Future computers will be smarter than humans, but they'will never be wiser' Internet tycoons have reached a rare consensus on the promise of artificial intelligence following the historic victory earlier this month for Google Inc's AI-powered AlphaGo over its human competitor, South Korean Go master Lee Se-dol. The widely watched five-match series came to a close on Tuesday, with four victories for the machine to the human's one. Mark Zuckerberg, CEO of Facebook Inc, told an audience at the China Development Forum in Beijing on Saturday that he predicted more great advances for AI within the next decade. "Artificial intelligence will understand senses, such as vision and hearing, and grasp language better than human beings over the next five to 10 years," he said. Lei Jun, founder and chairman of Chinese smartphone giant Xiaomi Corp, agreed, describing the win as a breakthrough in artificial intelligence.

Google has a special way to improve the quality of search results: artificial intelligence (AI.) The company uses a type of AI known as machine learning to figure out what its users really want to search for. Machine learning is where a computer gradually teaches itself how to perform a task. One example of that is Google DeepMind, which learned how to play retro arcade games over time. Google's machine learning system for search is called RankBrain, and it tries to figure out what a user is searching for.

This is the first video in our new video series, Deep Breath. I find it interesting that there are so many dystopian visions about Artificial Intelligence in popular culture and media nowadays. I want to invite you to a thought experiment here. What if consciousness, minus the human body with all of our tendencies towards violence, addiction, fear, attachments, is enlightenment? Most scientists and thinkers about Artificial Intelligence believe that if we succeed, we will be creating gods.

Dan Chao is an avid cyclist who likes to train on a stationary bike. Lately while training he's been sporting a pair of trendy-looking headphones that also stimulate his brain. And he says the device has helped him improve his performance on his real bike. Chao is a cofounder and the CEO of a startup called Halo Neuroscience, which released the neurostimulating headphones, called Halo Sport, last month. The arch of the headphones contains two electrodes that deliver a very small amount of electric current to the wearer's head, aimed at the neurons in the motor cortex, a brain region that coördinates movement. The mild stimulation, called transcranial direct current stimulation, essentially makes it "slightly easier for the neurons to fire," says Chao.

This was the title of a very popular book published in 2012, featuring several job interview questions (brain teasers) asked by Google's hiring managers to candidates. They apparently dropped all these questions, as they found out that they were not good indicators of career success. Do you think you are smart enough to work for Google? I had one phone interview with Google long ago, and was rejected right away. The interviewer was just focused on very technical details, and spent all her time arguing about Lasso regression, and was clearly looking for a specialist, dismissing people with a broad range of skills and non-standard approach to solving tech problems.

No longer the exclusive domain of data-reliant businesses like Google, Microsoft, and Amazon, machine learning has been making its way into the masses as an essential approach to data. Today, machine learning is understood and accepted by a more mainstream audience, and has become a measurable driver for big business benefits both on and offline. There are three key reasons why machine learning has become one of the top 10 strategic technology trends that will shape digital business opportunities through 2020. First, the volume of data companies now collect is so massive that many companies struggle to make sense of it and fail to take advantage of it. Second, the computing power required to process these exploding data assets, previously exclusive to the Googles of this world, is now widely available to smaller businesses.

God moves the player, he in turn the piece. But what god beyond God begins the round Of dust and time and sleep and agony? As I write this column, a computer program called AlphaGo is beating the professional go player Lee Sedol at a highly publicized tournament in Seoul. Sedol is among the top three players in the world, having attained the highest rank of nine dan. The victory over one of humanity's best representatives of this very old and traditional board game is a crushing 3 to 1, with one more game to come.

Hewlett Packard Enterprise outlined a machine-learning-as-a-service effort that runs on Microsoft's Azure platform. The service, called HPE Haven OnDemand, provides application programming interfaces as well as services for enterprise software. The service is part of an ongoing partnership between HPE and Microsoft's Azure cloud unit. Simply put, HPE Haven OnDemand is the cloud version of its big data analytics software. Testing on the service is free.

One of the things I love about my job is seeing how today's technologies can enable new ways of doing things that make a real impact on people's lives. Case in point: The dyslexia-screening tool developed by Optolexia, which was named a "Future Swedish Innovator" by SvD, one of the largest newspapers in Sweden. Taking advantage of the cloud computing and machine learning Optolexia aims to help schools identify students at risk for dyslexia significantly earlier than current screening tests. Its solution is a great example of a project that falls into the upper left quadrant of the four-block diagram tool I covered in a previous blog, which is to say that it's a project that benefits tremendously from being in the cloud with relatively low risk and it was able to be implemented quickly. As many as 10–15 percent of school-age children are dyslexic, and the International Dyslexia Association estimates there are 1 billion people with dyslexia worldwide.

We cover many emerging markets in the startup ecosystem. Previously, we published posts that summarized Financial Technology, Internet of Things, Bitcoin, and MarTech in six visuals. This week, we do the same with Artificial Intelligence (AI). At this time, we are tracking 855 AI companies across 13 categories, with a combined funding amount of 8.75billion. To see all of our AI related posts, check out our blog!