As if quantum computing wasn't mind-bending enough, one of D-Wave Systems' founders is now pursuing another futuristic idea: using artificial intelligence and high-tech exoskeleton suits to allow humans--and, at least according to one description of the technology, monkeys--to control and train an army of intelligent robots. Geordie Rose is a cofounder and chief technology officer of D-Wave, the Canadian company selling machines that it claims exploit quantum mechanical effects to solve certain problems hundreds of millions times faster than traditional computers. Now an IEEE Spectrum investigation has discovered that Rose is also CEO of Kindred Systems (aka Kindred AI), a stealthy startup he founded with others in 2014 dedicated to delivering advanced teleoperated and autonomous robots. The goal is making programming robots faster and less costly–and possibly revolutionize the world of work. Kindred has so far received well over US 10 million in funding, according to Data Collective, the venture capital firm that led one of the rounds.

Compelling data reveal a discouraging truth about growth today. There has been a marked decline in the ability of traditional levers of production--capital investment and labor--to propel economic growth. Yet, the numbers tell only part of the story. Artificial intelligence (AI) is a new factor of production and has the potential to introduce new sources of growth, changing how work is done and reinforcing the role of people to drive growth in business. Accenture research on the impact of AI in 12 developed economies reveals that AI could double growth rates in 2035 by changing the nature of work and creating a new relationship between man and machine.

IBM is applying the advanced cognitive computing capabilities of its Watson technology to a new cloud-based data and analytics platform called Project DataWorks. Running in the company's Bluemix hybrid cloud development platform, Project DataWorks integrates data of all types into one system so companies can quickly make decisions based on business insights gleaned from analytics projects powered by artificial intelligence (AI) and machine learning (ML). IBM said its new initiative frees up developers and data scientists from the mundane and time-consuming task of finding relevant data and preparing it for analysis. "We are at an inflection point in the Big Data era," said exec Bob Picciano. "We know that users spend up to 80 percent of their time on data preparation, no matter the task, even when they are applying the most sophisticated AI. Project DataWorks helps transform this challenge by bringing together all data sources on one common platform, enabling users to get the data ready for insight and action, faster than ever before."

You wouldn't think that articles on business and tech topics would make for the most beautiful music, but believe it or not, they were used by an artificial intelligence system and human composers to create an original symphony. It sounds like science fiction, but last week inside the Louvre Pyramid in Paris, a 50-piece orchestra performed "Symphonologie," a "symphonic experience" from Accenture Strategy, a business and technology consulting firm. The project aims to shed light on the tangible uses of this kind of artificial intelligence and its broad potential. "Initially, we talked about what could be a way for us to grab our clients and others in the business world? What would draw their attention? We wanted to show what's happening with digital and technology, and we thought about metaphors that cross cultures. We realized that music cuts straight through the list – there are so many different cultures and spoken languages around the world and we quickly went to music as something that transcends culture," Mark Knickrehm, group chief executive at Accenture Strategy, told CBS News. "The big question was how do you make music in the digital space using technology and artificial intelligence? It was quite creative to go from there. Words have real meaning, and they can make music."

Latina and Latin American women artists rarely get air time in U.S. museums. That will change next fall when the Pacific Standard Time series of exhibitions devoted to art from Latino and Latin American artists around the globe is set to touch down in Los Angeles. Of particular note will be "Radical Women: Latin American Art, 1960-1985," at the Hammer Museum, set to take place in the fall of 2017. Today, the museum released the list of participating artists -- a lengthy lineup that includes 260 works by 118 artists (all women) from the U.S., Mexico, Central America, the Caribbean and South America. Even Paraguay, never a contender in surveys about Latin American art, has two artists represented in the show.

A drone is a flying, autonomous camera. A drone is so much a flying camera that in a release video for their newest drone, dronemakers DJI don't even say the word "drone," instead just referring to the latest unmanned aerial vehicle as a "flying camera." The features that make it drone-like: remote controls, onboard stabilization and obstacle avoidance sensors, GPS location and navigation programs, are really just camera accessories, part of the built-in airborne body for the new selfie machine. And the body is compact. "Mavic," DJI's latest drone, folds up, and is designed for backpacks and large pouches, rather than large, bulky, specialized carrying cases.

I have read a book or some posts on machine learning. I have watched some of the Coursera machine learning course. I still don't know how to get started… How do you get started in machine learning? The most common question I'm asked by developers on my newsletter is: I honestly cannot remember how many times I have answered it. In this post, I lay out all of my very best thinking on this topic. You are a developer and you're interested in getting into machine learning. You read some blog posts. You tried to go deeper but the books are dreadful.

Automation, artificial intelligence and machine learning were key themes at the Structure Security conference in San Francisco. For business tech leaders, the bottom line is that security and automation are blending together. The trick for tech buyers will be to sort through what platforms are legit vs. mere marketing and buzzwords. Jay Leek, chief information security officer at private equity firm Blackstone, said his company started an effort to automate investigations, rote security tasks and other items in a bid to alleviate a security talent crunch and boost productivity. The upshot: Leek's security analysts do more high value work and initial investigations now take 40 seconds.

The introduction of connected machines into industrial environments has raised quality standards, led to increased profits and improved the maintainability of both manufacturing equipment and end products. Manufacturers that have integrated their production floors with other aspects of the business (including design, sales and supply chain) are seeing the largest benefits as the machine learning aspect of connected networks trickles into all areas of the business. Here is a look at six ways machine learning is impacting industrial business. One clear indicator that machine learning and artificial intelligence are coming together to improve customer relationship management is Salesforce's acquisition of several Machine Learning and AI companies. Since 2014, Salesforce has acquired six AI and Machine Learning companies including: RelateIQ, TempoAI, MinHash, PredicitonIO, MetaMind and Implisit Insights.

TensorFlow has been open to the public for about a year now and the buzz is real. Everyone is building models using TensorFlow, and we even have some state of the art examples such as: Parsey McParseface. As a data scientist at Old Street Labs(OSL) one of the most common questions I'm asked is how we deploy models and manage those in a production environment. TensorFlow Serving makes it simple and quick to deploy your models into a production environment. It also works with TensorFlow models out of the box without much modification. The purpose of this tutorial is to provide a brief introduction into TensorFlow Serving by walking through the process of deploying a TensorFlow model inside a Docker container.