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NVIDIA unveils platform for fully autonomous cars

Daily Mail

The Pegasus line will be available by the middle of 2018 for automakers to begin developing vehicles and testing software algorithms needed to control future driverless cars, NVIDIA executives told a developers' conference in Munich on Tuesday. The deal between Deutsche Post, ZF and NVIDIA will include future Deutsche Post StreetScooter delivery trucks. In Munich, the three partners are showcasing a prototype StreetScooter running NVIDIA Drive PX chips used to control sensors including six cameras, one radar and one lidar, or 3D laser camera. De Ambroggi said NVIDIA's Pegasus automotive platform was the first with the processing power for automakers to begin developing truly autonomous vehicles, which could be upgraded with software improvements ahead of actual roadway deployments.


Installing Nvidia, Cuda, CuDNN, TensorFlow and Keras

@machinelearnbot

In this post I will outline how to install the drivers and packages needed to get up and running with TensorFlow's deep learning framework. To start, install Ubuntu 14.04 Server. Download the Cuda 7.5 library run file, using wget and install the driver, the toolkit, and samples. CuDNN is a library that helps accelerate deep learning frameworks, such as TensorFlow or Theano.


Nvidia and the GPU: contribution to the AI world of self-driving cars

#artificialintelligence

In other words, GPU delivers better prediction accuracy, faster results, smaller footprint, lower power and lower costs. What is fascinating about Nvidia is that it has a full stack solution architecture for DL applications, making it easier and faster for data scientist engineers to deploy their programs. As part of a complete software stack for autonomous driving, NVIDIA created a neural-network-based system, known as PilotNet, which outputs steering angles given images of the road ahead. In addition to learning the obvious features such as lane markings, edges of roads, and other cars, PilotNet learns more subtle features that would be hard to anticipate and program by engineers, for example, bushes lining the edge of the road and atypical vehicle classes (Source:Cornell university CS department).


The Audi A8: the World's First Production Car to Achieve Level 3 Autonomy

#artificialintelligence

The 2018 Audi A8, just unveiled in Barcelona, counts as the world's first production car to offer Level 3 autonomy. Here that involves driving no faster than 60 kilometers per hour (37 mph), which is why Audi calls the feature AI Traffic Jam Pilot. When the car up ahead stops, the A8's AI hits the brakes in time to avoid rear-ending it. Audi said in a statement that it will follow "a step-by-step approach" to introducing the traffic jam pilot.


Faster machine learning is coming to the Linux kernel

#artificialintelligence

It's been a long time in the works, but a memory management feature intended to give machine learning or other GPU-powered applications a major performance boost is close to making it into one of the next revisions of the kernel. As Red Hat developer Jérôme Glisse explains, this makes it easier for hardware devices like GPUs to directly access the memory of a process without the extra overhead of copying anything. These kinds of speed-ups for CUDA, Nvidia's library for GPU-based processing, would only benefit operations on Nvidia GPUs, but those GPUs currently constitute the vast majority of the hardware used to accelerate number crunching. The third obstacle is hardware support, since HMM requires the presence of a replayable page faults hardware feature to work.


5 New Self Driving Car Companies - Nanalyze

#artificialintelligence

The notion of cars that drive themselves is one that becomes more and more real with each passing day. Acquisitions seem to be happening left and right, and almost every major auto manufacturer is devoting resources to bring us a self driving car. Companies like Google, Uber, and Tesla are all devoting significant investments to the self driving car with the universal target date of "2020" for commercialization being forecasted by nearly all of these players. Mobileye, about the only pure-play self driving car stock out there, recently announced a partnership with Delphi and a target date of 2019. While all eyes remain fixed on the big names in this game, there are some new entrants to this space that you may never heard of but that are getting closer and closer to making the self driving car a reality.


Bosch and Nvidia create an AI supercomputer for self-driving tech

#artificialintelligence

The AI onboard computer is expected to guide self-driving cars through even complex traffic situations, or ones that are new to the car. "Automated driving makes roads safer, and artificial intelligence is the key to making that happen. Driverless cars to be part of everyday life in the next decade Bosch's AI onboard computer can recognize pedestrians or cyclists. As a result, a self-driving car with AI can recognize and assess complex traffic situations, such as when an oncoming vehicle executes a turn, and factor these into its own driving.


NVIDIA Working with PACCAR on Self-Driving Trucks

#artificialintelligence

The collaboration was shared by NVIDIA Founder and CEO Jen-Hsun Huang during his keynote at the Bosch Connected World conference in Berlin. Separately, he provided details of NVIDIA's partnership with Bosch, the world's largest automotive supplier, on self-driving car technology. "This is probably the largest single mass of a product that we've helped make," said Huang, addressing a crowd of more than 2,000 executives, developers and others attending the event. PACCAR CEO Ron Armstrong, said separately, "PACCAR is exploring automated driving systems and we are excited about what our collaboration on artificial intelligence with NVIDIA has delivered so far." PACCAR – which manufactures the Kenworth, Peterbilt and DAF lines of trucks – has developed a proof-of-concept self-driving truck with SAE Level 4 capability built on NVIDIA DRIVE PX 2 technology, trained on deep neural networks.


Flipboard on Flipboard

#artificialintelligence

The AI onboard computer is expected to guide self-driving cars through even complex traffic situations, or ones that are new to the car. "Automated driving makes roads safer, and artificial intelligence is the key to making that happen. Driverless cars to be part of everyday life in the next decade Bosch's AI onboard computer can recognize pedestrians or cyclists. As a result, a self-driving car with AI can recognize and assess complex traffic situations, such as when an oncoming vehicle executes a turn, and factor these into its own driving.


Building Your Own Deep Learning Box

#artificialintelligence

After completing Part 1 of Jeremy Howard's awesome deep learning course, I took a look at my AWS bill and found I was spending nearly $200/month running GPUs. It's not necessary to spend that much to complete his course, but I started working on a few extracurricular datasets in parallel and I was eager to get results. After talking with fellow students and reading a number of blog posts, I decided to try building my own box. Technology and hardware change so rapidly that I'm afraid much of post will become outdated soon, but I hope my general approach will still be useful for at least a little while. I started by reading a bunch of blogs to get the current consensus on which parts to buy.