On October 29, during the 2017 Future Science Awards Ceremony and the Future Forum Annual Meeting, several leading experts in artificial intelligence and computer science gathered to discuss the future of AI and its impact on various industries. Among the speakers were Li Yongfei, a tenured professor at Stanford University, director of the AI lab, and chief scientist at Google Cloud; Dawn Song, a professor at UC Berkeley and founder of JingChi Corp.; Wang Jin, an associate professor at Tsinghua University and former senior executive at Baidu; Wang Yu, a professor at the Hong Kong University of Science and Technology and IEEE fellow; Yang Qiang, deputy director of the Department of Computer Science at Nanjing University and ACM/IEEE fellow; and Zhou Zhihua, a renowned AI researcher and AAAI fellow.
The event featured live broadcasts and discussions on key topics such as AI integration with autonomous vehicles, talent development, and the current state of AI research. One of the main questions raised was how AI could be combined with the automotive industry. Wang Jin emphasized that the car industry is undergoing a major transformation, with countries like China, the U.S., Germany, and Japan competing across technology, talent, and regulatory frameworks. He also pointed out that AI has a wide range of applications beyond just self-driving cars.
When asked about the talent landscape in the U.S. market, Li Feifei highlighted the global shortage of AI professionals and stressed the importance of investing in basic education and research. She noted that while AI has made impressive progress, there is still a long way to go, and without continued support, a crisis may arise. At Google, she mentioned the company's focus on nurturing AI talent and making AI more accessible through visualization.
Dawn Song echoed similar concerns, emphasizing the need for collaboration between academia and industry to address the talent gap. She also pointed out that a deeper understanding of AI and deep learning is essential, as current limitations could affect the long-term application of AI globally. Both sectors must invest heavily in research and innovation to sustain growth.
When comparing AI’s current stage to the early days of the Internet, Zhou Zhihua suggested that AI is not yet an explosion but rather a period where the results of decades of research are coming together. Wang Jin added that China, compared to other countries, still faces a significant demand for AI talent. Li Feifei concluded by reminding everyone that AI is only 60 years old, and although it has made great strides, it has not yet reached the level of scientific breakthroughs like Newtonian mechanics. She likened the current state of AI to the "Gallileo era," where many steps have been taken, but much remains to be discovered. From a scientific perspective, AI is still in its early stages, and the field requires humility and continuous exploration.
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