You don't need to be a chemist to make triacetone triperoxide, or TATP, the homemade explosive used in the bombs which killed 35 people and injured hundreds more last week in Brussels, according to one expert. Another calls the process "worryingly easy." The recipe can be found on the Internet, the ingredients -- hydrogen peroxide and acetone -- can be found at any drugstore, and can be mixed using regular kitchen equipment. "For the most part, IED components are commercial goods that are not subject to government export licences and whose transfer is far less scrutinised and regulated than the transfer of weapons," said a February report from the London-based Conflict Armament Research group, which traced the origins of more than 700 components recovered from ISIS bomb factories. In an attempt to head off attacks like those in Brussels, Boston, and scores of other places, the United States government has quietly asked the general public -- from credentialed professionals to "skilled hobbyists" -- to find ways of weaponizing "easily purchased, relatively benign technologies."

After taking a 2-0 lead in its five-game match with Lee Sedol on Thursday, Google-DeepMind's AlphaGo artificial intelligence program seems likely to claim victory within the next few days. This will no doubt resurface the many questions people have about AI's future and whether humans are inching towards Matrix-like enslavement. Fortunately, last night's "Don't Trust the Promise of Artificial Intelligence" Intelligence Squared U.S. debate in New York City addressed a lot of these questions and concerns. Lanier teamed with Internet entrepreneur Andrew Keen on the side of not trusting the promise of AI, emphasizing that the debate was about "the promise" as opposed to AI itself.

After taking a 2-0 lead in its five-game match with Lee Sedol on Thursday, Google-DeepMind's AlphaGo artificial intelligence program seems likely to claim victory within the next few days. This will no doubt resurface the many questions people have about AI's future and whether humans are inching towards Matrix-like enslavement. Fortunately, last night's "Don't Trust the Promise of Artificial Intelligence" Intelligence Squared U.S. debate in New York City addressed a lot of these questions and concerns. Arguments both for and against the motion were complex and nuanced but basically it was a debate over whether AI is being oversold at this time. "Go games are informing a Go algorithm," computer scientist Jaron Lanier noted in his opening statements in reference to Sedol's match against a computer.

In Seoul, South Korea, a Google-created artificial intelligence has been squaring off against a mortal man in the 2,500-year-old strategy game, called Go, that's several orders of magnitude more complicated than chess. When it was finally over, Google's AlphaGo won four out of five matchups, making AlphaGo a role model for young artificial intelligences everywhere. Wired reported that "AlphaGo relies on deep neural networks--networks of hardware and software that mimic the web of neurons in the human brain. With these neural nets, it can learn tasks by analyzing massive amounts of digital data." That's bad news for SEOs the world over, because Google isn't just using neural nets to beat Koreans at board games, it's also using these advanced networks to make their search results more efficient.

An enormous volume of software development is done overseas. The labor is cheaper and many countries have done a good job of training a large number of people to be competent developers. But history tells a story of machines and robots replacing people. This may be what is about to happen to overseas developers. And yes, once again it is robots that are taking their place.

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Visual effects rendering is a computationally intensive process where one second of screen-time can require thousands of cores and terabytes of frame data. Learn how Academy Award-winning and recognized studios take advantage of cloud economics and Google's on-demand computing to realize their creative visions and expand this digital medium for storytelling.

Artificial intelligence is on the rise in the world of machine translation. A string of recent news about tech giants bolstering machine translation engines with deep learning underscores just how central integrating deep learning into machine translation products has become for companies like Google and Microsoft. Slator reached out to a representative of Beijing-based Baidu, who is authorized to speak for the company, to get an exclusive look at what the Chinese tech leader has in store for its translation technology. Baidu began R&D on Baidu Translate in 2010, launching the product in June 2011. The company felt that translation was in line with what their search users needed.

Microsoft Build, the company's annual conference with software developers, gets underway Wednesday. Microsoft will be talking about its plans for the year, and encouraging developers to think up new applications for its products. Two of the most important things Microsoft is highlighting are artificial intelligence and machine learning. If you use Microsoft products, chances are you already experience machine learning, said spokesman Frank Shaw, who gave the example of Microsoft virtual assistant Cortana. "Cortana will say, currently, 'Hey, you sent email and promised a reply by tomorrow. One of the key elements of the Microsoft Build developer conference is thinking about how to incorporate that kind of intelligence throughout the Microsoft ecosystem. "Microsoft is very good, and they're getting better.

The Bank of Russia is using machine learning technology to identify unlicensed money lenders, and the websites hosting them. The technology, developed by Yandex Data Factory, has helped to reveal 2,500 suspicious organisations. The system uses algorithms to search out websites hosting illegal cash loan providers and unregulated financial activity by indexing web pages related to microfinance and consumer loans. Yandex uses keyword analysis across a search index of some seven million web pages related to finance topics. In order to help build the specialised search model, Bank of Russia experts sorted through and categorised 8,000 web pages.