenue and 1.34x Snowflake. Think about this.
All reports indicate that Anthropic could have added a lot more but are severely compute constraint. All developers know this already because Clade Code goes down frequently because they don't have enough compute to serve demand.
Your most likely thought is, well they can make a lot of money but are they making a profit? They're not profitable but they are on the way.
Anthropic CEO has repeatedly said that their gross margins on inference is 50%+. OpenAI CEO has said the same thing. Independent token analysis confirms this: [https://martinalderson.com/posts/are-openai-and-anthropic-really-losing-money-on-inference/](https://martinalderson.com/posts/are-openai-and-anthropic-really-losing-money-on-inference/)
There are also a ton of small inference providers on OpenRouter, and they are most certainly not going to inference at a loss since market share doesn't matter for them. They need to make more money per token than they lose because they do not have billions in VC backing.
So if they in such high demand, why can't Anthropic and OpenAI turn a profit? Because they don't need to yet. They're spending their money on the AGI race by training bigger, smarter models. Competition between OpenAI, Anthropic, Google, Meta, Chinese AI companies are intense.
So how can they ever make a profit then?
1. Inference revenue is outpacing training cost. This is happening now. In the past, training might have cost OpenAI/Anthropic 80% of their revenues. Today, it's a smaller and smaller pie as inference market explodes. Training is cost. Inference is profit. Inference profits need to grow faster than training costs and it is.
2. Many competitors will drop out. When competitors drop out, training costs do not need to rise as much. Given enough time, many tech fields are a natural monopoly or duopoly. Think Google search. Windows & MacOS. iOS and Android. Everyone expects foundational AI models to be a monopoly or duopoly because smaller competitors will not be able to come up with the compute to compete in training state of the art models. Leading AI model companies will run away as they make more money, use that money to train bigger models, leading to more users, leading to more data to train, etc. It's a flywheel effect.
There are a lot of wrong takes on AI on r/stocks. The goal posts keep moving. I've heard it all here:
* There is no demand or demand is "fake".
* AI is not useful or hallucinates too much.
* If AI is so useful, then where is the revenue?
* Ok, there is revenue, but where is the profit? <-- we are here