While intricate deep models are all the rage in machine learning, my last post tried to make the case that we still need to care about model regularization. As it has been since the dawn of time, choosing simple models is still our best weapon against overfitting. But what does "simple" mean exactly? Of the many ways to measure simplicity, I've always been partial to the "minimum description length" principle: the fewer lines of code needed to train, store, and evaluate your model, the more robust that model likely is. Unfortunately, there aren't numerical methods that reliably compute models of minimum description length.

The IBM Watson IoT Platform allows people to securely and easily connect devices, from chips and intelligent appliances, to applications and industry solutions, and use cognitive services including natural language processing and machine learning for deep insights into hidden or "dark" data for innovation and transformation. The platform also provides the ability to analyze sensor data from billions of devices, to better forecast weather events, for example. During the hackathon, developers will use IBM Watson IoT cognitive APIs and smart devices to create conversational interfaces like chatbots. "People are excited about chatbots because they see the potential to interact with technology using conversational language," said Damian McCabe, VP Engineering at Connected Lab. "As an IBM alumni, I'm excited about the potential of the IBM Watson's cognitive capabilities including natural language processing and machine learning. At the hackathon, developers will use this powerful platform to build more human ways for people to use innovative technology."

"Science has not yet mastered prophecy. We predict too much for the next year and yet far too little for the next ten." These words, articulated by Neil Armstrong at a speech to a joint session of Congress in 1969, fit squarely into most every decade since the turn of the century, and it seems to safe to posit that the rate of change in technology has accelerated to an exponential degree in the last two decades, especially in the areas of artificial intelligence and machine learning. Artificial intelligence is making an extreme entrance into almost every facet of society in predicted and unforeseen ways, causing both excitement and trepidation. This reaction alone is predictable, but can we really predict the associated risks involved?

The word AI is increasingly bandied about with notable abandon. And, as I like to say, AI is the promise that keeps on promising. So I'm always encouraged when I see a humble but viable use of artificial intelligence, even if just a few years ago we may have simply called the nascent technology machine learning. The latest example is Picturesqe, a tool for professional photographers that uses what the U.S./Hungary startup calls AI-powered automation to help pick out the best snaps and filter out the dross. Features of the Windows app and Adobe Lightroom plugin (with a Mac version to follow shortly) include smart grouping, which automatically groups similar photos, intelligent zoom so that you can quickly compare the same spot on multiple shots, and the option to have Picturesqe pick out the best photos for you and delete the duds.

"We're going to use this technology to breathe life into the inanimate objects and devices of our life through conversation," said Siri co-founder and CEO Dag Kittlaus. Viv (which means life in Latin) offers an experience akin to the AI in the film Her. When Kittlaus asked, "Will it be warmer than 70 degrees near the Golden Gate Bridge, after 5pm, the day after tomorrow?" Viv quickly retrieved the correct hourly forecast from the Weather Underground app. When I asked the same question to Siri on my iPhone 6S, it pulled up the daily forecast from San Francisco for the next week, but it's unclear if it actually gave me predicted temperatures after 6pm.

Michael Fassbender is not a big video game guy – at least not anymore. In his younger days, the actor remembers coming home from a night job unloading boxes in a warehouse and playing one particular racing game. "I'd get obsessive about it and sit there for six hours straight," Fassbender said recently by phone from Australia, where he is currently shooting the next film in the "Alien" franchise. "I decided it wasn't the best thing for me to have around." When the French video game developer Ubisoft approached Fassbender a few years ago about signing on to a film adaptation of its popular game series "Assassin's Creed," he knew next to nothing about the game, which blends history, parkour-style action, sci-fi, conspiracy theories and, as the title suggests, a whole lot of stealthy killing.

Lynda Carter, best known for her portrayal of the original Wonder Woman, will be presented with a lifetime achievement award at the 41st annual Gracie Awards Gala, Variety has learned. The Gracie Awards recognize programming created by, for and about women in all media. Carter starred as the titular female superhero in "Wonder Woman," an adventure-drama series that ran on ABC and later CBS from 1975-1979. In the 2000s she guest starred on TV shows including "Law & Order," "Law & Order: SVU," "Smallville" and "Two and a Half Men." The actress also appeared in the 2005 movie reboot of "Dukes of Hazzard" alongside Johnny Knoxville and Jessica Simpson, and she later lent her voice to video games such as "The Elder Scrolls" series and "Fallout 4." Aside from acting, Carter devoted herself to singing, beauty pageants and charity work.

Greece is making a renewed move for the Parthenon Marbles. The Museum of Modern Art is offering buyouts. A board member for L.A.'s Museum of Contemporary Art is going to work for Donald "Build the Wall" Trump. Plus, a gun sculpture is censored at a Texas university, gender in museums, Moscow's terrible art, a history of female robots and the historic photography of L.A. forefather Charles Lummis. There's a ton to read in today's Roundup: Related: The Metropolitan Museum of Art's chief digital officer, Sree Sreenivasan, says he will not participate in all-male panels.

As a masters student exploring artificial intelligence at Stanford University almost 30 years ago, Reed Hastings no doubt had an eye on where the future might take him. But of all the scenarios he imagined for his career, it's highly unlikely that any of them included the one that unfolded this past week: strolling the red carpet in the south of France, rubbing shoulders with some of the country's most glamorous actors and actresses, and fielding questions about his role as a global media kingpin. It's a future the CEO of Netflix says he couldn't even have predicted five years ago, when the company was still primarily shipping DVDs to customers in the U.S. while grappling with its emerging video streaming service. Even now, the Internet continues to scramble the game so fast that Hastings said his company is racing to keep up with all the changes. When asked, he didn't even want to hazard a guess as to where Netflix might be five years from now. "We don't really know," Hastings said.

Shutterstock is flexing its AI muscles with the news that the stock photo giant is introducing new computer-vision search smarts to its platform. The company, which is headquartered in New York's Empire State Building, went public back in 2012 and now offers more than 70 million images for bloggers and media outlets -- which can make searching for specific assets challenging. Of course, the trusty old keyword search tool is effective to an extent, but what if you want to find images that are similar to one you have in your possession? Or what if you want alternative images based on color schemes, mood, or shapes? This is where Shutterstock's new reverse image search comes into play.