The development and application of artificial intelligence (AI) technology have sparked a global boom in recent years, but some experts are starting to worry about the future of this industry. James Ferguson, the founding partner of the UK macroeconomic research firm MacroStrategy Partnership, said in an interview with Bloomberg's "Merryn Talks Money" podcast that the AI industry might be in a bubble that, once burst, could have catastrophic consequences.
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Ferguson believes that despite the attention AI technology is receiving, it remains "entirely unproven." He points out that Silicon Valley's "pretend to do, until you succeed" strategy may not be applicable to AI. He warns that once people are disappointed with AI technology, it could lead to long-term distrust of the entire industry.
This concern is not unfounded. In March, technology stock analyst Richard Windsor wrote in a research note that there have been similar situations in history, such as the internet bubble of 1999, the autonomous driving boom of 2017, and the current 2024 surge in generative AI.
Even some leaders in the technology industry are pessimistic about the future. Last summer, former Stability AI CEO Emad Mostaque warned bankers that he believes the AI industry could face "the largest bubble in history."
Technical flaws are also a concern for many. Ferguson notes that large language models like OpenAI's GPT-4 sometimes generate false information, a phenomenon known as "hallucination." Some experts believe this is an inherent characteristic of AI technology that may never be resolved. If AI cannot be trusted, in Ferguson's view, it is actually "useless."
Additionally, training and maintaining AI models requires a significant amount of electricity, making them "too energy-consuming." For example, Google's carbon emissions have increased by nearly 50% in five years, a trend driven by the company's large investment in AI and is far from its own climate goals.
Key Points:
⚠️ **Warning: AI Industry Bubble**: Experts worry that excessive capital inflow into the AI field may lead to catastrophic consequences.
💬 **Technology Trust Issues**: False information generated by AI (hallucination) may become a persistent problem affecting trust in the technology.
🔋 **Energy Consumption Issues**: The enormous electricity demand of AI models may conflict with climate goals.