Last week I came across this all-too-true tweet poking fun at the ubiquity of the Iris dataset. I'm sure many people who've taken a stats course can relate! While Iris may be one of the most popular datasets on Kaggle, our community is bringing much more variety to the ways the world can learn data science. There's so much data to analyze! Me: Cool let me at it.

Brad Hill knew what the jumbled letters represented, but he had no idea where they would lead. A handful of players had started finding strange things in Trials HD, a game released in 2009 by Finnish studio RedLynx in which you drive stunt bikes over outlandish obstacle courses. The mathematical patterns and cryptic messages discovered in the game's more hard-to-reach places hinted at something beyond high scores. One player uploaded a screenshot of some brass plaques he had found strewn on the ground after crashing his bike through a trapdoor. They were covered in what looked like a coded message and the player wanted to know what it meant.

"AI teaches us who we are," says Richard Socher. The recent rapid progress in the field of artificial intelligence is the result of successfully processing "a large amount of known training data, doing things [the computer] has seen before," he says. Unlike humans, computers cannot create something new and unique. Human creativity has been the driving force behind scientific and engineering advances, including making computers do more human-like activities such as identifying objects or words. Socher's creativity, his ability to come up with new approaches to solving computers' language and visual processing challenges, has made him a rising star of the deep learning movement that has spawned exciting new applications of artificial intelligence.

News headlines might not be the only things that are fake in the future. Powerful machine-learning techniques (see "The Dark Secret at the Heart of AI") are making it increasingly easy to manipulate or generate realistic video and audio, and to impersonate anyone you want with amazing accuracy. A smartphone app called FaceApp, released recently by a company based in Russia, can automatically modify someone's face to add a smile, add or subtract years, or swap genders. The app can also apply "beautifying" effects that include smoothing out wrinkles and, more controversially, lightening the skin. And last week a company called Lyrebird, which was spun out of the University of Montreal, demonstrated technology that it says can be used to impersonate another person's voice.

Digital healthcare company, Babylon Health, have raised about £50 million to further develop its artificial intelligence clinical diagnosis capabilities. Babylon says the new AI tool will help clinicians by providing them with a diagnosis of more routine conditions. Planned capabilities include using natural language processing to take notes in patient consultations. Speaking to Digital Health News, Ali Parsa, founder and chief executive of Babylon, claimed the new diagnosis tool could potentially cut the cost of a consultation by 80%. He said the latest £50m raised by Babylon that the money will go towards "engineering and mass producing the technology" for a new AI tool that will help clinicians by providing diagnosis of more routine conditions.

Good parties diverge widely; all bad parties are bad in the same way. I am trapped at a dull dinner following a dull talk: part of a series of dinners and talks that grad students organise, unpaid (though at considerable expense to themselves--experience! exposure!), to provide free content for the dull grad program I will soon leave. The Thai food is good. The man sitting across from me and a little down the way, a bellicose bore of vague continental origin, is execrable. He is somehow attached to a mild woman who is actually supposed to be here: a shy, seemingly blameless new grad student who perpetually smiles apologetically on his behalf, in an attempt to excuse whatever he's just said. One immediately understands that she spends half her life with that worry in her eyes, that Joker-set to her mouth, and that general air of begging your pardon for offences she hadn't even had the pleasure of committing. There is always such a woman at bad parties. She has always either found ...

We consider the inference of the structure of an undirected graphical model in an exact Bayesian framework. More specifically we aim at achieving the inference with close-form posteriors, avoiding any sampling step. This task would be intractable without any restriction on the considered graphs, so we limit our exploration to mixtures of spanning trees. We consider the inference of the structure of an undirected graphical model in a Bayesian framework. To avoid convergence issues and highly demanding Monte Carlo sampling, we focus on exact inference. More specifically we aim at achieving the inference with close-form posteriors, avoiding any sampling step. To this aim, we restrict the set of considered graphs to mixtures of spanning trees. We investigate under which conditions on the priors - on both tree structures and parameters - exact Bayesian inference can be achieved. Under these conditions, we derive a fast an exact algorithm to compute the posterior probability for an edge to belong to {the tree model} using an algebraic result called the Matrix-Tree theorem. We show that the assumption we have made does not prevent our approach to perform well on synthetic and flow cytometry data.

Big data in machine learning is the future. But how to deal with data analysis and limited resources: Computational power, data distribution, energy or memory? From September 25th to 28th, 2017 TU Dortmund University, Germany, hosts the 4th summer school on resource-aware machine learning. Topics of the lectures include: Exercises help bringing the contents of the lectures to life. The PhyNode low power computation platform was developed at the collaborative research center SFB 876.

There is so much written on this debate that it is nearly impossible to read and consider it all. Do a Google search for Evil AI and you get about 25,400,000 results. Do the same for Good AI and you get about 169,000,000 results. It is time to end the discussion of whether AI is good or evil and take action to create good. Every business and enterprise can do this.

Make no mistake: We're still probably at least a decade away from any kind of meaningful shift away from the smartphone. Assuming we're still eating at all, I guess.) Yet, piece by piece, the groundwork for the eventual demise of the smartphone is being laid by Elon Musk, Microsoft, Facebook, Amazon, and a countless number of startups that still have a part to play. And, let me tell you: If and when the smartphone does die, that's when things are going to get really weird for everybody. Not just in terms of individual products but in terms of how we actually live our everyday lives and maybe our humanity itself. Here's a brief look at the slow, ceaseless march toward the death of the smartphone -- and what the post-smartphone world is shaping up to look like.