The fields of Blockchain and Artificial Intelligence are converging, and they will intersect soon. Artificial Intelligence and Machine Learning require vast amounts of data. Meanwhile, Blockchain allows for decentralized autonomous organizations which will soon involve hundreds of millions of people. Furthermore, platforms built on Blockchain technology will soon be powerful enough to support AI applications. At that point, AI could evolve very quickly and become, effectively, an unstoppable utility for the world's population.

Underground mining poses a number of threats including fires, methane outbreaks or seismic tremors and bumps. An automatic system for predicting and alerting against such dangerous events is of utmost importance – and also a great challenge for data scientists and their machine learning models. This was the inspiration for the organizers of AAIA'16 Data Mining Challenge: Predicting Dangerous Seismic Events in Active Coal Mines. Our solutions topped the final leaderboard by taking the first two places. In this post, we present the competition and describe our winning approach.

Security cameras are great, but only when they're actually pointed at whatever is going on. Alarm has developed a machine learning algorithm, called the Insights Engine, that continually monitors sensors placed around your property to learn how things are normally run and to quickly identify unexpected events -- say, a break-in or a water leak -- when they occur. If the system does spot something out of the ordinary, it will deploy a swarm of autonomous UAVs built on Qualcomm's Snapdragon Flight drone platform to investigate. These little fliers will swarm over the event site and provide live video feeds to your phone. You can also opt in to share that video data with either Alarm.com's

Eight out of ten B2B marketing executives predict artificial intelligence (AI) will revolutionize marketing by 2020, according to a December report by Demandbase -- but is it the key to unlocking a future without email spam? Demandbase, an account-based marketing (ABM) platform, partnered with Wakefield Research to poll 500 B2B marketers from the manager level to c-level executives, at companies with at least 250 employees, about AI-driven marketing. The results of the study suggest that marketers are eager to embrace artificial intelligence, yet only 10% of respondents are currently using AI and only 26% of marketers are confident that they understand how artificial intelligence can be applied to marketing. Education and integration concerns are the largest hurdles obstructing marketers with regard to artificial intelligence. Integrating AI into an existing marketing stack was the top-ranking challenge expressed by marketers when they considered incorporating AI into their marketing campaigns, with 60% of marketers selecting it as their top concern.

In this article, I clarify the various roles of the data scientist, and how data science compares and overlaps with related fields such as machine learning, deep learning, AI, statistics, IoT, operations research, and applied mathematics. As data science is a broad discipline, I start by describing the different types of data scientists that one may encounter in any business setting: you might even discover that you are a data scientist yourself, without knowing it. As in any scientific discipline, data scientists may borrow techniques from related disciplines, though we have developed our own arsenal, especially techniques and algorithms to handle very large unstructured data sets in automated ways, even without human interactions, to perform transactions in real-time or to make predictions. To get started and gain some historical perspective, you can read my article about 9 types of data scientists, published in 2014, or my article where I compare data science with 16 analytic disciplines, also published in 2014. I also wrote about the ABCD's of business processes optimization where D stands for data science, C for computer science, B for business science, and A for analytics science.

Way back in 1969, as a kid, I watched a very interesting movie - "2001: A Space Odyssey." It was a science fiction where a super intelligent computer program HAL is in charge of a mission to Jupiter which also carries several astronauts. The program becomes rogue and tries to kill all the astronauts. The hero survives and manages to disable the program. There is a lot more to the plot, but the fight between human and computer is still vivid in my memory. In 1969, such a scenario looked possible. After all 32 years is a lot of time given the rate of our progress.

"We are Now Controlling the Transmission" If you aren't familiar with the 60's TV series "The Outer Limits" you need to watch this intro (its 58 seconds long). Artificial Intelligence is controlling more than you realize, and in 2017, it's going to accelerate. AI algorithms are already affecting which products & services you see when you perform a search – regardless of the device or interface. AI is pushing messages, offers, & advice to you that you may never have asked for. Artificial Intelligence is deciding what shows up in your news feeds, on the sites you frequent, and in the apps you use.

SINGAPORE--The acclaimed HBO sci-fi series, "Westworld," may have wrapped up recently, but that's no reason to fret, James Marsden told the Inquirer when we chatted with him early this month. What are your thoughts about artificial intelligence (AI)? There's a quote that says it all: With great power comes great responsibility. That's what we should keep in mind when it comes to the future of artificial intelligence. There are smarter people out there who know its potential more than we do.

I've been following the idea of algorithm-driven design for several years now and have collected some practical examples. The tools of the approach can help us to construct a UI, prepare assets and content, and personalize the user experience. The information, though, has always been scarce and hasn't been systematic. However, in 2016, the technological foundations of these tools became easily accessible, and the design community got interested in algorithms, neural networks and artificial intelligence (AI). Now is the time to rethink the modern role of the designer. One of the most impressive promises of algorithm-driven design was given by the infamous CMS The Grid3. It chooses templates and content-presentation styles, and it retouches and crops photos -- all by itself. Moreover, the system runs A/B tests to choose the most suitable pattern.

In this article, I clarify the various roles of the data scientist, and how data science compares and overlaps with related fields such as machine learning, deep learning, AI, statistics, IoT, operations research, and applied mathematics.