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When an AI company goes public, a curious phenomenon often emerges: the models onstage can do everything, while the profits in the financial statements may not be much to write home about.
If Anthropic really moves ahead with an IPO, the market will not only focus on how powerful Claude is and how many customers it has, but will also press a painful question: can the company actually make money?
Training models takes computing power, and running them takes computing power. The more customers use them, the higher inference costs may climb. In other words, AI isn’t a webpage that automatically prints money; all those servers in the back end won’t volunteer for free overtime just because the CEO gives a persuasive speech.
Of course, high costs don’t necessarily mean a bad business model. If enterprise customers are willing to pay for more powerful models, Anthropic could build revenue streams through enterprise subscriptions, API calls, and professional services. The key is whether revenue growth can outpace cost growth, whether gross margins can improve, and whether cash burn can gradually come under control. #每周来晒 and #Anthropic files for a US IPO
That’s the real financial drama after going public.
My view is that growth determines how much room the market is willing to give the story, while profitability determines what that story is actually worth.
If revenue grows fast but costs grow even faster, then every new customer could be like hiring a new colleague—the work gets done more efficiently, but the payroll gets longer too.
What investors ultimately want to see isn’t how well AI can answer questions, but whether the company can deliver a sustainable business answer.
After all, the stock market welcomes spending money to fuel growth, but what it likes least is money going up in fireworks while profits remain like the moon: visible from far away, but impossible to reach. $APD