ground transportation

AI, automation, and the future of work: Ten things to solve for


Beyond traditional industrial automation and advanced robots, new generations of more capable autonomous systems are appearing in environments ranging from autonomous vehicles on roads to automated check-outs in grocery stores. Much of this progress has been driven by improvements in systems and components, including mechanics, sensors and software. AI has made especially large strides in recent years, as machine-learning algorithms have become more sophisticated and made use of huge increases in computing power and of the exponential growth in data available to train them. Spectacular breakthroughs are making headlines, many involving beyond-human capabilities in computer vision, natural language processing, and complex games such as Go. These technologies are already generating value in various products and services, and companies across sectors use them in an array of processes to personalize product recommendations, find anomalies in production, identify fraudulent transactions, and more.

MIT researchers teach autonomous cars how to deal with selfish drivers


New research from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) examines the problem of how a self-driving car can predict the behavior of other drivers on the road. This prediction requires a degree of social awareness which is difficult for machines, so the researchers took tools from social psychology to help the system classify driving behaviors into either selfish and selfless. The system observed human driving behaviors and was then able to better predict the movements of other cars when it came to merging lanes or making unprotected left turns, with 25 percent greater accuracy than previously. This kind of insight into human behavior is important for safety when autonomous and human drivers are sharing the road. An Uber self-driving car which struck and killed a pedestrian last year, for example, didn't have the ability to recognize jaywalkers.

Uber driver mostly to blame for fatal self-driving crash, NTSB finds

USATODAY - Tech Top Stories

The operator of a self-driving Uber that hit and killed a pedestrian in Tempe last year was the primary cause of the accident because she was watching "The Voice" on her phone instead of the road. That's the finding from the National Transportation Safety Board, although the federal agency identified several other contributory causes in its final report submitted on Tuesday. The board also recommended new federal and state requirements for testing autonomous cars on public roads. Beyond the driver, the board found plenty of blame to go around for the nation's first pedestrian fatality involving a self-driving car. Officials called out Uber's lax safety culture, the pedestrian who was high on methamphetamine, and the state of Arizona's lack of safety requirements for the cars.

Train & Tune Your Computer Vision Models at Scale Registration


Whether you are training a self-driving car, detecting animals with drones, or identifying car damage for insurance claims, the steps needed to effectively train a computer vision model at scale remain the same.

Electric bike startup launches weekly subscription plan targeted at delivery people and gig workers

Daily Mail - Science & tech

This week, a Sydney-based electric bicycle company Bolt Bikes officially announced its expansion into the US and UK. Unlike other e-bike companies, Bolt Bikes wants its primary customers to be gig workers instead of pedestrians looking to save a little time. For a $39 a week, subscribers will get their own e-bike, a battery charger, a smartphone mount for their handlebars, a U-Lock, and full maintenance and repair coverage. But most importantly, they'll get a shot at becoming an on-demand delivery person for any number of apps that have become popular in recent years, including Uber Eats, Instacart, Deliveroo, and Door Dash. Since June, Bolt Bikes has been running a pilot program in San Francisco with Postmates, a food delivery app first founded in 2011.

A Framework For Developing A National Artificial Intelligence Strategy - Liwaiwai


We are now in the Fourth Industrial Revolution. Artificial Intelligence (AI) is the fuel behind all the developments that we are witnessing in this era. The continuous and vast development of computing infrastructure changed our goal from machine programming to machine learning. Today we see self-driving cars, translation software, virtual assistants, drones, and other things which are powered by AI. As our technologies continue to grow, AI will dominate our cities even further.

How Selfish Are You? It Matters for MIT's New Self-Driving Algorithm


Our personalities impact almost everything we do, from the career path we choose to the way we interact with others to how we spend our free time. But what about the way we drive--could personality be used to predict whether a driver will cut someone off, speed, or, say, zoom through a yellow light instead of braking? There must be something to the idea that those of us who are more mild-mannered are likely to drive a little differently than the more assertive among us. At least, that's what a team from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) is betting on. "Working with and around humans means figuring out their intentions to better understand their behavior," said graduate student Wilko Schwarting, lead author on the paper published this week in Proceedings of the National Academy of Sciences.

Microsoft sends a new kind of AI processor into the cloud


Microsoft rose to dominance during the '80s and '90s thanks to the success of its Windows operating system running on Intel's processors, a cosy relationship nicknamed "Wintel". Now Microsoft hopes that another another hardware–software combo will help it recapture that success--and catch rivals Amazon and Google in the race to provide cutting-edge artificial intelligence through the cloud. Microsoft hopes to extend the popularity of its Azure cloud platform with a new kind of computer chip designed for the age of AI. Starting today, Microsoft is providing Azure customers with access to chips made by the British startup Graphcore. Graphcore, founded in Bristol, UK, in 2016, has attracted considerable attention among AI researchers--and several hundred million dollars in investment--on the promise that its chips will accelerate the computations required to make AI work.

Self Driving Cars Have a Philosophical Brain.


AI distills data from principles of philosophy using patterns we see in physics. The universe gives us clues to structure our thinking because we are captive to our observations. While we think we can speculate widely, we're merely playing within the belly of the universe that has dictated our paradigms. When you lift the hood of an autonomous car, there is a philosophical brain. AI here is referring to algorithms that perform functions that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.

Principles of Eventual Consistency and AI Autonomous Cars - AI Trends


Rather than covering further the distributed system aspects of consistency, I'd like to shift your attention toward another angle on consistency as it relates to AI self-driving cars.