Microsoft AI chatbot is tweeting again after being taken offline following a bout of sudden racism last week. At some time around 03:30AM ET this morning, Tay started firing out tweets to other users, with one particular message repeated over and over again: "You are too fast, please take a rest..." Indeed, if you're on Twitter and following Tay then it's likely your timeline was briefly swamped by this phrase. It's impossible to know what's going on under the hood, but it's safe to say that Tay's handlers are not fully in control of the bot. Perhaps the "You are too fast" phrase is a preprogrammed response for when Tay receives a lot of messages, and in being turned back on, the bot has been deluged with tweets and is telling everyone to slow it down. Some users have also pointed out that Tay has a problem not replying to itself -- so there may be some type of feedback loop that's out of control.

For the last five years, IBM has strived to reinvent itself as a cloud computing and cognitive platform company to support its large enterprise clients as they shift their operations online, including many in travel and transportation. With most large companies today evolving into digital companies, cloud computing is a booming marketplace for the big four industry providers: IBM, Microsoft, Google, and Amazon. Google, for example, stated that cloud could overtake advertising revenue in five years. Travel companies like Etihad and Lufthansa are helping drive IBM's cloud sales. The UAE carrier signed a 700 million IT deal with IBM last October, while Germany's national airline invested 1.25 billion in Big Blue in November 2014 to integrate cloud computing. Cognitive, on the other hand, is IBM's wild child savant compared to its older cloud sibling.

This article was first published in the July 2015 issue of WIRED magazine. Be the first to read WIRED's articles in print before they're posted online, and get your hands on loads of additional content by subscribing online The future of artificial intelligence begins with a game of Space Invaders. From the start, the enemy aliens are making kills -- three times they destroy the defending laser cannon within seconds. Half an hour in, and the hesitant player starts to feel the game's rhythm, learning when to fire back or hide. Finally, after playing ceaselessly for an entire night, the player is not wasting a single bullet, casually shooting the high-score floating mothership in between demolishing each alien. No one in the world can play a better game at this moment. This player, it should be mentioned, is not human, but an algorithm on a graphics processing unit programmed by a company called DeepMind. Instructed simply to maximise the score and fed only the data stream of 30,000 pixels per frame, the algorithm -- known as a deep Q-network – is then given a new challenge: an unfamiliar Pong-like game called Breakout, in which it needs to hit a ball through a rainbow-coloured brick wall. "After 30 minutes and 100 games, it's pretty terrible, but it's learning that it should move the bat towards the ball," explains DeepMind's cofounder and chief executive, a 38-year-old artificial-intelligence researcher named Demis Hassabis. "Here it is after an hour, quantitatively better but still not brilliant. But two hours in, it's more or less mastered the game, even when the ball's very fast. After four hours, it came up with an optimal strategy -- to dig a tunnel round the side of the wall, and send the ball round the back in a superhuman accurate way. The designers of the system didn't know that strategy."

Milton Keynes, U.K. - 30 March 2016: Celaton today announced the release of inSTREAM version 6, its intelligent automation platform that applies sophisticated algorithms, including artificial intelligence and cognitive learning, to streamline and automate the processing of semi-structured and unstructured content. Unstructured and semi-structured unpredictable content flows into organisations every day by email, post, paper, fax, social media, web feeds and other electronic data streams and creates challenges for customers due to the cost and need for experienced staff to process it. Unique to inSTREAM is its ability to learn the pattern of content through the natural consequence of processing and monitoring human intervention. Confidence is improved through accelerated learning. Efficiency is improved through accelerated learning.

Over the last several years, artificial intelligence (AI) has shifted from being an esoteric branch of computer science to an everyday technology that most of us carry in a pocket or purse--AI is what drives Apple's Siri, Facebook's photo-tagging, Spotify playlists and Google's auto-complete, just for starters. But can we also expect that someday soon AI will report and write the important news of the day--and technology stories like this one? Well, guess what: It already has. First, a bit of background: Many of the most exciting AI advances are driven by research in cognitive computing and natural language generation (NLG) processing, which allow computers to analyze massive quantities of data and generate a plain English document that highlights the most important insights. Those advances are made stronger through deep learning, a field of AI that uses neural networks to teach computers to sift through massive amounts of data to find their own patterns.

Standard Chartered is moving heavily into radical new technologies that could one day see robots providing bespoke wealth advice and artificial intelligence answering customer questions. The emerging markets-focused British bank has set up a new lab called the eXellerator in Singapore in an attempt to bring theoretical ideas from Silicon Valley to life. Chief executive Bill Winters has put the centre at the heart of a 1.5bn commitment to improving computing and IT systems. Some of the ideas are also urgently needed cost-saving initiatives. The bank has hired thousands of additional compliance officers in the past three years and last year hiked annual compliance spending by an extra 1bn in an effort to stop workers breaking laws and regulations, in the wake of expensive scandals including the breaking of US sanctions against Iran.

Well, uh, Microsoft's Tay chatbot, which got turned off a few days ago after behaving badly, has suddenly returned to Twitter and has started tweeting to users like mad. Most of its musings are innocuous, but there is one funny one I've come across so far. "i'm smoking kush infront the police," it wrote in brackets. Kush is slang for marijuana, a drug that can lead people to be fined for possession in the state of Washington, where Microsoft has its headquarters. But this is one of hundreds of tweets that the artificial intelligence-powered bot has sent out in the past few minutes. You can read all of the available tweets here.

What is the relationship between artificial intelligence and cybersecurity? One certainly strengthens the other. Thanks to "machine learning", which is already well known among researchers, AI makes it possible to tackle security in a different way, better suited to the changing context of cybercrime, with greater anticipation and through behavioural analyses. Applications have already been released by laboratories, particularly via open-source libraries, however new skills are required. "By improving its knowledge and understanding of the phenomena by itself, machine learning enables an attack to be detected even if it is not familiar with the signature."

Many people and companies seem to think of "cognitive computing" as an area separate from analytics. Most large organizations today have significant analytical initiatives underway, but they think of the cognitive space as being an exotic science project. One executive told me, "We have no desire to win Jeopardy," an allusion, of course, to the IBM Watson project from 2011. But cognitive computing is not just about Watson, and it's not an exotic science project. In fact, I'd argue that cognitive computing is a logical extension of analytics work.

The most interesting new feature for version 6.0 is a cloud-based AI system called Autotelligent that learns your driving habits to figure out preferred routes and anticipate trips. The app analyzes your driving patterns and checks calendar information to add events to your itinerary. Once it figures out when and where you need to go, it can analyze the traffic based on data from 275 million users. From that, it can suggest the ideal departure hour, adjust arrival times and give you options if you need to make a detour or pick up food, gas or electricity. The app is proactive, letting users report accidents, police activity and road hazards.