MIT researchers have announced that they've concocted a new artificial intelligence system capable of successfully detecting 85% of cyber-attacks. The AI2 platform, produced by the MIT's Computer Science and Artificial Intelligence Laboratory (in conjunction with PatternEx, a machine learning startup), has notched up a much better record than previous systems. The 85% accuracy rating is three times better than previous benchmarks which have been recorded, and it also produced far less false positives, in fact a reduction of a factor of five was observed. MIT notes that AI2's initial testing ran over a period of three months and involved combing through some 3.6 billion log lines looking for suspicious activity, using machine learning to make the initial detections and then putting those in front of a human security analyst who confirmed whether or not a detection was an actual cyber-attack. AI2 then learned from that feedback, improving its routines for the next round of detection. Essentially, the system utilises the best in artificial intelligence smarts combined with human error correction which feeds the machine learning process, and AI2 is apparently capable of honing itself rapidly indeed.

Researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have collaborated alongside the machine learning startup PatternEx to demonstrate how an artificial intelligence platform that makes use of continuous input from human experts would be able to predict cyber attacks better than the systems that exist today. CSAIL and PatternEx are calling their new AI platform AI² due to how it combines the intuition of analysts with artificial intelligence. Previously'analyst-driven solutions' relied on the rules created by security experts which resulted in attacks that did not correspond to their rules slipping through the cracks. The machine learning approach to cyber-security relies on'anomaly detection' to discover possible attacks but often results in false positives. CSAIL and PatternEx created AI² by combining machine learning's ability to detect anomalies with the knowledge of analysts to flag possible threats.

An engineer recently asked me how she could turn an interest in machine learning into a full-time job. This can be a daunting prospect, because the whole field has until recently been very separate from traditional engineering, with only a few specialists at large companies using it in production, often far from traditional product teams. I took a very random path to focusing on deep learning full time, but so did most of the people I work with. It's not clear that there is one good route, but I wanted to share the advice I had to offer in case it's helpful to others. Every manager should point at one member of their team and say "You are now our machine learning expert".

In the busy weeks leading up to RSA this year, I was taking a rare break to drive my daughter to the airport. She was flying back to school to continue her 2nd year at University of Toronto (shout out to all of my Canadian peeps!). Btw, if you've not seen "Stronger Beer" highly recommended. Anyway, my daughter asked me an intriguing question on the ride to LAX. She said, "Last time I got caught in a random search… do you think the TSA finds anything doing that…" Great question, and my answer was "No" it's a horrible way to search people.

Have you ever joked that you wished you could clone yourself? Well, it looks like if you're an extremist of any stripe who spends a lot of time on social media, you'll soon be able to fulfill that dream. Swarms of real life, human trolls have already been able to achieve some remarkable things. For example, there's the well-known incident where Time's Man of the Year Poll met 4chan. But real-life trolls have to sleep.

Leave a human baby with some toys and it'll quickly learn to pick them up. Now a robot with deep-learning capabilities has done the same thing.

April 24 can't come soon enough for Game of Thrones fans eagerly awaiting the premiere of the hit show's sixth season. Naturally, most of us have been speculating wildly about the fate of our favorite characters for the past year, but now there's a clever app to help you withthat. The project, A Song of Ice and Data, was developed by a group of students of a JavaScript course at the Technical University of Munich. Some of the biggest names in tech are coming to TNW Conference in Amsterdam this May. It looks at 24 features of each character, the list of which includes attributes like their age, the House they belong to, whether they're married and how popular they are based on how many wiki pages link to them.

I don't know if you're in the market for a new car, of course, but chances are that soon, possibly the next time you buy a vehicle, it will have so much processing power and artificial intelligence that you won't won't be able to keep up. Because the smarter cars get, the safer we become. It's estimated that we could reduce traffic fatalities by 90% -- or 30,000 lives every year -- by 2050, once cars start driving themselves. To get there, tech companies are creating hardware and software that make semi-autonomous and fully autonomous cars a reality.NVIDIA andAlphabet's Google are two leaders in the car tech space -- and they're just getting started. Advanced hardware NVIDIA released two huge steps forward in automotive technology recently: its Drive PX 2 system and the DGX-1 supercomputer.

It's a good time to be Alphabet Inc. (GOOG), the parent company of Google. The holding company that owns Google, YouTube and Android -- as well as so-called moonshots like self-driving cars, the home-networking division Nest and Google Fiber -- is expected to turn in healthy first-quarter results on Thursday, driven by its dominant position in online search and display advertising. On Wednesday, the European Commission is expected to formally charge Google for favoring its own apps and services on its Android mobile operating system, which powers more than 80 percent of the world's smartphones. That will be the latest in a decade of entanglements with regulators on both sides of the Atlantic; Google also got some bad press in Britain earlier this year for having paid just 185 million in taxes over the past decade. Also confronting Google -- and the rest of the tech industry -- is how to manage government and law enforcement requests for information.