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.

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!

There is a plethora of new technologies entering the big data landscape, but perhaps the most avidly discussed in 2015 was Apache Spark. Some view this tool as a more accessible and powerful alternative to Hadoop, while others argue Spark can be used as a powerful complement to Hadoop, with its particular strengths and quirks. But what are the facts? Who is using Spark and how does it differ from other data processing engines? An all-purpose data processing engine, Spark can be used for a variety of operations. Data scientists and application developers can integrate Spark into their applications to query, analyse, and transform data quickly and at scale.

While being a vibrant subfield of computer science, machine learning is used for drawing models and methods from statistics, algorithms, computational complexity, control theory and artificial intelligence. It focuses on efficient algorithms for inferring good predictive models from large data sets and is natural candidate for problems arising in HFT – both trade execution & alpha generation. In quantitative finance inference of models of predictive nature using historical data is obviously not new. Some examples include the coefficient estimation for CAPM, Fama and French factors. The granularity of data arising in HFT poses special challenges for machine learning. Often data microstructure at the resolution of individual orders, executions, hidden liquidity and cancellation including lack of understanding of how such granular data relates to actionable circumstances, namely profitably buying or selling shares, optimally executing a large order, etc.

With a photo of Zuckerberg and his bodyguards jogging past Tian'anmen Square in Beijing on a heavily polluted day Friday, Zuckerberg announced his arrival and sparked heated online discussion in the process. He continued to grab public attention as he met and had a dialogue with Chinese tech mogul Jack Ma, the chairman of the Chinese tech mammoth Alibaba Group, at the China Development Forum, a state-sponsored forum. What did the two discuss? Have a look with AllChinaTech. On innovation When asked about his opinion of China's next five-year development plan, which highlights innovation, Zuckerberg talked about innovation being dedicated to solving long-term problems.