China lagged years, if not decades, behind the United States in artificial intelligence. But over the past three years China has caught AI fever, exp… - Kai-Fu Lee

the invention of deep learning means that we are moving from the age of expertise to the age of data. Training successful deep-learning algorithms requires computing power, technical talent, and lots of data. But of those three, it is the volume of data that will be the most important going forward. That’s because once technical talent reaches a certain threshold, it begins to show diminishing returns. Beyond that point, data makes all the difference. Algorithms tuned by an average engineer can outperform those built by the world’s leading experts if the average engineer has access to far more data.

In deep learning, there’s no data like more data. The more examples of a given phenomenon a network is exposed to, the more accurately it can pick out patterns and identify things in the real world.

Imagine, a $1,000 political assassin! And this is not a far-fetched danger for the future, but a clear and present danger.