Ford Motor Co. became the world's first automaker to announce hard plans to deliver driverless cars. "We'll have mass-produced, fully autonomous cars on the road in five years," said Raj Nair, head of global product development, at an event Tuesday in Palo Alto, Calif. Ford said the cars would be first used for ride hailing and ride sharing, but no companies were named. A few years after that, the company plans to roll out driverless cars to consumers. All the carmakers, plus Google and maybe Apple, are working on driverless cars, but none has announced firm dates.

An anonymous reader writes: MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) says that while many'analyst-driven solutions' rely on rules created by human experts and therefore may miss attacks which do not match established patterns, a new artificial intelligence platform changes the rules of the game. The platform, dubbed AI Squared (AI2), is able to detect 85 percent of attacks -- roughly three times better than current benchmarks -- and also reduces the number of false positives by a factor of five, according to MIT. The latter is important as when anomaly detection triggers false positives, this can lead to lessened trust in protective systems and also wastes the time of IT experts which need to investigate the matter. AI2 was tested using 3.6 billion log lines generated by over 20 million users in a period of three months. The AI trawled through this information and used machine learning to cluster data together to find suspicious activity.

Since the early days of the current Big Data and Data Science movements, many data scientists have been devoted to applications of those data collections and advanced algorithms to solving societal problems. Subsequently, informal groups (e.g., meetups) and entire organizations have coalesced around particular approaches (e.g., data hackathons; and online competitions), or particular societal needs (e.g., DataKind.org; The range and depth of those applications have a tremendous reach: from human health to ocean health, from pet shelters to sheltering persons in need, from healthy lifestyle change to climate change, from smart cities to smart farms, from precision law enforcement to precision medicine, from improving commuter traffic to stopping human trafficking. The world is data now. Data are the new asset to fuel insightful discoveries, smarter decisions, essential innovations, and better outcomes.

There are roughly 863 million people living in slums, with that number continuously rising, according to the World Health Organization. That's a massive issue, especially when you factor in Maslow's hierarchy of needs, a theory in psychology that outlines the basic needs of humans. As Berok Khoshnevis, a professor of engineering at the University of Southern California, points out, shelter is considered a fundamental need in Maslow's pyramid. That's why Khoshnevis wants to tackle the world's housing crisis head on using tech. Scroll down to see his plan.

Based on the disturbing number of successful data breaches over the past few years, it's pretty evident that organizations are being overwhelmed by the growing number of threats.

Nick Triantos spent the past year trying to commercialize the technology being developed at SRI International, the Stanford research offshoot that helped invent the Internet and Siri, among other things. Now he has joined Ignition Partners at its new office in Los Altos, where he says he will be able to help create companies from a broader range of innovation. Triantos said his focus will be on business-focused startups, particularly ones working in artificial intelligence, cybersecurity and augmented and virtual reality. But he doesn't expect that will include startups in the currently hot space of chatbots, despite his background with voice recognition and machine learning at SRI. The following Q&A about these and other topics has been edited for length and clarity. What was your role at SRI and why are you leaving there? Unfortunately, not many people know about SRI.

Machine learning has had fruitful applications in finance well before the advent of mobile banking apps, proficient chat bots, or search engines. Given high volume, accurate historical records, and quantitative nature of the finance world, few industries are better suited for artificial intelligence. There are more uses cases of machine learning in finance than ever before, a trend perpetuated by more accessible computing power and more accessible machine learning tools (such as Google's Tensorflow). Today, machine learning has come to play an integral role in many phases of the financial ecosystem, from approving loans, to managing assets, to assessing risks. Yet, few technically-savvy professionals have an accurate view of just how many ways machine learning finds it's way into their daily financial lives.

More importantly, we track how the functionality of Cloud Computing, Artificial Intelligence, Mobility, Big Data, Robotics and the Internet of Things will require new approaches to cybersecurity. If you enjoy the daily Threat Brief we know you will enjoy CTOvision.

Robert Gordon has written a magnificent book on the economic history of the United States over the last one and a half centuries. His study focuses on what he calls the "special century" from 1870 to 1970--in which living standards increased more rapidly than at any time before or after. The book is without peer in providing a statistical analysis of the uneven pace of growth and technological change, in describing the technologies that led to the remarkable progress during the special century, and in concluding with a provocative hypothesis that the future is unlikely to bring anything approaching the economic gains of the earlier period. The message of Rise and Fall is this. For most of human history, economic progress moved at a crawl. According to the economic historian Bradford DeLong, from the first rock tools used by humanoids three million years ago, to the earliest cities ten thousand years ago, through the Middle Ages, to the beginning of the Industrial Revolution around 1800, living standards doubled (with a growth of 0.00002 percent per year). Another doubling took place over the subsequent period to 1870. Then, according to standard calculations, the world economy took off. Gordon focuses on growth in the United States.

Firefighters undergo rigorous training before responding to their first call but they still aren't superhuman. In a burning building there's a difference between what someone can sense in the surroundings and all the environmental data around him. Researchers at NASA's Jet Propulsion Laboratory (JPL) and the Department of Homeland Security (DHS) are working to fill that gap with an artificial intelligence system that can collect relevant information from the environment and relay it back to firefighters in real time. AUDREY -- or, the Assistant for Understanding Data through Reasoning, Extraction, and sYnthesis -- is integrated with the Internet of Things, which lets the system connect to wearable sensors and head-mounted displays on each firefighter, communicating data about temperatures, hazardous gases, and even GPS locations from one team member to another. "When first responders are connected to all these sensors, the AUDREY agent becomes their guardian angel," Edward Chow, manager of JPL's Civil Program Office and program manager for AUDREY, said in a press release.