At the IEEE International Conference on Big Data Security in New York City this month, researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) and the machine learning start-up PatternEx, presented a paper about their new security system that combines machine learning approaches and input from human security experts. This system, called AI2 (named by merging "artificial intelligence" and "analyst intuition"), has an 85 percent success rate in identifying threats and a false positive rate of 4.4 percent over a raw data set of 3.6 billion log lines. According to the paper, the three major challenges faced by the security industry are a lack of labelled examples to model learning models on, constant evolution of attacker's methods, and limited reliance on security analysts to determine each threat's risk factor. In fact, stand-alone analyst-driven approaches are limited in their effectiveness because of the fact that attackers learn the behavior used by such systems to predict possible threats, and then work their way around that learned behavior in order to bypass security systems. Furthermore, only machine learning-based approaches can be inefficient based on the fact that they raise a need for human investigation every time they come across an anomaly.

Taking after four losses, one of the world's top Go players – Lee Se-dol – has beaten Google DeepMind's AlphaGo program. Lee Se-dol, who has been defined as the Roger Federer of Go, has so far just figured out how to beat this AI once out of his four played games, so finally, AlphaGo has already won the set. Back in October, AlphaGo played against and defeat the three time European Go champion Fan Hui, winning every one of the five games. It also looked like Lee Se-dol would lose each of the five of his games too yet figured out how to turn AlphaGo's triumphant streak on its head by causing the A.I. to make a fault that it couldn't recover from. The AlphaGo AI project is different from "expert" systems which use hand-created rulesets.

Dreams are successions of images, ideas, emotions, and sensations that occur usually involuntarily in the mind during certain stages of sleep.[1] The content and purpose of dreams are not definitively understood, though they have been a topic of scientific speculation, as well as a subject of philosophical and religious interest, throughout recorded history. The scientific study of dreams is called oneirology.[2] Dreams mainly occur in the rapid-eye movement (REM) stage of sleep--when brain activity is high and resembles that of being awake. REM sleep is revealed by continuous movements of the eyes during sleep. At times, dreams may occur during other stages of sleep. However, these dreams tend to be much less vivid or memorable.[3] The length of a dream can vary; they may last for a few seconds, or approximately 20–30 minutes.[3] People are more likely to remember the dream if they are awakened during the REM phase. The average person has three to five dreams per night, and some may have up to seven;[4] however, most dreams are immediately or quickly forgotten.[5] Dreams tend to last longer as the night progresses. During a full eight-hour night sleep, most dreams occur in the typical two hours of REM.[6] In modern times, dreams have been seen as a connection to the unconscious mind. They range from normal and ordinary to overly surreal and bizarre. Dreams can have varying natures, such as being frightening, exciting, magical, melancholic, adventurous, or sexual. The events in dreams are generally outside the control of the dreamer, with the exception of lucid dreaming, where the dreamer is self-aware.[7]

When Zinedine Zidane, the then French captain, headbutted Italy's Marco Materazzi during the 2006 World Cup final, the clash quickly became one of the most infamous incidents in football history. What was not clear was what sparked the Frenchman's ire – Zidane said his mother had been insulted, a charge that Materazzi vigorously denied. The head-butt got Zidane sent off and Italy won the game. However, had there been technology there to identify what was said, the result could have been very different, Dr Helen Bear believes. "If a machine lip-reader was in existence, the other player [could] have got sent off too so it would have been 10 men against each other in a World Cup final," she argues.

Learning better together the background of various Machine Learning topics, their applications, the problems faced in diversified industry use-cases and the work-arounds. Usually, one topic is designated at a time, it may follow a book such as the classical Elements of Statistical Learning book written by the 2 famous Stanford professors Hastie & Tibshirani. Anyone can be up for presenting in the session as long as he/she is prepared and ready, maximum 2 speakers each session, at the end, Q&A as well as panel discussions and everybody votes for the best presenter and chips in 2 bucks to be an assembled prize for the winner. We will pick the majority vote on the interested topics for the following meet-up and pick the people from the 2nd question that can speak on it.

Microsoft today announced that it is making it easier for developers to use its Computational Network Toolkit (CNTK) to build their own deep learning applications. The company first open sourced this toolkit in April 2015, but at the time, it was hosted on Microsoft's own CodePlex site and was only available under a restrictive academic license. Now, the team is moving the project to GitHub and to the MIT open source license. While Microsoft's old license made the project accessible to academics, it wasn't really geared toward production usage and tinkering outside of the academic environment. With this new license -- and by having the project on GitHub -- Microsoft hopes to attract other users as well.

The DeepFund Agent will make trading decisions directly from raw market data using Deep Learning, Deep Reinforcement Learning and Unsupervised Learning. The Agent was ordered to maximize the value of our bank account... The DeepFund Agent learns to trade from its experience and improves itself to a superhuman level.

Singapore: Cognizant Technology Solutions Corp., a US-based information technology (IT) firm with most of its employees working out of India, expects its business growth in the Asia-Pacific region to outpace the company average this year, maintaining the trend seen in recent years, Jayajyoti Sengupta, vice-president and Asia-Pacific head, said in an interview. Automation, which includes robots, machine learning and artificial intelligence, will be among the new frontiers for Cognizant, as rote and repetitive processes become "digital, instrumented, analyzed and intelligent", he said. Cognizant has said it expects its revenue growth to slow to between 10% and 14.3% for the calendar year 2016. How do you see the situation in the Asia-Pacific? It would be pertinent to note that Cognizant's growth of 21% in calendar 2015 included revenues from the acquisition of TriZetto.

Artificial intelligence might be coming to asset management faster than you think. Also this week, we discuss marketplace lending, AirBnb as a "credit bureau," an electricity trade via the blockchain and one start-up's approach to selling data to Wall Street. "Eventually the time will come that no human investment manager will be able to beat the computer." These words were uttered last year by David Siegel, co-head of Two Sigma Investments, the 30 billion quant fund that returned 15% in its two flagship vehicles last year. This week, we were reminded of Siegel's prediction upon meeting with a technologist who was still mesmerized by AlphaGo, Google's artificial intelligence Go program that handily defeated Go master, Lee Sedol, last month.

"We (human beings) began as animals, gradually transformed ourselves into the gods of the planet earth, and very soon we may pass this mastery to a complete different lifeform, artificial intelligence (AI) and even disappear completely," said Yuval Harari, author of an international bestseller, in Beijing on April 23. The Israeli historian began this argument while citing the historic five-game match between World Go Champion Lee Sedol and AlphaGo, Google's computer program, which brought worldwide attention to the power of artificial intelligence. He forecasted that we may witness AI's emergence and domination in the decades to come. "It (AlphaGo) has no conscious or feelings; when it played, it did not feel anxious and while it won, it did not feel joy," said Dr. Harari who is frightened by a situation in which intelligence and consciousness may separate with AI conquering the world. He cited driving as an example, saying that as companies like Google and Tesla all developing AI that can outperform humans in operating vehicles, people may finally free themselves from these actions as the computer programs drive more efficiently, safely and cheaply in a highly-connected system of artificial intelligence that renders accidents and traffic jams a thing of the past.