In the Aug. 12th CCF-GAIR summit artificial intelligence workshop, Michael Wooldridge, Head of the Department of Computer Science, and Professor Yang Qiang of the Hong Kong University of Science and Technology, respectively, presented the conference’s report and keynote speech on the progress of artificial intelligence. After the speech, there was a 1v1 high-end dialogue between the two guests.
Michael Wooldridge and Yang Qiang respectively believe that the next enthusiasm for artificial intelligence applications will be in the medical and financial fields. For the cooperation between academia and industry, they all think that a sentimental leader is very important, and believe that cross-border integration can promote the popularization and development of artificial intelligence. The following is the full text of the two guests' dialogue:
Question: The first question is that from the perspective of investment, artificial intelligence has a lot of enthusiasm in industrial applications. Where is the next possible application of artificial intelligence in investment? The second question, both of which are the directors of the joint laboratory of industry and academia, is the experience and inspiration that resulted from the cooperation between the two.
Michael Wooldridge: The next AI application, especially in industrial applications, I think it should be in the medical field. why? Because in the United Kingdom and the United States, I believe the same is true in China. There is now a bracelet that is very popular. It can monitor your heart rate, your blood glucose level, and how many steps you take. Apple Watch is also wearable. Equipment, now we are constantly monitoring the physical condition. All of this information will be given to AI and it will be able to achieve some healthy applications.
I don't know your situation. I only went to see a doctor when I was sick. Now, this application is to let the doctors stay with you and monitor it 24 hours a day. It knows how much you sleep, how much you eat, knows the level of your blood sugar, knows your movement through the skin, and more. So you can use smart phones to suggest when you want to exercise, eat too much, or drink too much alcohol. In the United Kingdom, one view is that the greatest application is in medicine, and there are already some such records. Cases of the British National Medical System, including all British case data, medication records. The AI ​​that we talked about this morning can be applied to the medical field. It really brings new discoveries for our entire medical industry. So I think the next hurdle should be medical care.
Yang Qiang: To answer this question, I would like to ask the following two questions: The first is where the data is, and whether there is any big data in the areas we care about; the second is a little secular, where the money is. Wherever there is data, there is no money to drive our work on artificial intelligence. We can look at which area around the data is almost ready. Here I want to put forward a concept: closed system. Just now I talked about the issue of clear boundaries. The definition is very clear. I mean that this closed system means that the entire business process has data footprints and all of them are left behind.
We look at whether there is such data in the field of education today, whether it is in the field of travel, finance, or medical care. In these fields, I prefer finance because it is too critical and important at every step. Many people have recorded all the entire business processes long ago. There is a digital method. It is not used there. Although there are many different political and economic angles affecting it, we must not forget that the commercial success of artificial intelligence is only better if the system is better than humans. It is just like winning gold medals in the Olympic Games is only slightly better than silver medals. Therefore, in terms of information processing and future forecasting, if we are in a closed system, under the premise of big data, and under the influence of funds, I think that finance will almost succeed.
Michael Wooldridge: For the first question, it must be a closed system, with funds and big data. The second question to say is that I am not the head of DeepMind. I am from Oxford University. I work with DeepMind and I also know DeepMind. His colleagues also have many cooperations with us. We understand the progress of DeepMind and I think there are indeed conditions for success.
First of all, DeepMind has leadership. One of the founders is not only the company owner, but also a technical expert. He really understands technology, understands deep learning, and also knows human brains in particular. This is very important. You must have a special understanding of technology at the management level, and it is a deep understanding. In addition to understanding technology, they also have a vision. DeepMind's vision is very clear. They have very specific projects, such as Alpha Dogs, who are very focused on this project to achieve their vision. They created a group and the group did attract other researchers to attend. In general, you may go to Hong Kong University of Science and Technology to study at MIT. If you are a good researcher, the university will accept you. DeepMind creates an atmosphere that creates a knowledge environment. People know that deepMind can have the right resources, have the right environment and atmosphere to study, so attracting good researchers is very important.
First of all, the leadership needs to have technical level support. The founders of DeepMind are very familiar with deep learning. Second, they have a very clear vision with a very focused project and vision. The third point attracts outstanding researchers. I think this is DeepMind's very successful experience.
Yang Qiang: My personal experience is more in China. First, in 2013, Li Hang and I established the Huawei Noah's Ark Lab. After that, I established a joint lab with WeChat. The emotional leader is very important. Wechat's Zhang Xiaolong is very familiar with everyone. He has a lot of expectations for artificial intelligence. WeChat is very great in China. There are many foreign reports today that Facebook is learning with WeChat. WeChat has provided us with a very good platform for doing artificial intelligence. We can't keep it in the house and do it with an ivory tower. We must open our minds and allow us to have more people to use. Let them benefit. WeChat provides such a platform.
Secondly, we have a clear distinction with WeChat in the discussion of many issues. Particularly difficult academic issues can be left for us. WeChat is also very keen to provide us with such a resource. We have more than a dozen professors, and the laboratory studies from robots to natural language processing, speech recognition, image processing, image recognition, including dialogue systems, and so on. Many professors and students are involved. Everyone has a Hong Kong University of Science and Technology tutor and WeChat tutor, a theoretical tutor and a practical tutor. Students also feel that they have benefited from it. They can use their experiments on the WeChat platform at any time. This is also the dividend we get. Therefore, in the case of such mutual benefit, if we do such a lab, then we think it is a win-win situation and a good scenario.
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