The artificial intelligence industry is in a "trough of disillusionment" as efforts are needed to solve many problems, such as beefing up the supply of computer algorithms so AI can be used in different industries at scale, industry experts said.
"Trough of disillusionment" is a term created by market research company Gartner Inc as part of a graphical presentation to represent the maturity, adoption, and social application of specific technologies. Trough of disillusionment happens when interest in the technology wanes as experiments and implementations fail to deliver on the hype the industry has created.
"After going through rapid development for the past five to six years, the AI industry is sliding into a deep-water zone. Entrepreneurs, investors and media are all lowering their previous high anticipation toward AI," said Yin Qi, co-founder and CEO of Megvii, a Chinese artificial intelligence unicorn.
Such views are echoed by many in the AI industry.
Duane Kuang, the founding managing partner of Qiming Venture Partners, said every investor was enthusiastic about AI years ago. As long as startups come with the label "AI", they were given a high valuation.
"Now, there are more and more AI companies. Although no one doubts the value of AI, everyone is beginning to ponder over the true value of AI companies," Kuang said.
This is a necessary stage for a technology to mature. Developers of the technology either shake out or fail. Investments continue only if the surviving providers improve their products to the satisfaction of early adopters, Gartner said.
"The trough of disillusionment for AI could last 18 to 24 months. Only companies that can apply AI to solve industrial problems at scale can survive the stage and emerge stronger," said Yin, who co-founded the computer vision technology provider nine years ago.
The 32-year-old senior executive said many problems are blocking AI from truly delivering its value, including insufficient supply of computer algorithms and the difficulty and high cost in applying algorithms to different industries at scale.
As AI is increasingly used in supermarkets, smartphones and other scenarios, some thought that AI algorithms have become very easy now. The fact though is that its supply is far from enough, Yin said.
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