While speaking with the Times, Urs Hölzle, an executive from Google cloud, stated that he believes that the business of renting out machine learning capabilities will take over Google’s advertising revenue one day. Meaning, that he is predicting that Google Robots will be bigger than Google search, which brought in $16.4 billion in profits last year.
Machine learning is a new branch of computer science where systems have the ability to train themselves in pattern recognition, or learn things for themselves. Because they can learn on their own, they do not require a programmer to teach them what works and what does not work.
In October 2015, Google created AlphaGo, a robot that mastered the game of Go, a game created in China 2,500 years ago. The game begins with an empty board, two players using different colored stones, which alternate placing stones in squares while trying to grab territory while avoiding getting their pieces taken. AlphaGo learned the game of Go itself, and just beat the human champion in the seemingly impossible to master game. Techinsider states that in the game of Go, “there are more possible game states than atoms in the universe.”
Many companies are on a quest for machine learning products—which could take over many jobs that are currently completed by humans. Industries as diverse as advertising, energy, cars, medicine, and finance are all being affected by machine learning. Already, at Goldman Sachs, the responsibilities of $350,000 a year jobs are being automated.
Although the Techinsider article did a great job of explaining what machine learning is and the amazing technological advances that have surfaced because of it, it failed to mention any cons to machine learning. This technological advance could be beneficial in some aspects, it would exponentially increase the unemployment rate, leaving more and more people without jobs every year. This advance could be detrimental to the economy, as the machine learning devices are expensive to produce, and so many people will be out of jobs. The article also did not state how much it costs or how long it takes to create products like the AlphaGo or the driverless car. Do the machines learn things quickly, or did it take years for the AlphaGo to master the game of Go?