The author also points out potential challenges in disrupting industries like law and mental health due to structural and regulatory barriers. They question the potential for AI to significantly impact industries like movies and games, and express skepticism about the economic impact of AI in areas like search and programming. The author concludes by cautioning investors about the potential economic limitations of AI, despite its impressive technological capabilities.
Key takeaways:
- The author argues that while AI models like Google's Gemini and OpenAI's GPT-4 are impressive in their capabilities, they may not be as economically valuable as investors believe.
- The author introduces the "supply paradox of AI," suggesting that the easier it is to train an AI to do something, the less economically valuable that thing is, as the AI is merely adding to an already-massive supply of the stuff it's trained on.
- The author also points out that many industries that AI could potentially disrupt, such as law and mental health, are difficult to disrupt due to structural reasons and established systems.
- The author warns investors to be wary, as AI might end up incredibly smart, but mostly at things that aren't economically valuable.