CES 2018 Autonomous Driving Tech Review
At CES 2018, 555 companies or organizations participated in the “Automotive/Vehicle Technology” category, 23% of which were companies using autonomous driving technologies.
AI Technology & Industry Review
At CES 2018, 555 companies or organizations participated in the “Automotive/Vehicle Technology” category, 23% of which were companies using autonomous driving technologies.
China is undergoing a revolutionary transformation as AI rapidly penetrates industries from transportation to communication — a growth rate phenomenon that Baidu Group President & COO Qi Lu calls “China speed.”
At Synced we are naturally fans of machine intelligence, but we also realize some new techniques struggle to perform their tasks effectively, often blundering in ways that humans would not.
The conference was held November 17-19th, and attracted research scientists, industry influencers, venture investors, and entrepreneurs from the Greater Boston Area.
The objective of Voyage’s self-driving vehicles is to deliver fully functional autonomous taxis within five years.
The global market for this versatile, high-precision, long-distance measuring “eye” will reach US$36 billion in 2030.
Jianxiong Xiao (肖健雄), founder of startup AutoX, developed his first self-driving car in six months with seven cameras costing a total of just US$500.
Autonomous wheelchair developed by researchers at MIT and in Singapore promises improved independence for the disabled Abstract After building self-drivingContinue Reading
In this report, we will touch on some of the recent technologies, trends and studies on deep neural network inference acceleration and continuous training in the context of production systems.
Andrew Ng, one of the top minds in deep learning, loves teaching. And so, the Stanford University professor decided toContinue Reading
Apple is confused about what its next big thing will be.
One crucial standard in measuring autonomous vehicles is whether the autonomous vehicles can go through intersections with no signals. In this paper, the authors provide us with a new strategy of using Deep Reinforcement Learning.
A practical way to make an autonomous vehicle is not by programming a car to drive in any environment, but by showing the car how to drive and make the car learn by itself. NVIDIA created a system of this kind, named PilotNet.
In a tech talk at University of Toronto, NVIDIA shared some updates regarding their research of self-driving car and End-to-End Learning