As a venture capitalist, my team and I try to foresee the major disruptive trends ahead of most and it has become clear to us that we are moving from a world of machine automation to a world of autonomous machines. Sometimes some of the biggest disruptions are happening in plain sight of everyone but go unnoticed for years and can only be fully appreciated with a rear view mirror perspective! At BootstrapLabs we feel that the Autonomous Corporation is one of these mega trends silently awakening in the networks of every corporations around the world... For this reason we felt it was important to bring this topic at the forefront and bring our our AI community together on November 15th. We stand in front of the 4th and largest wave of the industrial revolution, powered by AI and Data.

These days there's no shortage of things to keep you awake at night, wherever you stand on the political spectrum. For others it's the prospect of Brexit being thwarted. For others still, it's whether the Chinese economy will hold up, what the outcome of the US presidential election will be or the risk of artificial intelligence taking over your job. So what's the best way to handle the inevitable anxiety that goes hand-in-hand with all that uncertainty? Will Borrell studied that anxiety up close after the Brexit vote in the UK earlier this year.

LONDON--(BUSINESS WIRE)--MediaGamma has announced the launch of a new Audience Prediction product, which is set to make a major impact on the ad tech market. By applying deep learning to unique data sets, coupled with MediaGamma's unique AI Decision Support Engine, the product is set to provide players in the ecosystem with over 90% certainty about a user's interests and demographic profile. The new product will help people to navigate uncertainty to make better decisions, and a major telecoms company has already signed up. The Audience Prediction product is the latest in a broad portfolio of products created by MediaGamma (http://www.mediagamma.com/), The start-up's world-renown team of data scientists deliver bespoke real time, prediction-based data science solutions focusing on online user behaviour.

Check out how three Galvanize students put together an IBM-inspired chess AI, and get the files for free on Github. This project focuses on computer science concepts such as data structures and algorithms. Chessnut is the chess engine we are using for all the moves and chess logic. Currently trying to implement multiprocessing as our recursive function uses a lot of computing power so calculating heuristics on board states more than 4 levels deep takes a lot of time. With a depth of 3 levels, our AI makes pretty good moves but also makes a lot of ill-advised ones as well. The AI's chess intelligence is estimated to be at a level 3 out of 9.

At its core, machine learning is a sub-field of artificial intelligence. Machines are being designed and developed in a way that they can not only process information but also mine the data being fed to come up with patterns and trends that facilitate decision making. Some machines have progressed to a point where they can make decisions without requiring human input. However, this is a basic definition of what machine learning is and how it works. To understand the concept better, here's a 5-point cheat sheet you can refer to: To sum it up, machine learning is a journey that enables organizations to be more data driven by using data to proactively make decisions.

DeepMind, an artificial intelligence firm that was acquired by Google in 2014 and is now under the Alphabet umbrella, has developed a computer than can refer to its own memory to learn facts and use that knowledge to answer questions. DeepMind says its new AI model, called a differentiable neural computer (DNC), can be fed with things like a family tree and a map of the London Underground network, and can answer complex questions about the relationships between items in those data structures. For example, you could get responses to questions like, "Starting at Bond street, and taking the Central line in a direction one stop, the Circle line in a direction for four stops, and the Jubilee line in a direction for two stops, at what stop do you wind up?" It's these networks that helped DeepMind's AlphaGo AI defeat world champions at the complex game of Go.

People have been dreaming of ways to hand off their more mundane work to machines for centuries. Advertisers in the 1930s spoke of "labor-saving devices" such as the toaster and electric kettle, and economists began to envision utopias in which machines wouldfree us from laborso we could follow our own creative pursuits. That's not as sci-fi as it sounds. Artificial intelligence has already proven effective atautomating repetitive tasks that salespeople, HR specialists, and small business owners used to spend hours each week on. Artificial intelligence allows people to spend those hours on the more thoughtful and creative aspects of their jobs.

This past May, China announced its AI roadmap for the next three years: The National Development and Reform Commission expects their artificial intelligence sector will give them a market worth topping 100 billion yuan (that's 15.26 billion) within that time period. Where is China's AI sector at now, and what steps could plausibly deliver that strong a return by 2019? Tech.Co had a chat with Luke Tang, General Manager of global entrepreneurship company TechCode, who drew on his experience working with AI companies worldwide to detail China's unique opportunities. Here are the biggest takeaways on AI in China. "China has already got a great start in both research and business applications in AI -- right behind the U.S. […] On the research side, the White House recently published a report showing that China has now surpassed the U.S. in total papers and citations published in Deep Learning or Neural Network, a crucial area in AI, but overall both the U.S. and China are way ahead of other countries. In fact, author's names with Chinese-origin represent about 50 percent of the articles published yearly in Deep Learning. Of course, there are other keywords one can use to search, e.g. computer vision, autonomous cars, natural language processing, etc. but it's very clear that the two leading countries in AI research are U.S. and China. This is actually very surprising to me, since China is not usually very strong in other fundamental sciences or computer science areas."

San Mateo-based Movidius may still be in the process of getting bought up by Intel, but the company's latest deal will put its low-power AI and computer vision platform into more than just DJI drones and Google VR headsets. The company announced today that the Movidius Myriad 2 Video Processing Unit (VPU) will soon power a new generation of Hikvision smart surveillance cameras capable of recognizing everything from suspicious packages to distracted drivers. While most deep-learning neural networks require a lot of cloud-based processing power, the same platform found in Movidius' Fathom AI-on-a-stick will allow Hikvision cameras to do more on-board processing. Hikvision's cameras have already been able to achieve around 99 percent accuracy in scenarios like identifying car models, detecting intruders, spotting suspicious baggage and even calling out drivers who don't buckle up. The Myriad 2 VPU basically puts all these capabilities in the camera itself, allowing it to instantly process everything it sees while reducing false alarms at the same time.

AUSTIN, Texas -- The race is on in Formula One. Not just to the checkered flag, but to see which team can marshall the best technology. In its 70th year, the preeminent auto-racing circuit has become a tech arms race. At the U.S. Grand Prix here this past weekend, the Internet of Things, big data, virtual reality, machine learning, 3-D printing, flash storage, predictive analytics and design play integral roles in the success (or failure) of the 22 drivers that compete in 21 races globally each year. The slightest advancement, or tweak, can mean the difference between first place and 10th place -- often the difference of one second.