Mark Curtis, Fjord co-founder and chief client officer – and Inspirefest 2016 speaker – tells us how design thinking can not only bring real human emotion into business, but it can also help forge the future of work. The world is changing at a pace we've not witnessed since the industrial revolution. With the added uncertainty of Brexit and global political turmoil, the future has never been less predictable, particularly for businesses that are so exposed to outside influence. But from challenge emanates great opportunity, and, with advancements in design, technology and even'contentious' artificial intelligence (AI), the workplace of the future is primed for disruption from within. So what do organisations need to do to future-proof themselves against these outside sociopolitical, economic and sometimes geographical challenges?

There's a lot of talk these days about how robots, software, and artificial intelligence will (or won't) steal jobs. On one side of the debate you find denialists, like U.S. Treasury Secretary Steven Mnuchin, who believes that widespread impact on jobs is "50 or 100 years" away. On the other side, you find steadfast pessimists: Analysts who believe that robots will replace as many as half the jobs in the economy, like Oxford scholars Carl Frey and Michael Osborne, or Martin Ford, author of Rise of the Robots. Each of these views holds elements of truth, but both are also fundamentally incorrect. Denialists are wrong, as automation technologies have replaced human jobs for more than a century and this trend has been accelerating for 10 years.

ABSTRACT Automatically assessing emotional valence in human speech has historically been a difficult task for machine learning algorithms. The subtle changes in the voice of the speaker that are indicative of positive or negative emotional states are often "overshadowed" by voice characteristics relating to emotional intensity or emotional activation. In this work we explore a representation learning approach that automatically derives discriminative representations of emotional speech. In particular, we investigate two machine learning strategies to improve classifier performance: (1) utilization of unlabeled data using a deep convolutional generative adversarial network (DCGAN), and (2) multitask learning. Our speakerindependent classification experiments show that in particular the use of unlabeled data in our investigations improves performance of the classifiers and both fully supervised baseline approaches are outperformed considerably. We improve the classification of emotional valence on a discrete 5-point scale to 43.88% and on a 3-point scale to 49.80%, which is competitive to state-of-the-art performance. Index Terms-- Machine Learning, Affective Computing, Semisupervised Learning, Deep Learning 1. INTRODUCTION Machine Learning, in general, and affective computing, in particular, rely on good data representations or features that have a good discriminatory faculty in classification and regression experiments, such as emotion recognition from speech.

SYRACUSE, N.Y.--It was a nightmare scenario: As thousands of Syracuse University basketball fans poured into town on February 1, 2014 for a big match against arch rival Duke, a water main break flooded Armory Square, surrounding the city's iconic 24-second shot clock monument. Days before the game, there were 11 other water main breaks around the city. Mayor Stephanie Miner was desperate for help to get a handle on the problem; on average, water lines in the city were breaking 332 times a year, nearly once every day. But she couldn't get the state to help foot the bill for the onerous costs of updating the city's underground infrastructure. She even tried to shame state officials with a "Hunger Games"-style ad campaign that showed her wading in thigh-high water wielding a wrench.

From the printing press to the digital age, new technology has long had a tendency to be viewed as disruptive, and is often met with resistance in the workplace. This is also the case when new advancements shift or evolve how we work. Artificial Intelligence (AI), what many have deemed the cause of the "fourth industrial revolution," is no different. While humans aren't always inventing new things, one thing we're really good at is figuring out how to do things better, faster, and more efficiently. Thirty years ago, robots might have seemed limited to science fiction novels, but even today there are many industries that have seen the shift towards automation take hold.

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next two months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. After seeing this video, I'm convinced that RoboCup 2017 in Nagoya will be the best robot competition in the history of the universe. NASA's humanoid robots are too big and expensive to spend their time doing human-robot interaction studies, so students at Rice University built NotBot to take their place: It's not at all surprising that a human in a robot suit is much more capable than an actual robot for many (if not most) applications.

Android Things allows you to make amazing IoT devices with simple code, but one of the things that can make a device extraordinary is machine learning. While there are a few services available online that will allow you to upload data and will return results, being able to use machine learning locally and offline can be incredibly useful. Machine learning can help solve problems that conventional apps cannot. To provide context, let's go through a simple example where machine learning can be used with an IoT device to improve daily life. Here in Colorado, it's not uncommon to see news articles about wildlife coming out from the mountains and walking around a downtown: I've even had a friend post video of a bear outside of their home!

What is Jeff Bezos "Day 1" philosophy? "The outside world can push you into Day 2 if you won't or can't embrace powerful trends quickly. If you fight them, you're probably fighting the future. Embrace them and you have a tailwind"--Jeff Bezos A recent Security and Exchange Commission (SEC) filing, Amazon Exhibit 99.1 statement [1] is really quite interesting. Also known as the 2016 Letter to Shareholders, Jeff Bezos sketched out a philosophy that he calls "Day 1" and "Day 2". This idea came about in the very early days of Amazon. He occupied a building called "Day 1", named as a reminder that the company should always be in "Day 1" mode.

Planetary Resources, a company hoping to make asteroid mining into a trillion dollar industry, earlier this year unveiled the world's first 3D printed object made from bits of an asteroid. Just a few years ago, most 3D printing was only used for building prototypes, which would then go on to be manufactured via conventional processes. But it's now increasingly being used for manufacturing in its own right. Nearly two years ago, NASA even sent a 3D printer to the International Space Station with the goal of testing how the technology works in micro-gravity. While the printer resembles a Star Trek replicator, it's not quite that sophisticated yet; the objects it can print are small prototypes for testing.

"Very little skill" is required to become a cyber criminal, according to a new report. Research from the National Crime Agency (NCA) claims that free "off-the-shelf" hacking tools, online tutorials and video guides are making it increasingly easy for young people become involved in cyber crime. The report also says that, while financial gain is a key incentive for some offenders, it isn't always key, with many instead motivated by a "sense of accomplishment" and building a reputation. The average age of the young offenders involved in the study was 17, and the NCA says they're "unlikely" to commit more traditional crimes, such as theft, fraud and sexual offences. The I.F.O. is fuelled by eight electric engines, which is able to push the flying object to an estimated top speed of about 120mph.