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Research and development of artificial intelligence in China
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In a forum chaired by National Science Review's Executive Associative Editor,Mu-ming Poo, who also leads the CAS centre for excellence and the China BrainProject, several research experts discussed China's latest initiatives andprogress in artificial intelligence, where the future lies and what the main challenges are.
This discussion was published in English in the latest issue of National Science Review. However, I am sure it is also available somewhere in China in Chinese. Thus, I won’t repeat the English version here except to note some excerpts of the article below. These provide a counterpoint to current popular writings aboutAI on ScienceNet .
Panelists
Yunji Chen | Hongbin Zha | ||
Tieniu Tan | Mu-ming Poo (Chair) | ||
Yi Zeng |
Excerpts from the published discussion
. . . . . Artificial intelligence is not a new topic. It's very hot now, partly because recent progress in neuroscience. While promising, brain inspiration may not be the only approach for advancing learning machines. . . . . .
. . . . . The public reaction towards machines like AlphaGo is misplaced. It's not that difficult for machines to beat humans in board games. . . . . .
. . . . . Humans are not evolved to playboard games or performing super complicated arithmetic tasks. These are not the fundamental aspects of human intelligence. This is a key problem inartificial-intelligence research, in which has been largely focusing on developing machines that excel in circumstances with clearly defined rules. Much less attention has been paid to behavior capabilities in situations with fewer set rules, such as cooking at home or doing real work in the field. . . . . .
. . . . . In my view, the key to artificial intelligence is to develop artificial neural networks in ways that their architecture can be changed through learning. . . . . .
. . . . . The key lies in the plasticity of connectivity, which is related to feedback and correcting errors during learning and ultimately structural changes. The focus so far has been on computing power and speed, which is not the essence of the human intelligence. .. . . .
. . . . . This probably echoes the progress in neuroscience. There have been lots of advances in sensory perception, but we still know very little about higher cognitive processes, such as language and decision-making. . . . . .
. . . . . But humans do not function that way, and can transfer skills learned from one task to new, unrelated tasks. . .. . .
. . . . .I think the Holy Grail inartificial intelligence is to develop general intelligent systems that are mechanistically inspired by the brain and behaviorally similar to humans. Truly human-level intelligence systems should be able to process environmental information, define problems, and find solutions on their own. While the hard progress may not only be challenging higher cognitive functions. The key challenge is well articulated in the so-called Moravec's paradox. As Hans Moravec put it: ‘It's comparatively easy to make computers exhibit adult level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility. . . . .
. . . . . This is a golden era forneuroscience and artificial intelligence in China . . . . .
. . . . . Undergraduate education (in China) is very specialized these days. They have too many classes on specialized topics, and are reluctant to switch to a different field once graduated. In my view, researchers should switch fields much more often. It should be a norm rather than exception because that's how creative ideas come about. . . . . .
. . . . . There is a serious lack of significant breakthroughs and we definitely lags behind the West. . . .
It's due to China's strategic framework and the evaluation system . It's also to dowith the country's science culture, especially the tendency of jigongjinli [seeking quick success and short-term gains] . . . . . . .
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