Update 06:11AM ET: Whatever the problem was Microsoft has dealt with it. Tay's account is now locked and all its tweets from this morning have been deleted. It's not clear exactly what happened, but it's been suggested that the account may have been hacked. We've reached out to Microsoft for more detail, and will update the story when we know more. Microsoft AI chatbot is tweeting again after being taken offline following a bout of sudden racism last week.

If you had the opportunity to vote for a politician you totally trusted, who you were sure had no hidden agendas and who would truly represent the electorate's views, you would, right? What if that politician was a robot? Futures like this have been the stuff of science fiction for decades. And, if so, should we pursue this? Recent opinion polls show that trust in politicians has declined rapidly in Western societies and voters increasingly use elections to cast a protest vote.

In recent years, we've been flooded with articles and blogs on big data and how it can be used to derive amazing new insights into almost every facet of a business operation. The deluge now has expanded to include artificial intelligence (AI). Although these two hot topics have received overwhelming attention, the interesting – even obvious – connection between the two hasn't often been explored. It is this combination of big data and AI working together that is now enabling business leaders to deliver new insights, efficiencies and even new functions that haven't been possible before. This is evident in the increasingly useful role big data and AI are playing in a broad spectrum of traditionally outsourced functions such as recruitment, HR, finance and supply chain, through to security and IT.

Microsoft's attempt to converse with millennials using an artificial intelligence bot plugged into Twitter made a short-lived return on Wednesday, before bowing out again in some sort of meltdown. The learning experiment, which got a crash-course in racism, Holocaust denial and sexism courtesy of Twitter users, was switched back on overnight and appeared to be operating in a more sensible fashion. Microsoft had previously gone through the bot's tweets and removed the most offensive and vowed only to bring the experiment back online if the company's engineers could "better anticipate malicious intent that conflicts with our principles and values". Microsoft's sexist racist Twitter bot @TayandYou is BACK in fine form pic.twitter.com/nbc69x3LEd Tay then started to tweet out of control, spamming its more than 210,000 followers with the same tweet, saying: "You are too fast, please take a rest …" over and over.

Records of global temperatures over the last few decades figure prominently in the debate over the climate effects of CO2 emitted by burning fossil fuels, as I discussed in my first post in this series, on What can global temperature data tell us? One recent controversy has been whether or not there has been a pause' (also referred to as a hiatus') in global warming over the last 15 to 20 years, or at least a slowdown' in the rate of warming, a question that I considered in my second post, on Has there been a pause' in global warming? As I discussed in that post, the significance of a pause in warming since around 2000, after a period of warming from about 1970 to 2000, would be to show that whatever the warming effect of CO2, other factors influencing temperatures can be large enough to counteract its effect, and hence, conversely, that such factors could also be capable of enhancing a warming trend (eg, from 1970 to 2000), perhaps giving a misleading impression that the effect of CO2 is larger than it actually is. To phrase this more technically, a pause, or substantial slowdown, in global warming would be evidence that there is a substantial degree of positive autocorrelation in global temperatures, which has the effect of rendering conclusions from apparent temperature trends more uncertain. Whether you see a pause in global temperatures may depend on which series of temperature measurements you look at, and there is controversy about which temperature series is most reliable. In my previous post, I concluded that even when looking at the satellite temperature data, for which a pause seems most visually evident, one can't conclude definitely that the trend in yearly average temperature actually slowed (ignoring short-term variation) in 2001 through 2014 compared to the period 1979 to 2000, though there is also no definite indication that the trend has not been zero in recent years. Of course, I'm not the only one to have looked at the evidence for a pause.

On a wet and windy day in October 2014, Team Seldon was sitting on Brighton Beach, discussing the bigger picture of what we could achieve. We had come a long way over the previous three years; every month we were serving content recommendations to over a hundreds million people. However, we believed that if we continued to ship a black box solution we would increasingly face obstacles to user adoption by enterprises. Machine learning technology was becoming increasingly commoditized, and new applications were, and continue to be, both widely developed and adopted. Through the mist that had settled over Brighton Beach the bigger picture of what we could achieve became clear -- democratising machine learning.

Google's move to give away its latest machine-learning software, key to its speech- and photo-recognition programs, isn't as crazy as it may appear. The unit of Alphabet said Monday it is releasing its TensorFlow system for free under an open-source license. That's one of the company's crown jewels, a machine-learning program that teaches computers to be smarter. But Google retains much of what makes its machine-learning effort special: massive piles of data, a powerful network of computers to run the software and a big team of artificial-intelligence experts to tweak the algorithms. "It's not a suicidal idea to release this," said Nello Cristianini, a professor of artificial intelligence at the U.K.'s University of Bristol.

Entrepreneur's inspiration lies in a business idea! If you've been planning to build a product, I'd suggest you to check these startups first. May be, you can find a new angle to your product and make it more powerful using machine learning & predictive analytics. These startups got featured at Y Combinator Winter 2016. Y Combinator is a startup accelarator which invests 120k in startups twice a year.

Britain is on the brink of a robotics revolution. Advances in technology are unleashing a new age where computers handle many tasks previously carried out by humans. From automated manufacturing to software that does complex legal work, business is adapting to the robot economy. Some worry that this will lead to a jobs apocalypse as "thinking machines" replace workers. Others are optimistic that robots will free workers from mundane tasks and allow them to concentrate on higher-level creative and strategic work.

The importance of Google owned DeepMind's AI victory over the world's best Go player is difficult to fathom. People expect computers to be smarter than human beings, however, Go is one game that was expected to be beyond what AI is capable of right now. The reason for this is that GO is a deceptively simple game with very few rules. All the pieces on the board have the same value, unlike chess where having more'valuable' pieces means that you will win more often than not. Players themselves describe the game as being based on intuition and'feel' rather than any set rules.