In this video I will share my views on the AI bubble and whether the exponential rise of expenses could have an impact on it bursting.

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Philipp Lackner

AI companies like OpenAI, Anthropic, and big tech giants are burning massive amounts of capital in a race to build ever-larger models, with no clear path to profitability. However, the cost to achieve equivalent AI performance has dropped dramatically — GPT-3.5-level performance fell from $20 to $0.07 per million tokens in just two years, a 285x reduction. The argument is that cost alone won't burst the AI bubble; instead, growth will likely slow as training costs hit a ceiling, consolidating the market to two or three dominant players. The analogy to the dot-com bubble is explored: like the internet, AI's underlying business value is real and unlikely to disappear, but the hype cycle may cool into slower, steadier growth.

Is the cost of AI a dead end?