This week's outlook:
FT Viewpoint: Where does the profitability of AI’s final application scenarios lie?
Currently, the profitable AI companies we see in earnings reports are mainly in the mid-to-upstream segments of the AI industry chain. According to McKinsey, an estimated $6.7 trillion will be required globally for data center expansion from now until 2030, necessitating that AI companies achieve annual profits of $2 trillion to reach a reasonable return on investment.
Drawing parallels with the smartphone revolution, ultimate profitability was realized across the entire consumer market for smartphones. Smartphones benefited from infrastructure support, with expenditures on network signals largely borne by governments rather than private companies. Presently, two AI ecosystems exist worldwide: the U.S.-led paid closed-source ecosystem and China’s free open-source ecosystem. A16z noted that 80% of the startups seeking funding from them are utilizing Chinese AI, and the vast third-world markets are also adopting Chinese AI.
The most critical bottleneck for the future development of AI is electricity, and currently, only China can provide the most stable and affordable power supply. Therefore, both China and the United States will become innovation hubs for AI in the future.
Financial Times report: UK computing hubs will take eight to ten years to connect to the power grid.
Thus, the final profitability of AI lies in whether it can enhance productivity. The current market is pricing in the expectation that productivity will improve and that meg7 will recover its costs. Therefore, whenever the valuation of AI is discussed, the issue always returns to productivity.
FT Perspective: Bitcoin becomes a liquidity barometer.
We observed in the previous cycle...