Reality Check on AI

Mar 21, 2019

Utopian and dystopian visions of the super-intelligent future inspire both awe and a sense of dread in audiences.

Those all-consuming emotions then blur the lines in our mind separating these fantastical futures from our current age of AI implementation. The result is widespread popular confusion over where we truly stand today, and where things are headed.

Utopia, Dystopia, and the Real AI Crisis

Mar 19, 2019

All of the AI products and services outlined in the previous chapter are within reach based on current technologies. Bringing them to market requires no major new breakthroughs in AI research, just the nuts-and-bolts work of everyday implementation: gathering data, tweaking formulas, iterating algorithms in experiments and different combinations, prototyping products, and experimenting with business models.

But the age of implementation has done more than make these practical products possible. It has also set ablaze the popular imagination when it comes to AI. It has fed a belief that we’re on the verge of achieving what some consider the Holy Grail of AI research, artificial general intelligence (AGI)—thinking machines with the ability to perform any intellectual task that a human can—and much more.

Conquering Markets and Arming Insurgents

Mar 14, 2019

What happens when you try to take game-changing AI products global?

Thus far, much of the work done in artificial intelligence has been contained within the Chinese and U.S. markets, with companies largely avoiding direct competition on the home turf of the other nation. But despite the fact that the United States and China are the two largest economies in the world, the vast majority of AI’s future users still live in other countries, many of them in the developing world. Any company that wants to be the Facebook or Google of the AI age needs a strategy for reaching those users and winning those markets.

The Autonomous AI Balance of Power

Mar 12, 2019

While new developments in AI may sound exciting and innovative to the Chinese landscape, the hard truth is no amount of government support can guarantee that China will lead in autonomous AI.

When it comes to the core technology needed for self-driving cars, American companies remain two to three years ahead of China. In technology timelines, that’s lightyears of distance. Part of that stems from the relative importance of elite expertise in fourth-wave AI: safety issues and sheer complexity make autonomous vehicles a much tougher engineering nut to crack. It’s a problem that requires a core team of world-class engineers rather than just a broad base of good ones. This tilts the playing field back toward the United States, where the best engineers from around the globe still cluster at companies like Google.