Mitsubishi Heavy Industries has cut the number of workers on its turbocharger production lines west of Tokyo by more than 80 percent, as manufacturers from carmakers to electronics producers push further into automation. Such advances explain why Japan's factory productivity growth ranked highest among Group of Seven nations over the two decades to 2014. Yet the nation's overall productivity ranks worst in the G-7, dragged down by a lack of progress in the services sector, where white-collar work culture demands long hours rather than efficiency. Higher productivity is critical to sustaining economic growth and living standards as Japan's population shrinks. One forecast predicts the current labor force of about 77 million could decline by more than 40 percent by 2065.

If a recent interaction between a human journalist and his Chinese robot counterpart is anything to go by, it'll be a while before a journalist job will be lost to (a robot in) China. On Monday (April 24), Jia Jia, a Chinese-manufactured robot under development for about three years (link in Chinese), had a conversation with AI expert Kevin Kelly, the co-founder of technology magazine Wired. State-run Xinhua news agency broadcast the chat live, billing Jia Jia as a special reporter. Jia Jia looks like a young woman in her early twenties, blinks and smiles in a fairly human way, moves her lips when she speaks, and has micro-expressions. But she had a hard time responding naturally to many of the questions posed by Kelly, sometimes taking up to 10 seconds to answer.

If a recent interaction between a human journalist and his Chinese robot counterpart is anything to go by, it'll be a while before a journalist job will be lost to (a robot in) China. On Monday (April 24), Jia Jia, a Chinese-manufactured robot under development for about three years (link in Chinese), had a conversation with AI expert Kevin Kelly, the co-founder of technology magazine Wired. State-run Xinhua news agency broadcast the chat live, billing Jia Jia as a special reporter. Jia Jia looks like a young woman in her early twenties, blinks and smiles in a fairly human way, moves her lips when she speaks, and has micro-expressions. But she had a hard time responding naturally to many of the questions posed by Kelly, sometimes taking up to 10 seconds to answer.

The phrase'hype cycle' could have been invented for the mobile marketing industry. Typically, a new tech's day in the sun lasts anything from six – 12 months, before the next big thing comes along. Think about Native, Wearables, Programmatic, Augmented Reality and Virtual Reality. All came, all are still very much around, but each has been superseded by the next. And if VR was last year's big thing, AI (Artificial Intelligence) is this year's, infiltrating an increasing number of aspects of our daily lives.

Uber has unveiled plans to partner with plane manufacturers to develop and test a network of flying cars by 2020. The ride-sharing company said it will run trials in the US city of Dallas and Dubai in the United Arab Emirates. The flying electric taxis are being developed with aviation companies including Embraer and Bell Helicopter. While the technology is largely unproven, Uber believes the service will eventually cost about the same as its car rides. Expanding on ideas first published in a white paper last October, the company said the electric vehicles will take off and land vertically like a helicopter, with zero emissions and minimal noise.

In the late 19th century, the Industrial Revolution introduced complicated farm machinery that changed the way farmers planted, cultivated and harvested their crops. These machines meant fewer farm hands were needed, but it created jobs for people to build and repair farm equipment. The improved benefits of utilizing farm machinery impacted the quality of life, it produced food faster, and it created jobs and a new life for farmers. Machine learning is today's Industrial Revolution. TV shows and movies currently portray machine learning as this creepy, self-aware, futuristic technology that takes over humans' jobs, but these examples do not properly show the real advancements of these cognitive systems.

Recently we talked before how big data is the new frontier with just .05% of all data available today having been analyzed. This means that all kinds of gold prospectors are lining up with their freshly crafted artificial intelligence (AI) algorithms looking to extract all the value they can from this wild west of data before someone else does. Perhaps nowhere is there more excitement at the moment than the applications to be had in the healthcare industry. Here's a look at just some of the startups that are applying artificial intelligence and big data to healthcare (courtesy of the bright minds over at CB Insights): The application that we've circled above is "drug discovery" using AI or what's also known as "computational drug discovery". The reason that this is now a thing is not just because of all the big data that's available now, but also because of how cheap cloud computing has become, not to mention the emergence of deep learning algorithms.

In the 1950s, when America was hopeful and reckless conjecture was encouraged, prognosticators had some wild ideas about 21st century technology. A few came true, like robot companions. But one concept in particular has endured without quite being realized -- the flying car. Check those special "future" editions of old magazines and you'll find plenty of stalwart citizens commuting to work in hovering sedans, with tail fins. So where did the dream go wrong?

Having lavished millions of dollars on data scientists to search for patterns in a deluge of digital information, banks and financial institutions need to start doing something to make that newfound intel pay. Big Data - the bits and bytes of everyday life harvested from our increasingly digital world - has been hailed as the foundation of a new financial architecture. Predictive analytics, machine learning and artificial intelligence (AI) are the mechanisms most commonly touted to realise that vision. But aside from sales traders using predictive analytics to help clients with their decision processes, some well-publicised robo-advisory services, and a handful of AI-managed funds, institutions have yet to deploy on any scale the means of capitalising on their newly bulging databases. Having new data-driven insights is great, but operationalising and monetising them is the tricky part.

"Thou canst not touch the freedom of my mind," wrote the playwright John Milton in 1634. But, nearly 400 years later, technological advances in machines that can read our thoughts mean the privacy of our brain is under threat. Now two biomedical ethicists are calling for the creation of new human rights laws to ensure people are protected, including "the right to cognitive liberty" and "the right to mental integrity". Scientists have already developed devices capable of telling whether people are politically right-wing or left-wing. In one experiment, researchers were able to read people's minds to tell with 70 per cent accuracy whether they planned to add or subtract two numbers.