The 28,000-word report, "Artificial Intelligence and Life in 2030," looks at eight categories -- from employment to healthcare, security, entertainment, education, service robots, transportation and poor communities -- and tries to predict how smart technologies will affect urban life.

How do you create a movie trailer about an artificially enhanced human? Fox wanted to explore using artificial intelligence (AI) to create a horror movie trailer that would keep audiences on the edge of their seats. Movies, especially horror movies, are incredibly subjective. Think about the scariest movie you know (for me, it's the 1976 movie, "The Omen"). I can almost guarantee that if you ask the person next to you, they'll have a different answer.

In the midst of an international freakout about what is to become of us as robots learn to do for free the things humans do to make a living, it's easy to feel lost in the flurry of papers and panels and general pontification on how terrified we ought to feel about it. We at Wonkblog have created a repository of evidence on all sides of the debate, and will maintain it as a public service as long as automation anxiety continues to be a thing. To that end, please send worthy contributions to lydia.depillis@washpost.com. Robots are taking our jobs, and the future looks grim! Robots are taking our jobs, but everything might be fine!

The entire tech industry is racing to build artificial intelligence and machine learning technologies, computers that can learn and react to stuff they've never seen before, sort of like a human brain.

Like all financial companies PayPal worries about fraudsters, armed with stolen credentials, logging into a legitimate customer's account and using a credit card linked to it. "We want to stop these guys at our door," said Hui Wang, senior director of global risk and data sciences at PayPal. The company has more reason than most to worry, given its high visibility and massive payment volumes. It generates 10,900 in payments every second, and it handled 4.9 billion payments in 2015 for 188 million customers in 202 countries. To detect suspicious activity, and more importantly to separate false alarms from true fraud, PayPal uses a homegrown artificial intelligence engine built with open-source tools.

Serving more than a billion people a day, Facebook has its work cut out for it when providing customized news feeds. That is where the social network giant takes advantage of deep learning to serve up the most relevant news to its vast user base. Facebook is challenged with finding the best personalized content, Andrew Tulloch, Facebook software engineer, said at the company's recent @scale conference in Silicon Valley. "Over the past year, more and more, we've been applying deep learning techniques to a bunch of these underlying machine learning models that power what stories you see." Applying such concepts as neural networks, deep learning is used in production in event prediction, machine translation models, natural language understanding, and computer vision services. Event prediction, in particular, is one of the largest machine learning problems at Facebook, which must serve the top couple of stories out of thousands of possibilities for users, all in a few hundred milliseconds. "Predicting relevance in and of itself is a very challenging problem in general and relies on understanding multiple content modalities like text, pixels from images and video, and the social context," Tulloch said.

This story was delivered to BI Intelligence IoT Briefing subscribers. To learn more and subscribe, please click here. Baidu, the Chinese-based internet services conglomerate, has made several major announcements about its upcoming IoT projects. The company's plans center on a revamped artificial intelligence (AI) platform, which the company hopes will enable it to effectively increase its presence in the world of the IoT. Baidu plans to use this revamped AI platform to develop a voice assistant similar to Amazon's Echo, reports Bloomberg. It will be working with speaker manufacturer Harman Industries to develop the device, which it hopes will allow users to order food, summon a ride, or control smart home products via voice commands.

For years, science-fiction moviemakers have been making us fear the bad things that artificially intelligent machines might do to their human creators. But for the next decade or two, our biggest concern is more likely to be that robots will take away our jobs or bump into us on the highway. Now five of the world's largest tech companies are trying to create a standard of ethics around the creation of artificial intelligence. While science fiction has focused on the existential threat of A.I. to humans, researchers at Google's parent company, Alphabet, and those from Amazon, Facebook, IBM and Microsoft have been meeting to discuss more tangible issues, such as the impact of A.I. on jobs, transportation and even warfare. Tech companies have long overpromised what artificially intelligent machines can do.

Amazon poaches eBay A.I. chief, continues ramping up machine learning operations See The Eerie Sci-Fi Movie Trailer Made By IBM's Artificial Intelligence

Convolutional Neural Networks (ConvNets or CNNs) are a category of Neural Networks that have proven very effective in areas such as image recognition and classification. ConvNets have been successful in identifying faces, objects and traffic signs apart from powering vision in robots and self driving cars. In Figure 1 above, a ConvNet is able to recognize scenes and the system is able to suggest relevant tags such as'bridge', 'railway' and'tennis' while Figure 2 shows an example of ConvNets being used for recognizing everyday objects, humans and animals. Lately, ConvNets have been effective in several Natural Language Processing tasks (such as sentence classification) as well. ConvNets, therefore, are an important tool for most machine learning practitioners today. However, understanding ConvNets and learning to use them for the first time can sometimes be an intimidating experience.