Successful Cloud Operations Means Knowing When to Say "No!" Building a cross-cloud operational model can be a daunting task. Per-cloud silos are not the answer, but neither is a fully generic abstraction plane that strips out capabilities unique to a particular provider. In his session at 20th Cloud Expo, Chris Wolf, VP & Chief Technology Officer, Global Field & Industry at VMware, will discuss how successful organizations approach cloud operations and management, with insights into where operations should be centralized and when it's best to decentralize. Speaker Bio Chris Wolf serves as CTO, Global Field and Industry at VMware. In that role, he is responsible for driving the execution and communication of the Office of the CTO's vision, internally and externally, supporting VMware's global field teams on all CTO evangelism and representing VMware's technical vision to customers, partners and analysts.

News headlines might not be the only things that are fake in the future. Powerful machine-learning techniques (see "The Dark Secret at the Heart of AI") are making it increasingly easy to manipulate or generate realistic video and audio, and to impersonate anyone you want with amazing accuracy. A smartphone app called FaceApp, released recently by a company based in Russia, can automatically modify someone's face to add a smile, add or subtract years, or swap genders. The app can also apply "beautifying" effects that include smoothing out wrinkles and, more controversially, lightening the skin. And last week a company called Lyrebird, which was spun out of the University of Montreal, demonstrated technology that it says can be used to impersonate another person's voice.

Though further developments are underway, Google said on April 27 that it has successfully developed new deep learning algorithms that can detect and diagnose diabetic retinopathy, an eye disease which can lead to blindness, as well as locate breast cancer. Lily Peng, product manager of the medical imaging team at Google Research, shared how the US tech giant is using deep learning to train machines to analyze medical images and automatically detect pathological cues, be it swollen blood vessels in the eye or cancerous tumors, during a video conference with the South Korean media hosted by Google Korea. Based on the workings of the human brain, deep learning uses large artificial neural networks -- layers of interconnected nodes -- that rearrange themselves as new information comes in, allowing computers to self-learn without the need for human programming. "Artificial neural networks have been around since the 1960s. But now with more powerful computing power, we can build more layers into the system to handle more complicated tasks with high accuracy," Peng said. "In deep learning, the feature engineering is handled by the computer itself.

Good parties diverge widely; all bad parties are bad in the same way. I am trapped at a dull dinner following a dull talk: part of a series of dinners and talks that grad students organise, unpaid (though at considerable expense to themselves--experience! exposure!), to provide free content for the dull grad program I will soon leave. The Thai food is good. The man sitting across from me and a little down the way, a bellicose bore of vague continental origin, is execrable. He is somehow attached to a mild woman who is actually supposed to be here: a shy, seemingly blameless new grad student who perpetually smiles apologetically on his behalf, in an attempt to excuse whatever he's just said. One immediately understands that she spends half her life with that worry in her eyes, that Joker-set to her mouth, and that general air of begging your pardon for offences she hadn't even had the pleasure of committing. There is always such a woman at bad parties. She has always either found ...

Reporters called it the robot, but its physical presence was hardly felt. It was almost invisible, just a Microsoft Excel macro that could write a fairly detailed stock-market report that could then be edited and polished by a human journalist. But when Reuters introduced the robot to its newsroom in 2007 -- just before the financial crisis -- it was an early sign that manufacturing was not the only industry that automation was infiltrating. White-collar workers in fields like journalism, finance, medicine, and law are seeing an increasing use of machines, but one much less damaging to workers' job prospects. Unlike in manufacturing, where machines can take over entire factory floors in a physical, almost menacing way, machine learning and artificial intelligence so far are playing fairly benign roles in the professional world.

Dave Wakeling of the English Beat performs at the Tribeca Film Festival. Dave Wakeling of the English Beat performs at the Tribeca Film Festival. One of the great advantages of a gathering like the Tribeca Film Festival is the sheer variety of what's on offer -- not just the usual array of movie screenings, but television and technology programming, music performances, gaming sessions and plenty of talks with well-known personalities. From one vantage, of course, that can seem like chaos. And granted, the fest's many niches can make for an overwhelming, at times muddying affair.

I suppose I could sit here and fret over a day in the not-too-distant future when a robot powered by artificial intelligence(AI) will spit out newspaper columns like this one, rendering redundant columnists like me. After all, there have been reports that computers can already churn out news reports that read almost as well as those written by journalists, and in a fraction of the time taken. The thought of being replaced by software is depressing and, I might add, self-defeating. That is why I disagree with the way technological advances and the future of work are all too often framed in either-or terms: either robot or human worker, either AI or human brain. Here are a few recent examples of headlines in local media that fall into this category: "AI may replace a third of graduate jobs: Study", published on April 6; "Evidence that robots are winning the race for American jobs", published on March 30; and "Robots may take over 10 million jobs in Britain in 15 years", published on March 25. Such reports reflect how automation and AI are more often than not viewed - not just in Singapore but in other parts of the world too - as threats to jobs and human well-being.

MegaBots' giant robot duel might just turn into a full-scale brawl. Beijing outfit Greatmetal has unveiled a prototype of Monkey King, China's take on an enormous battle machine. It's still human-piloted, but it has a distinct trick up its sleeve: it can either fight on all fours (good for stability) or stand on its hind legs to wield a staff. While we wouldn't expect wuxia-style acrobatics out of this bot, it could throw a curveball into what was otherwise set to be a relatively straightforward fight. You might not have long to wait to see it in action, either. MegaBots is deciding whether or not Greatmetal can enter its giant fighting robot league, and might even pit its Mk.

Whether you are an owner of a thriving small business or a decision maker at an established enterprise, you cannot ignore digital technology. Businesses worldwide are going digital to deliver compelling experiences to customers, which is becoming a key differentiating factor. The rise of social and mobile have increased the discoverability of businesses. Consumers are turning to social media to find the right product and retailers based on recommendations and reviews from their friends. Before embracing social media, it is important for businesses to have a visible online presence.

American Mark Pavlyukovskyy created a company that provides materials people can use to build their own computer. Last year, when he was searching for people to invest in his company, he wanted someone who knew the Chinese market. Pavlyukovskyy did not have to travel to Beijing or Shanghai to find people knowledgeable about China. Silicon Valley in California is home to many Chinese with money to invest in small or start-up businesses. Pavlyukovskyy was born in Ukraine.