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China 6 months behind US on AI, says Google’s former region head
China 6 months behind US on AI, says Google’s former region head

AI

China is going to be a leader in AI apps, even though it is behind in developing models

At the moment, Chinese AI models are 6 to 9 months behind their U.S. peers. However, Kai-Fu Lee, who used to be the head of Google China, has said that China plans to adopt AI apps faster than the U.S. by early next year. The rise of AI apps in China is sped up by the lower cost of training AI models. However, it might take a few years to make a fully integrated “super app.”

China is about to jump ahead in AI apps, even though it is behind in developing models.Former Google China head Kai-Fu Lee has said that Chinese AI technology is six to nine months behind that of the United States. Even though model development is taking longer than planned, he thinks that AI uses in China will quickly outpace those in the US.

Lee said at the AVCJ Private Equity Forum in China on September 11 that advanced large language models (LLMs) in China are not as far along as those in the US, but that lower costs for training AI models are speeding up the use of AI apps. Lee thinks that by the beginning of next year, there will be more AI apps in China than in the U.S.

Lee also talked about how new kinds of gadgets might be needed to fully use AI. He said that smartphones might not be able to handle the needs of advanced AI apps. In the future, he sees gadgets that are always on and hearing to help AI functions work better.

Big Chinese tech companies like Alibaba and Tencent are putting a lot of money into AI, making their own models, and helping new companies in the field. Tencent released its own LLM last year, which it called “Hunyuan,” and used it in many areas of the business, such as cloud computing and games.

Lee’s ideas suggest that China may be behind in developing AI models right now, but that the country will soon be ahead in deploying AI applications thanks to its fast technology progress and lower training costs.

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