Innovation, investment urged to win global AI race

Chinese technology companies, which have better access to data resources and industrial application scenarios, should step up investment in improving computing power and algorithms and accumulate more high-quality training data to gain an edge in the global artificial intelligence race, industry experts said.

They made the remarks as GPT-4o, the latest large language model launched on Monday by United States company OpenAI, caused a global sensation.

According to OpenAI, the new flagship generative AI model surpasses the company's existing models in vision and audio understanding, making the interaction between humans and machines much more natural and easier.

GPT-4o is capable of handling 50 different languages with a faster response time and will be available for free to all users, the company said.

Chinese experts said the multimodal LLMs, which possess the abilities to process and generate content across multiple modalities, including text, images, audio and video, lead the way for the further development of the generative AI industry and can be applied to a wider range of fields.

Pan Helin, a member of the Ministry of Industry and Information Technology's Expert Committee for Information and Communication Economy, said the launch of GPT-4o is undoubtedly a major breakthrough in the AI domain and has significantly enhanced human-machine interaction efficiency, as the model is capable of realistic voice conversations and can interact across texts and images.

He noted that the training of multimodal AI models necessitates massive requirements for computing capacity resources, which will give a strong boost to the development of the computing power industry.

"Chinese tech companies should beef up independent innovation abilities in underlying computing power chips and programming software, and invest more in basic scientific research including mathematics, statistics and computer science, in order to catch up with leading foreign counterparts amid intensifying competition in the global AI industry," Pan added.

Chinese companies are scrambling to roll out AI-powered LLMs and making concerted efforts to narrow the gap with the US in the fast-developing generative AI sector.

Alibaba Cloud, the cloud computing arm of Chinese tech heavyweight Alibaba Group, recently unveiled Tongyi Qianwen 2.5, the latest version of its LLM, saying the capabilities have surpassed those of OpenAI's GPT-4 Turbo model, the predecessor of GPT-4o.

Alibaba's AI chatbot has achieved a full upgrade with improved performance in reasoning, code comprehension and textual understanding compared with its previous versions, the company said.

Chinese AI company iFlytek announced that its upgraded LLM outperformed GPT-4 Turbo in metrics, including language understanding and math, while internet company Baidu said in October that capabilities of its latest LLM version, Ernie 4.0, are on a par with those of OpenAI's GPT-4.

Wang Peng, a researcher at the Beijing Academy of Social Sciences, said, "China's major advantages in developing AI lie in abundant data resources and diversified industrial application scenarios, while the US has taken the lead in basic AI research, chips, algorithms and other crucial technologies, as well as a sound innovation ecosystem."

Chinese enterprises should pool more resources into improving the quality of data that satisfy the training of LLMs, optimizing algorithms, cultivating talent specialized in the field of AI and expanding cooperation with leading international AI companies, he said, calling for efforts to make breakthroughs in core technologies covering AI chips and cloud servers.

Weng Xi, a professor at Peking University's Guanghua School of Management, said that major Chinese AI enterprises lag only half a year behind their US counterparts in the development level of their AI products.

China should make more efforts to encourage the application of AI in industries, in order to boost the development of the AI sector, Weng said.

Experts said the use of AI models raises concerns about ethics, copyright protection, privacy and data security, and more efforts are needed to formulate rules and regulations to ensure the healthy development of the technology.