If you're as plugged in as we are, then you probably have something like 150 online accounts. That means you probably have 150 variations of the same half-dozen login names and passwords. And chances are, you've gotten a message from a friend in the last few months telling you that it looks like you got hacked again, after he received email spam to enlarge an embarrassingly small body part. Well, we think the days of the alphanumeric password are numbered. The age of biometric authentication is dawning.

Facebook is trialling a "dislike" button for the first time, in response to high demand from users. The feature has been rolled out to a small number of people on the Messenger app, who now have the option to respond to individual messages. Facebook wants users to attach emojis to messages in a similar way to the "reactions" feature on the news feed. The social media giant had previously ignored calls for the "dislike" button due to fears the feature might be used as a form of bullying and would be unpopular with big brands. Facebook is however adamant this is more of a "no" button and it is being tested to see if the reaction is helpful for when group conversations need to vote, for instance.

Last week, I compiled a list of the 5 jobs robots will take first. Today, let's have a go at the 5 jobs robots will take last. For this article only, let's define "robots" as technologies, such as machine learning algorithms running on purpose-built computer platforms, that have been trained to perform tasks that currently require humans to perform. For example, an assembly line worker performs mostly manual repetitive tasks which, depending on complexity and a cost/benefit analysis, can be automated. A CEO of a major multinational conglomerate performs mostly cognitive nonrepetitive tasks which are much harder to automate.

Oxford University researchers have estimated that 47 percent of U.S. jobs could be automated within the next two decades. But which white-collar jobs will robots take first? First, we should define "robots" (for this article only) as technologies, such as machine learning algorithms running on purpose-built computer platforms, that have been trained to perform tasks that currently require humans to perform. With this in mind, let's think about what you'll do after white-collar work. Oh, and I do have a solution for the short term that will make you the last to lose your job to a robot, but I'm saving it for the end of the article.

IBM has taken its first step towards selling computers that are millions of times faster than the one you're reading this on. The company has set up a new division, IBM Q, that is intended to make quantum computers and sell them commercially. Until now, quantum computers have mostly been a much hyped but long away dream. But IBM believes they are close enough to reality to start work on getting software ready for when they become commercially available. The giant human-like robot bears a striking resemblance to the military robots starring in the movie'Avatar' and is claimed as a world first by its creators from a South Korean robotic company Waseda University's saxophonist robot WAS-5, developed by professor Atsuo Takanishi and Kaptain Rock playing one string light saber guitar perform jam session A man looks at an exhibit entitled'Mimus' a giant industrial robot which has been reprogrammed to interact with humans during a photocall at the new Design Museum in South Kensington, London Electrification Guru Dr. Wolfgang Ziebart talks about the electric Jaguar I-PACE concept SUV before it was unveiled before the Los Angeles Auto Show in Los Angeles, California, U.S The Jaguar I-PACE Concept car is the start of a new era for Jaguar.

I mean, you really suck. That's what I wanted to write, but a new feature in the Office 365 version of Word called Editor made an interesting suggestion. The "machine" noted how the word "really" is superfluous, and it's true. The extra word doesn't add anything to the sentence, so I removed it. I've been writing professionally since 2001 (around 10,000 published articles now), but I'm still learning, I guess.

Developers from Orange Labs in France developed a deep learning system that can quickly make young faces look older, and older faces look younger. A number of techniques already exist, but they are expensive and time consuming. Using CUDA, Tesla K40 GPUs and cuDNN for the deep learning work, they trained their neural network on 5,000 faces from each age group (0-18, 19- 29, 30-39, 40-49, 50-59, and 60 years old) taken from the Internet Movie Database and from Wikipedia and then labeled with the person's age -- this helped the system learn the characteristic signature of faces in each age group. A second neural network, called the face discriminator, looks at the synthetically aged face to see whether the original identity can still be picked out. If it can't, the image is rejected, which they call the process in their paper, Age Conditional Generative Adversarial Network.

Robots are taking over retail, well not quite. There has been much talk about robots taking on human roles within retail. Whilst this seems like an incredible innovation and still very futuristic, IBM Watson, the supercomputing power behind Pepper, the high profile robot with linguistic talents is one of several technologies such as advanced voice-recognition, data analytics, cognitive systems and automation that are going to transform our experience of shopping. What can be a painful drag, will, thanks to these advances, become more convenient and satisfying, whichever way we shop. Get right to the point When you go online to shop for a new coat the power of machine learning and artificial intelligence means you won't immediately be confronted by a bewildering range that takes hours to trawl through and ends up making you unhappy with your indecisiveness.

Is creativity in the marketing industry on a slow death march? Go to any marketing conference or seminar these days and you are likely to hear someone lament declining creative standards and the loss of'brand magic'. Financial pressures have put a squeeze on marketers' ability to unleash their creative instincts, but of greater concern is the role of technology and automation. The growing influence of programmatic media buying, machine learning and artificial intelligence (AI) have changed the way marketers perform their jobs, potentially putting creativity and independent thought at risk. HSBC's former head of marketing in EMEA Philip Mehl hit on this point in a recent Marketing Week roundtable when he declared: "Marketing used to be a creative challenge but it's a data challenge now."

Machine Intelligence (AI, ML and Deep Learning) requires a certain calibre of computer science talent. Today, this kind of talent is at the "top of the stack" of computer science. These cutting-edge capabilities used to be found at universities, and work on publicly-funded blue sky research; today, companies have the talent, and use it for private, applied purposes. The Economist touched on this in "Million Dollar Babies": That race for talent, is catalysing acquisitions by corporates interested in adding AI to their products and services. As an example, Ex-Googler Sebastian Thurn estimated that the going rate for self-driving engineering talent is $10 million per person.