AI costs drop while demand surges
The cost of AI tokens has hit a new record low, driven by increased efficiency in AI models, according to Silicon Data. This deflationary trend signals that AI models are using fewer tokens, lowering the adjusted cost per use, even as overall token usage surges to new record highs. This dynamic mirrors Jevons Paradox, where decreased costs stimulate new demand and increase overall consumption.
This development has significant implications for AI labs like Anthropic and OpenAI, particularly as they consider going public. Investors are scrutinizing margin pressures, and the rise of cheaper open-source alternatives could impact their profitability.
The episode also covers the lowest hiring rate in financial services since 2011, potentially indicating an impact from AI adoption.
