Named one of the "Top Ten Technology Books of 2018" by Peter High, Forbes.com "Compared with the amount of ink spilled over the prospects of artificial general intelligence and all its accompanying fears--the singularity!--there's "…a readily understandable guide to artificial intelligence and the immensely consequential effects it could have on our economy, our society and our political system." -- Robert E. Rubin, former U.S. Treasury secretary and co-chair Emeritus, Council on Foreign Relations This 2018 book…on the timely topic of AI - tops my summer reading list. "This is a timely book, well written, and accessible putting forward their insights, and is well worth reading." Lawrence H. Summers, Charles W. Eliot Professor, former president, Harvard University; former secretary, US Treasury; and former chief economist, World Bank-- "AI may transform your life.

Artificial Intelligence (AI) is a lot of things. It's a game changer for business, it can enable humans to work smarter and faster than ever before, and it could potentially have a significant impact on economies and the labor market. But at the root of it all – the function which gives AI value – is the ability to make predictions. Calculating – more quickly and accurately than has ever been possible – what the likelihood is of a particular outcome, is the fundamental advance which AI brings to the table. To start with, it's worth defining what we mean when we talk about AI.

As AI and machine learning have infused themselves over the last half decade into nearly every corner of our lives, there has been a growing interest in how the biases of these models may be silently impacting society. Much of this focus has been on the issues of biased training data and a homogeneous workforce that lacks sufficient diversity of experience to recognize bias. However, lost in this conversation is the far bigger driving force: the lack of economic incentive to minimize bias in the technologies that increasingly power our lives. The digital world is an incredibly biased place. Geographically, linguistically, demographically, economically and culturally, the technological revolution has skewed heavily towards a small number of very economically privileged slices of society.

Lawmakers are ignoring simple economics in favor of lunatic policies. If it continues, a voter revolution is guaranteed. The government shutdown continues as the debate over a border wall enters its fourth contentious week. Neither side in this has shown any sign of willingness to compromise. This remains a stalemate as of now, the very definition of it, or at least that's what it seems like from the outside.

The CIFAR deep learning summer school in Toronto has been training the top AI researchers entering or finishing Ph.D. programs since 2005. Over 1,200 students from 60 different countries applied, of which 200 were selected to attend. Attendees represent some of the leading AI labs in the world, Montreal Institute of Learning Algorithms (MILA), University College London, University of Toronto, University of Alberta, Berkeley, NYU, Columbia, CMU, MIT, ETH Zurich, and Stanford. Every year, the school has trained the next generation of top AI researchers which now hold top posts at AI companies like Google, Facebook, Tesla, and Uber. During an intense 10-day period, students learn the tricks of the trade from top AI researchers like deep learning pioneers Yoshua Bengio (MILA), Geoff Hinton (UofT), and reinforcement learning pioneer, Richard Sutton (University of Alberta, Google Deepmind).

Artificial Intelligence (AI) is a lot of things. It's a game changer for business, it can enable humans to work smarter and faster than ever before, and it could potentially have a significant impact on economies and the labor market. But at the root of it all – the function which gives AI value – is the ability to make predictions. Calculating – more quickly and accurately than has ever been possible – what the likelihood is of a particular outcome, is the fundamental advance which AI brings to the table. To start with, it's worth defining what we mean when we talk about AI.

Just a few days before Christmas 2015, I found myself staring down the silicone mouth hole of the "world's first blowjob robot." I'd set out to find the future of sex but quickly realized that: 1) The Autoblow 2 wasn't a robot at all, and 2) I'd be better off sticking to a grapefruit for simulated fellatio. My encounter with the Autoblow 2 was both disturbing and fascinating and sparked a 15-month exploration of male sex toys that came to a head in a small sex-robotics R&D lab in Southern California. NSFW Warning: This story may contain links to and descriptions or images of explicit sexual acts. The lab is staffed by a small group of artists who meticulously craft individual body parts en masse. There's a man painting erect penises, another carving the contours of a cheekbone, and in the far right corner sits an empty workstation for the lab's dedicated eye technician.

The year 1995 was heralded as the beginning of the "New Economy." Digital communication was set to upend markets and change everything. It wasn't that we didn't recognize that something changed. It was that we recognized that the old economics lens remained useful for looking at the changes taking place. The economics of the "New Economy" could be described at a high level: Digital technology would cause a reduction in the cost of search and communication.

The year 1995 was heralded as the beginning of the "New Economy." Digital communication was set to upend markets and change everything. It wasn't that we didn't recognize that something changed. It was that we recognized that the old economics lens remained useful for looking at the changes taking place. The economics of the "New Economy" could be described at a high level: Digital technology would cause a reduction in the cost of search and communication.