Investors poured a record high 1.05B into artificial intelligence startups in Q2'16, and AI is already affecting more areas of our lives than many people realize. Even retail and e-commerce companies are increasingly integrating the technology. Recently there's been a rush of AI announcements and acquisitions by major retailers: Just this week, Etsy acquired Blackbird to enhance its search functionality through AI, followed the very next day by Amazon acquiring Angel.ai And earlier this month, e-commerce unicorn Houzz (see our full unicorn tracker here) announced a deep learning initiative to help users find and buy products by clicking on images. Using CB Insights data, we dove into the wide array of AI startups focused on retailers and e-commerce businesses, including AI-powered personal shopping apps, natural language processing and image recognition tools for shopping websites, predictive inventory allocation tools, and more.

For Matt Osborne, finding exploited children typically starts with a walk on the beach, and it ends with hands cuffed behind his back. It's almost always the same--Osborne and a few friends travel somewhere that's known for sex tourism and walk along the beach or hang in area nightclubs, not to look for girls but to be seen themselves. A group of white American men is easy to spot in heavily-touristed resort towns in Asia, Central America, and South America, so it doesn't take long to make a connection. "They approach us," Osborne says. "At first, everything is innocuous. Want to go jet ski or parasailing? Buy a margarita or beer? They offer us drugs, and the conversation always turns to girls. And if you let them talk long enough and say, 'What else do you have? What else do you have?' Then sooner or later, they always offer us young girls."

I have a little secret: I don't like the terminology, notation, and style of writing in statistics. I find it unnecessarily complicated. This shows up when trying to read about Markov Chain Monte Carlo methods. Take, for example, the abstract to the Markov Chain Monte Carlo article in the Encyclopedia of Biostatistics. Markov chain Monte Carlo (MCMC) is a technique for estimating by simulation the expectation of a statistic in a complex model. Successive random selections form a Markov chain, the stationary distribution of which is the target distribution.

That's how much content will be captured by 2020 by surveillance cameras across the globe. These one billion cameras -- twice today's number -- will be at traffic intersections, transit stations and other public areas, helping to make our cities safer and smarter. They'll be in retail stores, service centers, warehouses, and more, gathering information to boost sales, track inventory and improve service. But how to make sense of this staggering number of pixels? But a branch of artificial intelligence called deep learning offers a powerful, scalable method for extracting the most out of these vision systems.

The Nuggy Smoker's Multi-Tool is a ten-in-one tool that takes all the mess out of the smoking process – from packing to scraping it clean. The Nuggy comes in handy in tons of different situations outside of smoking too.

Artificial intelligence companies are sprouting up all over, though AI itself is far from new. At its deepest sense, artificial intelligence (AI) has been around for a very long time -- its intellectual roots are found in Greek mythology. To be sure, artificial intelligence has come a long way recently, with rapid advancements ranging from virtual assistants (such as Apple's Siri) to fraud detection, this emerging tech now plays a part in everyday life. According to CB Insights, over 30 artificial intelligence companies have been acquired recently. Clearly, there is interest in artificial intelligence and its ability to improve the human experience, despite pushback from naysayers who warn of AI's disruption.

Pixelation is used heavily across the media to obscure faces, vehicle license plates and restricted pieces of text. The technique generally works well, preventing people from identifying what's beneath the blur without completely destroying the image with overlays or cut-outs. However, we may soon need to find an alternative to pixelation, according to researchers at the University of Texas. WIRED reports that a team has developed software that is able to see through a pixelated mask to determine the identity of a person beneath it. The technology is able to process images as if the pixelation simply didn't exist.

It was an experiment straight out of "2001: A Space Odyssey." In an effort to gauge the accuracy of AI technology, researchers presented real estate journalist John Rebchook with several recommended listings. The recommendations, which were based on a home Rebchook liked, came in two sets – one from Denver-area brokers, another from "Find More Genius," a computer algorithm that Denver-area broker Creed Smith had created. In the end, the humans did not stand a chance. Over three separate days of testing, Rebchook's favorite recommendation came from the algorithm each day, as did two of his three overall favorites.

In this interview, we chat with Wizeline's head of growth, Matt Pasienski. As a PhD-educated data scientist and chatbot enthusiast, Matt has lots of interesting opinions on the emerging role of artificial intelligence in the worlds of business and social media. So if you're curious about any of these topics, don't be afraid to hit him up on Twitter. To learn more about Matt and our team's work on chatbots, visit Wizeline's solutions page. Adam: Everyone, welcome to the program, I'm Adam, and today we're being joined by Matt Pasienski who runs the services team at Wizeline.

Azure Machine Learning is an end to end solution that facilitates descriptive, predictive and prescriptive analysis. Working with Azure ML helps data scientists easily publish their code as a web service, to be accessible from different platforms. Data scientists can publish their R code directly from R Studio into Azure ML and create a web service that can be called from any other application. Imagine that we have a simple function in R Studio for calculating the sum of two variables. We are going to create an API (web service) for this function that can be called from other platforms (eg mobile applications, web applications).