Technology is changing how we practice medicine. Sensors and wearables are getting smaller and cheaper, and algorithms are becoming powerful enough to predict medical outcomes. Yet despite rapid advances, healthcare lags behind other industries in truly putting these technologies to use. A major barrier to entry is the cross-disciplinary approach required to create such tools, requiring knowledge from many people across many fields. We aim to drive the field forward by unpacking that barrier, providing a brief introduction to core concepts and terms that define digital medicine. Specifically, we contrast "clinical research" versus routine "clinical care," outlining the security, ethical, regulatory, and legal issues developers must consider as digital medicine products go to market. We classify types of digital measurements and how to use and validate these measures in different settings. To make this resource engaging and accessible, we have included illustrations and figures ...

Ocado and Google DeepMind executives are among a cohort of experts that have been called to advise the Government on how to boost the use of artificial intelligence in Britain. Paul Clarke, chief technology officer of the e-commerce company, and DeepMind co-founder Mustafa Suleyman will join the new lineup of the Government's AI council, an advisory group set up as part of a push to boost investment in the technology. Mastercard vice chairman Ann Cairns, Amazon machine learning director Neil Lawrence and Microsoft research lab director Chris Bishop are also among those who gained seats on the new council. The executives are expected to promote the use of AI by businesses in the UK and advise the Government about future public investments in the industry. The Government already set aside £3m for AI projects aimed at boosting productivity in financial and legal services last year as part of this effort.

Artificial intelligence is a big talking point these days and I use this video series to talk about it in the context of games. I run a series of videos that address this topic in different ways: Case Studies How artificial intelligence is applied in commercial video games. How AI research in games is used to enhance our understanding of the field. AI 101 Explaining core AI tech in the games industry, how it works and clever ways it is used in games. Design Dive How AI applications in games influence game design.

Hidden away somewhere in my attic is an old Xbox 360 that I'll never throw away. On its hard drive is a Minecraft save file that contains the first house my oldest son ever built in the game. He was seven and, coming from a boy on the autism spectrum with a limited vocabulary and no patience to draw and paint, his creation was a revelation. Sure, it is a monstrous carbuncle, a mess of wooden planks, cobblestone and dirt. But it is also the greatest building I ever saw.

Neuroscience is a multidisciplinary science that is concerned with the study of the structure and function of the nervous system. When applied to our professional lives, neuroscience can help us to unlock our greatest potential. Increasing your meaningful productivity can have a huge impact on your day-to-day work and can greatly influence your professional success over a long period of time. This week on the Science of Social Media, we're examining the fascinating field of neuroscience and how it can positively influence our marketing productivity. Think of today's show as little tricks for your brain to work smarter, not harder.

Our first article (What is AI?) highlighted that Artificial intelligence already has a huge impact on our lives. People are concerned about AI replacing jobs or being misused, with good reason. So here we take a broad look at the ethics of AI. AI is software: it's no more intrinsically good or bad than a database or website. Because AI has great power, the way we apply it is critically important.

Background: We think that AI is all-knowing, but actually it's only partly so. When it comes to the AI behind driverless technology, for instance, sensors can take fantastically granular pictures of streets and hazards of all types, and AI can be fed with the experience of every type of driving situation. But autonomous technology companies still need humans to inform the AI what it's looking at -- to circle things like trees, stop signs and crosswalks. The big picture: The winners are AI companies, which are mostly in the U.S., Europe, and China. The losers are workers in both rich and relatively poor countries, who are paid little.

YITU is also expanding to help cities digitize data such as traffic patterns, energy supply information and infrastructure development. Now the company plans to move even further afield. In January YITU opened its first international office in Singapore, where it plans to hire more than 50 researchers, and the company recently formed a strategic cooperation with local governments and various organizations in Britain in the fields of public security, finance and health care. Although YITU's track record is outstanding thus far -- it won first place in the 2017 Face Recognition Prize Challenge organized by Intelligence Advanced Research Projects Activity for its highly acclaimed facial recognition devices, which boast a 95.5% accuracy rate -- the company still has work ahead to become the facial recognition leader in China. Chinese start-ups Megvii Technology and SenseTime are considered to have the most powerful facial recognition systems in the world.

Halfbrick Studios is a professional game development studio based in Brisbane, Australia. Founded in 2001, Halfbrick has developed many popular games, including Fruit Ninja, Jetpack Joyride, and Dan the Man. When Halfbrick first learned about Firebase Predictions, they were excited about targeting users based on predicted behavior, rather than historic. Re-engagement is tough, so intervening before a user churned - based on predictions instead of ad hoc heuristics - seemed like a strong strategy. They had been trying to create their own churn prediction models, but like many companies, didn't have the time or resources to properly devote to the problem.

Police departments across the nation are generating leads and making arrests by feeding celebrity photos, CGI renderings, and manipulated images into facial recognition software. Often unbeknownst to the public, law enforcement is identifying suspects based on "all manner of'probe photos,' photos of unknown individuals submitted for search against a police or driver license database," a study published on Thursday by the Georgetown Law Center on Privacy and Technology reported. The new research comes on the heels of a landmark privacy vote on Tuesday in San Francisco, which is now the first US city to ban the use of facial recognition technology by police and government agencies. A recent groundswell of opposition has led to the passage of legislation that aims to protect marginalized communities from spy technology. These systems "threaten to fundamentally change the nature of our public spaces," said Clare Garvie, author of the study and senior associate at the Georgetown Law Center on Privacy and Technology.