Tonight during Valve's yearly Dota 2 tournament, a surprise segment introduced what could be the best new player in the world -- a bot from Elon Musk-backed startup OpenAI. Engineers from the nonprofit say the bot learned enough to beat Dota 2 pros in just two weeks of real-time learning, though in that training period they say it amassed "lifetimes" of experience, likely using a neural network judging by the company's prior efforts. Musk is hailing the achievement as the first time artificial intelligence has been able to beat pros in competitive e-sports. While the demonstration was highly limited to a few variables of gameplay, it was still remarkable to witness crowd-favorite Dota 2 pro Danylo "Dendi" Ishutin get crushed in a live 1-vs-1 match with the bot. Some of the bot's maneuvers looked eerily human.

There exist two main approaches to automatically extract affective orientation: lexicon-based and corpus-based. In this work, we argue that these two methods are compatible and show that combining them can improve the accuracy of emotion classifiers. In particular, we introduce a novel variant of the Label Propagation algorithm that is tailored to distributed word representations, we apply batch gradient descent to accelerate the optimization of label propagation and to make the optimization feasible for large graphs, and we propose a reproducible method for emotion lexicon expansion. We conclude that label propagation can expand an emotion lexicon in a meaningful way and that the expanded emotion lexicon can be leveraged to improve the accuracy of an emotion classifier.

If you ask ten data scientists, "Which machine learning tool is best?" you'll likely get many different answers. But slightly more surprising is that if you ask any one data of those data scientists the same question, you'll likely still get many different answers. The reason turns out to be one of a couple of surprising things about the current state of machine learning that I discovered while delving into the question of what's the best tool for machine learning (or deep learning). Here's a quick preview of two key observations about what makes machine learning successful: Instead they usually keep three to five machine learning options in their tool box. Let's start with the first observation.

Until the last 5 years or so, it was infeasible to uncover topics and emotions across the web without powerful computing resources. Engineers didn't have efficient methods to make sense of words and documents at a large scale. Now, with deep learning, we can convert unstructured text to computable formats, effectively incorporating semantic knowledge for training machine learning models. Harnessing the vast data troves of the digital world can help us understand people more directly, going beyond the limitations of collecting data points through measurements and survey results. Here's a glimpse into how we achieve this at MarianaIQ.

Artificial intelligence took a step forward last night, at an annual tournament for players of the tactical wargame Defense of the Ancients 2. A bot created by the Elon Musk-backed nonprofit OpenAI defeated champion human player Danylo "Dendi" Ishutin in two back to back demonstration matches. Musk hailed the achievement on Twitter, saying that it was a significant advance over what AI had accomplished in more traditional games. OpenAI first ever to defeat world's best players in competitive eSports. Vastly more complex than traditional board games like chess & Go. Defense of the Ancients 2 – commonly referred to as DOTA 2 – is what's known as a multiplayer online battle arena, or MOBA.

The result is an AI that not only has the fundamentals nailed down, but understands the nuances that take human players a long time to master. It's adept at tricks like zoning (preventing the enemy from hitting your creeps to deny them experience and gold) and raze faking (starting a raze animation to trick an enemy into dodging a non-existent attack). While its actions per minute aren't any better than that of an average flesh-and-bone player, the choices make a huge difference. And it doesn't take too long to learn, either; OpenAI's creation can beat regular Dota 2 bots after an hour of learning, and beat the best humans after just two weeks. Of course, these victories came about under controlled, ideal conditions.

Lots of people will tell you they're nervous about the changes artificial intelligence will bring to the world, but Andrew Ng is confident it's all for the best. The former AI chief of Baidu and founder of Google Brain is on a mission to build what he calls an "AI-powered society" -- one where smart computers are as integral to businesses as electricity. And to bring about that future, Ng, now an adjunct professor at Stanford, will share what he knows best by teaching. Today, Ng is launching a new course on deep learning on Coursera, the online education site he co-founded. The syllabus will follow his popular machine learning course, which has attracted some 2 million enrollments since its launch in 2011.

The billionaire says his artificial intelligence research startup OpenAI has developed the first bot to beat a professional esports gamer. Musk used the news to send out a warning about AI safety, saying the industry should be regulated and is more of a threat than North Korea.

"If you're not concerned about AI safety, you should be. Vastly more risk than North Korea," Musk tweeted after his $1 billion startup, OpenAI, made a surprise appearance at a $24 million video game tournament Friday night, beating the world's best players in the video game, "Dota 2." Musk claimed OpenAI's bot was the first to beat the world's best players in competitive eSports, but quickly warned that increasingly powerful artificial intelligence like OpenAI's bot -- which learned by playing a "thousand lifetimes" of matches against itself -- would eventually need to be reined in for our own safety. "Nobody likes being regulated, but everything (cars, planes, food, drugs, etc) that's a danger to the public is regulated. AI should be too," Musk said in another tweet on Friday night. Musk has previously expressed a healthy mistrust of artificial intelligence.

Saw this story after it was tweeted by Puni Rajah – Bosch to invest 300m euros in AI, employ 100 experts from India, USA, Germany. As ever India has done great job building its native skills base. But the fact Bosch needs to look outside Germany is telling. We're seeing a lot of pressure owing to skills shortages, and companies, countries and cities everywhere are going to need to up their game to avoid brain drain. Silicon Valley is still the main place data scientists, in particular machine learning and AI specialists, are ending up. Pierre Etienne Bardin of Société Générale expressed the need to be more active in hiring and training succinctly in a recent post on data transformation as the new digital transformation.