On October 29th, during the 2017 Future Science Awards Ceremony and the Future Forum Annual Meeting, several leading figures in artificial intelligence and computer science gathered to share their insights. Among them was Li Yongfei, a tenured professor of computer science at Stanford University, director of the AI laboratory, and chief scientist at Google Cloud AI and Machine Learning. Also present was Dawn Song, a professor of computer science at UC Berkeley, founder of JingChi Corp., and former senior vice president at Baidu. Wang Jin, associate professor of electronic engineering at Tsinghua University, and former general manager of Baidu’s autonomous driving division, joined the discussion. Additionally, Wang Yu from the Hong Kong University of Science and Technology, IEEE Fellow, and AAAI Fellow Yang Qiang, deputy director of the Department of Computer Science and Technology at Nanjing University, as well as ACM, IEEE, and AAAI Fellow Zhou Zhihua, were all part of the event.
A photo titled “Contrast physics – artificial intelligence may not be in the Newton era†was displayed, highlighting the ongoing debate about the maturity of AI compared to classical scientific fields.
As part of the event, science and technology played a key role, with live broadcasts and discussions on various topics. Here are some highlights from the Q&A session:
**Q: What do you see as the opportunities for combining AI and cars?**
**Wang Jin:** The automotive industry is facing a huge opportunity. Countries like China, the US, Germany, and Japan are competing across three dimensions: technology and talent, industry development, and national regulations and public acceptance. AI has a wide range of applications beyond just self-driving, making it a valuable asset in the sector.
**Q: What is the current pattern of talent competition in the US market?**
**Li Feifei:** I would summarize it in four words: "the world is scarce." This is a global issue. In academia, I've always advocated for more investment in basic education and research. While we’ve seen some exciting developments, there's still a long way to go. Without increased support, we risk a crisis. In the industry, Google places a strong emphasis on talent, focusing on visualizing AI and nurturing talent from multiple angles.
**Dawn Song:** There is a clear shortage of AI talent, and both the academic and business communities need to work together to cultivate it. Additionally, our understanding of AI and deep learning is still limited, which could affect its long-term application. For emerging fields, both research and investment are essential.
**Q: If we compare AI to the development of the Internet, where are we now? Could it be similar to the stage of the Internet in 1995?**
**Zhou Zhihua:** From an academic perspective, AI isn’t an explosion yet—it’s more of a culmination of the past two decades of research and development.
**Wang Jin:** Whether at Baidu or JingChi Corp., I can see the high demand for AI talent. Compared to other countries, China needs more skilled professionals in this field.
**Li Feifei:** I want to emphasize that AI is only 60 years old. Intelligence is a profound topic. When looking at the history of physics, Newton’s impact was monumental. But AI hasn’t reached the level of Newtonian mechanics—whether in algorithms or other areas. Recently, I’ve been thinking about whether we’re in the Galileo era or the early stages of understanding. We’ve made progress, but there’s still a lot to discover. From a scientific standpoint, any field evolves through exploration and discovery. I approach AI with humility and curiosity.
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