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What we mean when we talk about an AI 'bubble' - The World Economic Forum
The term "AI bubble" often comes up in discussions about the future of artificial intelligence (AI). It refers to the idea that the rapid growth and investment in AI may result in an over-hyped market, where the potential benefits of AI are overstated, leading to a burst in the bubble when expectations are not met.
The AI bubble concept is based on the experience of the dot-com bubble in the late 1990s, where people invested heavily in tech startups, believing that the internet would revolutionize everything. When the bubble burst in 2000, many of those companies failed, and investors lost billions of dollars.
In the context of AI, the bubble could be attributed to the rapid growth of AI companies and investment in AI technology. For example, according to data from CB Insights, there were 1,298 AI start-ups as of August 2020. This growth in the number of AI start-ups is accompanied by a belief that AI is set to revolutionize not only business but also society more broadly, from healthcare to transportation.
The AI bubble also has its own unique risks. For example, the gap between AI hype and AI reality has led to concerns that AI is over-promising and under-delivering, as in the case of solutions like GPT-3, which had a high-profile launch, but where claims about its abilities were quickly debunked. This suggests that investors might be putting their money into projects that are simply not capable of meeting their expectations.
The AI bubble also raises questions about the sustainability of the current AI boom. The last few years have seen trillions of dollars invested in AI projects, but it remains unclear whether these investments will actually lead to a return. Indeed, there are concerns that the bubble could burst, leading to a significant slowdown in AI investment.
Source: "artificial intelligence" - Google News, Link
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