Baidu CEO predicts that artificial general intelligence will take more than a decade to develop.

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Rumor has it that the development of artificial general intelligence (AGI) might still be a long way into the future – more than a decade away. In the tech industry where predictions often fluctuate, Robin Li, the CEO of Baidu, one of China’s tech giants, expressed his belief that achieving AI that surpasses human intelligence is no easy task and will take considerable time. He shared this view during a discussion at the VivaTech conference held in Paris. This perspective contrasts starkly with Elon Musk’s forecast that AGI could become a reality by 2026. Li’s caution around the timescale needed for AGI’s arrival stems from the complexity involved in creating an AI that matches or exceeds human intelligence levels.

Li emphasized the importance of speeding up the development of AI technology. He expressed concern that the pace at which AI technology is progressing may not be fast enough to meet the lofty goals set by industry players. Despite significant advancements in AI technology in recent years, Li believes that there is still much ground to cover to achieve the level of artificial intelligence that rivals human cognition.

AI Growth and Development

Baidu’s foray into AI is evident with the launch of its ChatGPT-style chatbot named Ernie, utilizing the company’s large language model, Ernie. In similar moves, other Chinese tech giants like Alibaba and Tencent are also heavily investing in their AI projects, mirroring the trends seen among their American counterparts. However, Li points out a distinct divergence in approach between the East and the West. While U.S. and European companies focus on refining foundational AI models, the emphasis in China leans more towards practical applications of AI technology.

Despite the significant investments and strides made in AI development, Li notes the absence of a standout “killer app” for AI currently. Unlike popular mobile applications such as Instagram and TikTok with their massive user bases, there hasn’t been an equivalent standout AI-native application to capture users’ attention at such scale. This leads Li to pose the question of what form AI-native apps should take to attract the same level of engagement and user adoption seen in popular mainstream apps.

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