Results


Machine learning and data are fueling a new kind of car, brought to you by Intel

@machinelearnbot

The automobile is being dismantled, reimagined, and rebuilt in Silicon Valley. Intel's proposed $15.3 billion acquisition of Mobileye, an Israeli company that supplies carmakers with a computer-vision technology and advanced driver assistance systems, offers a chance to measure the scale of this rebuild. In particular, it shows how valuable on-the-road data is likely to be in the evolution of automated driving. While the price tag might seem steep, especially with so many players in automated driving today, Mobileye has some key technological strengths and strategic advantages. It's also developing new technologies that could help solidify this position.


New Google Street View Cameras Will Fuel AI Assistants

#artificialintelligence

Wired reports that the cameras Google uses to create imagery on its Street View service have gotten their first upgrade in eight years. Those units record images of stores, road signs, and other objects at the side of the road in incredible detail--and information gleaned from the data will feed Google's ever-hungry machine-learning algorithms. New 360-degree cameras allow users to upload their own panoramas to Street View, and the company hopes cities and other organizations may do the same to keep things fresh. All of that data will be indexed by Google's algorithms--so who knows, maybe one day, a handwritten "sorry we're closed today" sign might stop a wasted journey for a sandwich.


Demystifying AI: Understanding the human-machine relationship

#artificialintelligence

Rules are then written for the computer system to learn about all the data points and make calculations based on the rules of the road. Computer systems are programmed with machine learning algorithms and continuously learn to look at more data more quickly than any human would be able to. It might even notice lots of interactions when "Fly the Friendly Skies" ads are placed next to images of a person being brutally pulled off the plane and place more ads there! Artificial intelligence, machine learning and "self-aware systems" are real.


Machine learning and data are fueling a new kind of car, brought to you by Intel

#artificialintelligence

Intel's proposed $15.3 billion acquisition of Mobileye, an Israeli company that supplies carmakers with a computer-vision technology and advanced driver assistance systems, offers a chance to measure the scale of this rebuild. The company's vision systems are a simple, low-cost solution that offers surprisingly sophisticated sensing. This involves capturing images as cars drive around, and annotating them to identify things like road markings, traffic signs, other vehicles, and pedestrians. Stephen Zoepf, executive director of the Center for Automotive Research at Stanford, agrees that Intel's acquisition of Mobileye shows how critical data and machine learning are to the auto industry's future.


How NVIDIA's Neural Net Makes Decisions

#artificialintelligence

With NVIDIA PilotNet, we created a neural-network-based system that learns to steer a car by observing what people do. What makes BB8 an AI car, and showcases the power of deep learning, is the deep neural network that translates images from a forward-facing camera into steering commands. This visualization shows us that PilotNet focuses on the same things a human driver would, including lane markers, road edges and other cars. Besides PilotNet, which controls steering, cars will have networks trained and focused on specific tasks like pedestrian detection, lane detection, sign reading, collision avoidance and many more.


Dr Nathan Griffiths: Driverless cars? How the road to the future will be driven by machine learning

Robohub

Nathan is a Reader in the Department of Computer Science at the University of Warwick, whose research into the application of machine learning for autonomous vehicles (or "driverless cars") has been supported by a Royal Society University Research Fellowship. My research uses machine learning to give insights into how objects or people interact and how patterns emerge and evolve. Machine learning algorithms will examine previous behaviours and learn from these behaviours, to then predict what will happen in the future. An accurate algorithm could then be used to inform the decisions vehicles make and predict vehicle journeys and routes.


How is predictive data shaping the auto industry

#artificialintelligence

How is predictive data changing the automotive industry and what changes can we expect to see in the future? Connected and autonomous cars are going to benefit most from the inclusion of predictive data because their design centers on data collection and processing. As more and more connected cars hit the roads, data management is going to become an essential tool. Predictive data has already shown potential for preventative maintenance, but this same application could be used to predict software problems and security flaws as well.


Conversations in Machine Learning: Autonomous Vehicles for a Better World

#artificialintelligence

This is another installment of Mighty AI's "Conversations in Machine Learning" blog series. Since meeting them at June's Conference on Computer Vision and Pattern Recognition (CVPR), we've been chatting with a Corporate Research Engineer and Automated Driving Research Engineer from a behemoth of a company that's working on self-driving car technology. So autonomous vehicles require advanced computer vision, and advanced computer vision requires excellent training data--that's why Mighty AI's in the picture here. Before they came to know about Mighty AI's Training Data as a Service (TDaaS) solution and our talented tasking community, they'd never found a resource other than their own employees that could annotate images to their specifications at a meaningful velocity.


Machine learning and data are fueling a new kind of car, brought to you by Intel

#artificialintelligence

Intel's proposed $15.3 billion acquisition of Mobileye, an Israeli company that supplies carmakers with a computer-vision technology and advanced driver assistance systems, offers a chance to measure the scale of this rebuild. The company's vision systems are a simple, low-cost solution that offers surprisingly sophisticated sensing. This involves capturing images as cars drive around, and annotating them to identify things like road markings, traffic signs, other vehicles, and pedestrians. Stephen Zoepf, executive director of the Center for Automotive Research at Stanford, agrees that Intel's acquisition of Mobileye shows how critical data and machine learning are to the auto industry's future.


The most detailed maps of the world will be for cars, not humans

#artificialintelligence

Here started work building HD maps back in 2013, according to Sanjay Sood, the company's VP for highly automated driving. "Starting last year, we're essentially building the road network in order to have this map available for the first fleets of cars that are going to be leveraging this technology that are going to be showing up on the roads around 2020," said Sood. But a more scalable solution involves leveraging the embedded sensors in cars already using HD maps to navigate. "Here's adoption of our deep learning technology for their cloud-to-car mapping system will accelerate automakers' ability to deploy self-driving vehicles."