China is the saudi arabia of data
But this Chinese commitment to grunt work is also what is laying the groundwork for Chinese leadership in the age of Al implementation. By immersing themselves in the messy details of food delivery, car repairs, shared bikes, and purchases at the corner store, these companies are turning China into the Saudi Arabia of data: a country that suddenly finds itself sitting atop stockpiles of the key re-source that powers this technological era. China has already vaulted far ahead of the United States as the world's largest producer of digital data, a gap that is widening by the day.
As I contended in the first chapter, 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 out-perform those built by the world's leading experts if the average engineer has access to far more data. But China's data advantage extends from quantity into quality. The country's massive number of Internet users — greater than the United States and all of Europe combined—gives it the quantity of data, but it's then what those users do online that gives it the quality. The nature of China's alternate universe of apps means that the data collected will also be far more useful in building Al-driven companies. Silicon Valley juggernauts are amassing data from your activity on their platforms, but that data concentrates heavily in your online behavior, such as searches made, photos uploaded, YouTube videos watched, and posts 'liked: Chinese companies are instead gathering data from the real world: the what, when, and where of physical purchases, meals, makeovers, and transportation. Deep learning can only optimize what it can "see" by way of data, and China's physically grounded technology ecosystem gives these algorithms many more eyes into the content of our daily lives. As Al begins to "electrify" new industries, China's embrace of the messy details of the real world will give it an edge on Silicon Valley.
We are still the masters of our fate. Rational thinking, even assisted by any conceivable electronic computors, cannot predict the future. All it can do is to map out the probability space as it appears at the present and which will be different tomorrow when one of the infinity of possible states will have materialized. Technological and social inventions are broadening this probability space all the time; it is now incomparably larger than it was before the industrial revolution—for good or for evil.
The future cannot be predicted, but futures can be invented.
It was man’s ability to invent which has made human society what it is. The mental processes of inventions are still mysterious. They are rational but not logical, that is to say, not deductive.
Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultraintelligent machine could design even better machines; there would then unquestionably be an ‘intelligence explosion’, and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make, provided that the machine is docile enough to tell us how to keep it under control.
Social media has given everyone a virtual megaphone to broadcast every thought, along with the means to filter out any contrary view [...] The result is a creeping sense of isolation and emptiness, which leads people to swipe, tap, and click all the more. Digital distraction keeps the mind occupied but does little to nurture it, much less cultivate depth of feeling, which requires the resonance of another’s voice within our very bones and psyches.
Moravec's paradox is the observation by artificial intelligence and robotics researchers that, contrary to traditional assumptions, reasoning (which is high-level in humans) requires very little ...
Almost always the men who achieve these fundamental inventions of a new paradigm have been either very young or very new to the field whose paradigm they change. And perhaps that point need not have been made explicit, for obviously these are the men who, being little committed by prior practice to the traditional rules of normal science, are particularly likely to see that those rules no longer define a playable game and to conceive another set that can replace them.