An Oxford University spin-off has developed the technology to control automated cars, but it doesn't make hardware, rather providing the "brains" of the vehicle. Oxbotica's "brain" – called Selenium – can recognise its location and surroundings and, crucially, it can be applied to anything that moves – not just cars. The company's co-founder, Paul Newman, explained the technology could be used in anything from space ships to fork lift trucks in warehouses. It's because the company has invested so much into the research behind the technology that it's become such an innovative solution. "We never called ourselves a driverless car group," Posner told the FT. That has applications in all places."

Last week, Treasury Secretary Steven Mnuchin said he wasn't worried at all about advancing artificial intelligence taking over jobs anytime soon. In fact, he said, he wouldn't be worried about it for for another 50 to 100 years. As I wrote recently, many experts would disagree with the notion that displacement--or at the very least, shifts--in the labor market due to automation are that far afield. Recent studies from McKinsey and the economists Carl Benedikt Frey and Michael A. Osborne estimate that around 45 percent of workers currently perform tasks that could be automated in the near future. And the World Bank estimates that around 57 percent of jobs could be automated within the next 20 years.

Search Beyond is a forum that brings together the latest discussion from some of the UK's most innovative independent digital agencies. A handful of senior practitioners meet on a quarterly basis to debate a topic facing the digital marketing industry, with the insights and output appearing here on Think with Google. In our second Search Beyond session, we wanted to hear how independent agencies are preparing to face down increasing complexities in the digital landscape by adopting machine learning. The participants launched into the discussion by revealing how they're already putting these tools to use in their own work on behalf of clients today. "An element of automation is machine learning, so that is a lot of what we do", said Maria Yiangou, Group Account Director at All Response Media.

We introduce a novel loss max-pooling concept for handling imbalanced training data distributions, applicable as alternative loss layer in the context of deep neural networks for semantic image segmentation. Most real-world semantic segmentation datasets exhibit long tail distributions with few object categories comprising the majority of data and consequently biasing the classifiers towards them. Our method adaptively re-weights the contributions of each pixel based on their observed losses, targeting under-performing classification results as often encountered for under-represented object classes. Our approach goes beyond conventional cost-sensitive learning attempts through adaptive considerations that allow us to indirectly address both, inter- and intra-class imbalances. We provide a theoretical justification of our approach, complementary to experimental analyses on benchmark datasets. In our experiments on the Cityscapes and Pascal VOC 2012 segmentation datasets we find consistently improved results, demonstrating the efficacy of our approach.

Compared to the financial services sector where blockchain and AI have, in many ways, revolutionised operations, healthcare has been slower to move with these types of innovation. At the same time, people are living longer but present more care demands on the health system, leading to bed shortages and longer wait lists for treatment. With the NHS creaking under ever-increasing pressures to serve a growing population of the elderly and obese, and all on unsustainable budgets, mobilising technology to provide relief from this strain seems like the only solution to an unfolding crisis. One major trend in healthcare is intervention; the growing focus on prevention rather than cure. The growth in sedentary lifestyles imposes an unsustainable burden on healthcare provision.

Want to know more about AI and how it relates to 4th Industrial Revolution? What are the drivers behind this? How do we see past the Hollywood myths of the rise of machine intelligence? What are the future consequences of this new race in intelligence? This event can contribute towards your Continuing Professional Development (CPD) as part of the IET's CPD monitoring scheme.

Artificial intelligence and drones will be key policing tools in the future amid budget and job cuts, Gwent Police's chief constable has said. Jeff Farrar said he foresees every police vehicle carrying a drone in the years to come and for more computers to do jobs "that do not involve emotion". Gwent has had £50m of funding cuts and still needs to make £9m of savings. It has also lost 300 officers since 2011. But Mr Farrar said the force was recruiting again after a jobs freeze.

This is a guest post by the Secretary of State for Culture, Media and Sport, Karen Bradley, coinciding with the launch of the UK's Digital Strategy. Digital technology already underpins innovation and improvements in productivity across the whole economy, and the government's new Digital Strategy I am publishing today aims to harness this power and make Britain the best place in the world to start and grow a digital business. The strategy will also ensure the benefits are felt right across the country and throughout all sections of society – with nobody left behind. We already have some of the most exciting startups in the world, and some of the strongest technology clusters. But as we prepare to leave the European Union, the UK's global competitiveness will increasingly depend on not only a vibrant digital sector but also on all our businesses using the best digital technology and data to drive innovation and productivity.

Growth is shifting, disruption is accelerating, and societal tensions are rising. Confronting these dynamics will help you craft a better strategy, and forge a brighter future. "The trend is your friend." It's the oldest adage in investing, and it applies to corporate performance, too. We've found through our work on the empirics of strategy that capturing tailwinds created by industry and geographic trends is a pivotal contributor to business results: a company benefiting from such tailwinds is four to eight times more likely to rise to the top of the economic-profit performance charts than one that is facing headwinds. It's easy, however, to lose sight of long-term trends amid short-term gyrations, and there are moments when the nature and direction of those trends become less clear. Today, for example, technology is delivering astounding advances, and more people are healthy, reading, and entering the global middle class than at any period in human history. At the same time, the post–Cold War narrative of progress fueled by competitive markets, globalization, and innovation has lost some luster. Those contradictions are showing up in politics, and the long-term trends underlying them are reshaping the business environment.

This post is the written version of the talk I presented at The Inbounder World Tour Madrid on March 17. Who knows me or simply follows me on social networks, knows that I am a science fiction geek, which is not surprising in a man who in his childhood saw "Star Wars" in the movie theater or the original series of "Battlestar Galactica" on television. Robots are ones of the main characters in sci-fi tv series, movies and novels. These mechanical beings with human or superhuman intelligence have always fascinated us. If we look only at the history of cinema, we can find some naive robots, like the Tin Man of "The Wizard of Oz", or subtly dangerous, like Ava in "Ex-Machina", or more humans than humans, like the mythical Roy Batty of "Blade Runner".