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The Fourth Industrial Revolution is Here!

So much talk about AI and robots taking our jobs. Well, guess what, it’s already happening and the rate of change will only increase. I estimate that about 5% of jobs have been automated — both blue collar manufacturing jobs, as well as, this time, low-level white collar jobs — think back office, paralegals, etc. There’s a thing called RPA, or Robot Process Automation, which is hollowing out back office jobs at an alarming rate, using rules based algorithms and expert systems. This will rapidly change with the introduction of deep learning algorithms into these “robot automation” systems, making them intelligent, capable of making intuitive decisions and therefore replacing more highly skilled and creative jobs. So if we’re on an exponential curve, and we’ve managed to automate around 5% of jobs in the past six years, say, and the doubling is every two years, that means by 2030, almost all jobs will be automated. Remember, the exponential math means 1, 2, 4, 8, 16, 32, 64, 100%, with the doubling every two years.

We are definitely going to need a basic income to prevent people (doctors, lawyers, drivers, teachers, scientists, manufacturers, craftsmen) from going homeless once their jobs are automated away. This will need to be worked out at the government level — the sooner the better, because exponentials have a habit of creeping up on people and then surprising society with the intensity and rapidity of the disruptive change they bring. I’m confident that humanity can and will rise to the challenges ahead, and it is well to remember that economics is driven by technology, not the other way around. Education, as usual, is definitely the key to meeting these challenges head on and in a fully informed way. My only concern is when governments will actually start taking this situation seriously enough to start taking bold action. There certainly is no time like the present.

Google Doodle Honors Mathematician Johann Carl Friedrich Gauss

A German mathematician, physicist and astronomer, Johann Carl Friedrich Gauss rose from humble origins to become one of the world’s greatest minds.

Born in 1777 in Brunswick, then part of the Holy Roman Empire, Gauss was the only child of poor parents who had received little or no formal education. His mother was illiterate. But when Gauss started school at age seven, he was quickly recognized as a child prodigy who could solve complex math problems in his head.

While still a teenager, Gauss became the first person to prove the Law of Quadratic Reciprocity, a math theory to determine whether quadratic equations can be solved.

How AI is helping us discover materials faster than ever

Another problem is that we still don’t have enough data about every compound, according to Wolverton, and a lack of data means algorithms aren’t very smart. That said, he and Mehta are now interested in using their method on other types of materials beside metallic glass. And they hope that one day, you won’t need a human to do experiments at all, it’ll just be AI and robots. “We can create really a completely autonomous system,” Wolverton says, “without any human being involved.


For hundreds of years, new materials were discovered through trial and error, or luck and serendipity. Now, scientists are using artificial intelligence to speed up the process.

How Music Generated

There is an enduring fear in the music industry that artificial intelligence will replace the artists we love, and end creativity as we know it.

As ridiculous as this claim may be, it’s grounded in concrete evidence. Last December, an AI-composed song populated several New Music Friday playlists on Spotify, with full support from Spotify execs. An entire startup ecosystem is emerging around services that give artists automated songwriting recommendations, or enable the average internet user to generate customized instrumental tracks at the click of a button.

But AI’s long-term impact on music creation isn’t so cut and dried. In fact, if we as an industry are already thinking so reductively and pessimistically about AI from the beginning, we’re sealing our own fates as slaves to the algorithm. Instead, if we take the long view on how technological innovation has made it progressively easier for artists to realize their creative visions, we can see AI’s genuine potential as a powerful tool and partner, rather than as a threat.

Google made an AR microscope that can help detect cancer

In a talk given today at the American Association for Cancer Research’s annual meeting, Google researchers described a prototype of an augmented reality microscope that could be used to help physicians diagnose patients. When pathologists are analyzing biological tissue to see if there are signs of cancer — and if so, how much and what kind — the process can be quite time-consuming. And it’s a practice that Google thinks could benefit from deep learning tools. But in many places, adopting AI technology isn’t feasible. The company, however, believes this microscope could allow groups with limited funds, such as small labs and clinics, or developing countries to benefit from these tools in a simple, easy-to-use manner. Google says the scope could “possibly help accelerate and democratize the adoption of deep learning tools for pathologists around the world.”

The microscope is an ordinary light microscope, the kind used by pathologists worldwide. Google just tweaked it a little in order to introduce AI technology and augmented reality. First, neural networks are trained to detect cancer cells in images of human tissue. Then, after a slide with human tissue is placed under the modified microscope, the same image a person sees through the scope’s eyepieces is fed into a computer. AI algorithms then detect cancer cells in the tissue, which the system then outlines in the image seen through the eyepieces (see image above). It’s all done in real time and works quickly enough that it’s still effective when a pathologist moves a slide to look at a new section of tissue.

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