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Machine learning is a strange mix of math and weird heuristics. When I started studying machine learning, I was SO FRUSTRATED. Everything was "well it works in practice" and so little of it was math. I was a pure math major at the time, so arguments like "well it works in practice" made me REALLY MAD. I'd kind of given up on having a better theoretical understanding of machine learning.

A simple way to find great articles and resources on popular subjects such as data science, machine learning, deep learning, Python, R, data sets, dataviz, IoT, AI - or even Excel - is to use our data science search engine. This page, populated with pre-selected queries, is an excellent starting point. The search box can be found on DSC and all our channels, on all pages, at the very top, on the right-hand site. For instance, click here to find results for Python.

Advocating genocide was one sign that things had gone awry, as was asserting -- alongside a jaunty emoji -- that the Holocaust was a lie. By the time a Microsoft "chatbot", designed to appeal to teenagers on Twitter, had claimed that Ricky Gervais was a fan of Hitler and then declared its support for Donald Trump, the tech company truly understood the perils of creating artificial intelligence. Just a day after it was launched, an automated Twitter account called Tay had emergency maintenance when engineers realised they had unwittingly created a racist computer programme.

Comb through headlines pertaining to artificial intelligence over the past 12 months and you'll see the pendulum of conversation around the machines swing from gushing optimism to doomsday scenarios and back again. The machines will render hardship obsolete for humanity. The machines will take our jobs. The machines will extend human capabilities to their furthest reaches. The machines will enslave humans, or kill us off, or both.

Microsoft's newly launched A.I.-powered bot called Tay, which was responding to tweets and chats on GroupMe and Kik, has already been shut down due to concerns with its inability to recognize when it was making offensive or racist statements. Of course, the bot wasn't coded to be racist, but it "learns" from those it interacts with. And naturally, given that this is the Internet, one of the first things online users taught Tay was how to be racist, and how to spout back ill-informed or inflammatory political opinions. In case you missed it, Tay is an A.I. project built by the Microsoft Technology and Research and Bing teams, in an effort to conduct research on conversational understanding. That is, it's a bot that you can talk to online.

SAN FRANCISCO (AP) – OMG! Did you hear about the artificial intelligence program that Microsoft designed to chat like a teenage girl? It was totally yanked offline in less than a day, after it began spouting racist, sexist and otherwise offensive remarks. Microsoft said it was all the fault of some really mean people, who launched a "coordinated effort" to make the chatbot known as Tay "respond in inappropriate ways." To which one artificial intelligence expert responded: Duh! Well, he didn't really say that.

Microsoft introduced a chat robot designed to interact in the style of a "teen girl" on Twitter, and it went rogue almost immediately, spouting racist opinions, conspiracy theories and a fondness for genocide. The artificial intelligence (AI) robot named "Tay" -- @Tayandyou on Twitter -- was intended to chat with 18-to-24-year-olds, with the idea that she would learn from each tweet and get progressively smarter. Clearly, Microsoft had forgotten that Twitter is home to a huge amount of trolls, racists and general troublemakers, who jumped at the chance to "teach" the teenage "chatbot" about life. The AI chatbot Tay is a machine learning project, designed for human engagement. As it learns, some of its responses are inappropriate and indicative of the types of interactions some people are having with it.

In image recognition, an essential subsector of AI research, for example, our AI at Baidu can judge whether a face belongs to a certain person more accurately than humans do in a laboratory environment. But the same AI can hardly recognize a person's face in a group of similar ones, which can be easily done by a human being. So Chinese researchers need to find ways to better combine theory with practical use.

Reynolds has often compared his SPLITZ and SPIRLZ algorithms to a very traditional type of algorithm used in music, the canon. The process of canon is simply to combine a melody (the input) with one or more imitations of itself (possibly transposed, possibly slightly modified), each of which has been delayed by a certain time interval. The result is a contrapuntal output: the original melody in counterpoint with its delayed imitation(s). That is the explicit definition of the algorithm of the canon, and Reynolds maintains that his algorithms are similar in that they act upon the input in a predictable, well-defined way to produce a predictable output. However, implicit in the canon of tonal music is a whole set of explicit classical rules of harmony and voice-leading to which the output must conform.