NVIDIA CES 2016 Press Conference
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The document presents an overview of NVIDIA's advancements in self-driving technology, highlighting the capabilities of the NVIDIA Drive PX 2, which features a supercomputer with deep learning capabilities for autonomous vehicles. It emphasizes the importance of deep learning in improving the perception and decision-making processes for self-driving cars, showcasing various partnerships and achievements from companies like Audi, BMW, and Ford. The narrative outlines the challenges of autonomous driving and the role of NVIDIA's technology in driving the self-driving revolution forward.
![20
Image from ZMP
[Sahin]
“Deep learning technology can
dramatically improve accuracy
of detection and decision-
making algorithms for
autonomous driving. ZMP is
achieving remarkable results
using deep neural networks on
NVIDIA GPUs for pedestrian
detection. We will expand our
use of deep learning on NVIDIA
GPUs to realize our driverless
Robot Taxi service.”
Hisashi Taniguchi
CEO, ZMP Inc.](https://image.slidesharecdn.com/nvidiaces2016pressevent-160105191744/85/NVIDIA-CES-2016-Press-Conference-20-320.jpg)
NVIDIA CES 2016 Press Conference
- 1. Jen-Hsun Huang, Co-Founder & CEO, NVIDIA | Jan. 4, 2016 ACCELERATING THE RACE TO SELF-DRIVING CARS
- 2. 2 SELF-DRIVING IS A MAJOR COMPUTER SCIENCE CHALLENGE SOFTWARE SUPERCOMPUTER DEEP LEARNING
- 3. 3 NVIDIA DRIVE PX 2 12 CPU cores | Pascal GPU | 8 TFLOPS | 24 DL TOPS | 16nm FF | 250W | Liquid Cooled World’s First AI Supercomputer for Self-Driving Cars
- 4. 4 THE SELF-DRIVING REVOLUTION Safer Driving New Mobility Services Urban Redesign
- 6. 6 LOCALIZE MAP THE BASIC SELF-DRIVING LOOP CONTROLSENSE PLAN PERCEIVE
- 7. 7 SELF-DRIVING IS HARD The world is complex The world is unpredictable The world is hazardous
- 8. 8 DEEP LEARNING TO THE RESCUE “The GPU is the workhorse of modern A.I.” DNN GPUBIG DATA
- 9. 9 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 2009 2010 2011 2012 2013 2014 2015 2016 THE AI RACE IS ON IBM Watson Achieves Breakthrough in Natural Language Processing Facebook Launches Big Sur Baidu Deep Speech 2 Beats Humans Google Launches TensorFlow Microsoft & U. Science & Tech, China Beat Humans on IQ Toyota Invests $1B in AI Labs IMAGENET Accuracy Rate Traditional CV Deep Learning
- 10. 10 EDUCATION START-UPS CNTKTENSORFLOW DL4J THE ENGINE OF MODERN AI NVIDIA GPU PLATFORM *U. Washington, CMU, Stanford, TuSimple, NYU, Microsoft, U. Alberta, MIT, NYU Shanghai VITRUVIAN SCHULTS LABORATORIES TORCH THEANO CAFFE MATCONVNET PURINEMOCHA.JL MINERVA MXNET* CHAINER BIG SUR WATSON OPENDEEPKERAS
- 11. 11 DEEP LEARNING EVERYWHERE NVIDIA Titan X NVIDIA Jetson NVIDIA Tesla NVIDIA DRIVE PX
- 12. 12 END-TO-END DEEP LEARNING PLATFORM FOR SELF-DRIVING CARS DNN TRAINING PLATFORM IN-CAR AI SUPERCOMPUTER DEEP NEURAL NETWORK
- 13. 13 39% 55% 72% 88% 30% 40% 50% 60% 70% 80% 90% 100% 7/2015 8/2015 9/2015 10/2015 11/2015 12/2015 Top Score 9 inception layers 3 convolutional layers 37M neurons 40B operations Single and multi-class detection Segmentation KITTI Dataset: Object Detection NVIDIA DRIVENet
- 14. 14KITTI dataset
