AlphaGo an AI giant, still not a threat

Google Deep Mind's AlphaGo artificial-intelligence program has beaten South Korean Go master Lee Sedol 4:1, sparking a debate world wide on whether AI could pose a threat to humankind.

The development of AI began decades ago. In 1997, Deep Blue developed by IBM defeated the world chess champion Garry Kasparov. In 2010, Apple added Siri (speech interpretation and recognition interface) to its iPhone, which understands the users' audio commands and replies accordingly-similar examples include Xiaobing of IBM and Jimi of jd.com.

But Siri, Xiaobing and Jimi can only deal with a limited number of questions, as they compare the user's command with those pre-installed in their "memories" and answer accordingly. The Deep Blue, on the other hand, relies heavily on fast computing; it decides its next move in a chess game mainly by evaluating the condition on the chessboard and comparing it with the manuals saved in its "memory". That's why it cannot win a Go game, which involves many more possibilities than chess.

AlphaGo, in this sense, is a big step forward because it uses multi-layered artificial neural network, or ANN, and reinforcement learning alGorithm, which can more exactly imitate the way a human brain thinks. AlphaGo repeatedly observes the Go board, analyzes it with its processor and makes the best choice. More importantly, it can store the decisions in its "memory" for future references. In other words, it can more efficiently "learn" and improve.

ANN has become a hot subject of research since the 1980s. It is already being used in many fields besides games. For example, the driverless car developed by Google "observes" the environment through sensors, using calculations to judge how things are moving, and chooses its route accordingly.

AlphaGo marks another step forward because the ANN it uses has more than 30 layers thanks to developers and faster computers. Each layer has multi-parameters that get adjusted each time it obtains information from the outside world, a process through which AlphaGo constantly optimizes its strategy. The more information it gets, the more exactly it can adjust the parameters to suit new situations.

Many people jocularly say AlphaGo is a hardworking student that "studies" hundreds of manuals every night. That may be a joke, but AlphaGo has learned a great deal about Go, or it couldn't have defeated Lee Se-dol. Let's hope its victory would make more people interested in AI research.

Yang Feng is an associate professor at the School of Automatics, Northwestern Polytechnical University.

AI research to boom

AlphaGo's victory in Go is good news for artificial intelligence as well as human intelligence. Its victory means AI is improving fast thanks to human intelligence.

AlphaGo's performance is likely to start a global wave in AI research, which would help AI to play a bigger role in sectors such as medicine, education and manufacturing.

But AlphaGo's victory has also raised concerns that AI might eventually control, even enslave humans, as depicted in some science fiction movies. Such concerns are unnecessary, at least for the time being. Even the best AI cannot match human intelligence, which is unique in accumulating experience and thinking creatively and independently. Also, scientists are far from clear how exactly the human brain functions. So how can there be a perfect imitation of the human brain? The greatest advantage of AI is its computing speed, which far surpasses that of humans. But it can learn and improve its strategies, not think independently. Machines running on AI can only execute the orders given to them and they seem to be doing it well.

However, AI may be a cause for concern for us as individuals. AI may not be able to conquer the entire human race, but AI-propelled machines have been performing better than humans in sectors other than Go and chess as well. For instance, Foxconn has long been using robots on its assemble lines, while Google and Apple are testing unmanned vehicles. Since AI could replace humans in sectors that require repetitive manual labor in the future, the sense of urgency among workers is understandable. But that is no reason for China to fall behind in innovative technology R&D.

Zhang Zhouxiang is a writer with China Daily. zhangzhouxiang@chinadaily.com.cn