- 15. 15Courtesy of Cityscapes dataset project
- 16. 16Courtesy of Cityscapes dataset project
- 18. 18 “Using NVIDIA DIGITS deep learning platform, in less than four hours we achieved over 96% accuracy using Ruhr University Bochum’s traffic sign database. While others invested years of development to achieve similar levels of perception with classical computer vision algorithms, we have been able to do it at the speed of light.” Matthias Rudolph, Director of Architecture, Driver Assistance Systems, Audi
- 19. 19 “Due to deep learning, we brought the vehicle’s environment perception a significant step closer to human performance and exceeded the performance of classic computer vision.” Ralf G. Herrtwich Director of Vehicle Automation, Daimler
- 20. 20 Image from ZMP [Sahin] “Deep learning technology can dramatically improve accuracy of detection and decision- making algorithms for autonomous driving. ZMP is achieving remarkable results using deep neural networks on NVIDIA GPUs for pedestrian detection. We will expand our use of deep learning on NVIDIA GPUs to realize our driverless Robot Taxi service.” Hisashi Taniguchi CEO, ZMP Inc.
- 21. 21 “BMW is exploring the use of deep learning for a wide range of automotive use cases, from autonomous driving to quality inspection in manufacturing. The ability to rapidly train deep neural networks on vast amounts of data is critical. Using an NVIDIA GPU cluster with NVIDIA DIGITS, we are achieving excellent results.” Uwe Higgen Head of BMW Group Technology Office (USA)
- 22. 22 “With the NVIDIA deep learning platform, we have greatly improved performance on a variety of image recognition applications for cars, surveillance cameras and robotics. The remarkable thing is that we did it all with a single NVIDIA GPU-powered deep neural network, in a very short time.” Daisuke Okanohara Founder & SVP, Preferred Networks Distributed Cooperative Deep Learning
- 23. 23 “Deep learning on NVIDIA DIGITS has allowed for a 30x enhancement in training pedestrian detection algorithms, which are being further tested and developed as we move them onto the NVIDIA DRIVE PX.” Dragos Maciuca, Technical Director, Ford Research and Innovation Center
- 24. 24 MANY THINGS TO LEARN
- 25. 25 END-TO-END DEEP LEARNING PLATFORM FOR SELF-DRIVING CARS NVIDIA DRIVE PX 2NVIDIA DIGITS NVIDIA DRIVENET Localization Planning Visualization Perception DRIVEWORKS
- 26. 26
- 27. 27
- 28. 28 NVIDIA DRIVE PX 2 TITAN X DRIVE PX 2 Process 28nm 16nm FinFET CPU — 12 CPU cores 8-core A57 + 4-core Denver GPU Maxwell Pascal TFLOPS 7 8 DL TOPS 7 24 AlexNet 450 images / sec 2,800 images / sec
- 29. 29 150 MACBOOK PROS IN YOUR TRUNK 6 TITAN X = 42 TFLOPS, Core i7 = 280 GFLOPS, 42 / 0.28 = 150 MacBook Pros
- 30. 30 2 NEXT-GEN TEGRA PROCESSORS
- 31. 31 2 NEXT-GEN PASCAL GPUS
- 32. 32 LIQUID COOLING 250W | Operation up to 80C (175F) ambient | 256 cubic inches
- 33. 33 NVIDIA DRIVE PX 2
- 34. 34 NVIDIA’s Deep Learning Car Computer Selected by Volvo on Journey Towards a Crash-Free Future
- 35. 35 NVIDIA DRIVE PX SELF-DRIVING CAR PLATFORM NVIDIA DRIVE PX 2NVIDIA DIGITS NVIDIA DRIVENET Localization Planning Visualization Perception DRIVEWORKS