获奖名单
用户 | 昵称 | 联系方式 |
1 | 樊海荣 | 186XXXX0832 |
2 | 孙磊 | 137XXXX9746 |
3 | 张传雷 | 138XXXX6837 |
4 | 万辉 | 139XXXX1827 |
5 | 曾春辉 | 137XXXX5960 |
6 | L | 182XXXX6962 |
7 | 陈一新 | 186XXXX2886 |
8 | 陈先生 | 158XXXX0273 |
9 | 聂九辉 | 138XXXX7172 |
10 | 曹学鹏 | 136XXXX5782 |
11 | 焦盼冬 | 134XXXX4495 |
12 | 邱小勇 | 159XXXX8267 |
13 | 张勇 | 137XXXX5856 |
14 | 杨世熙 | 185XXXX6381 |
15 | 胡仡 | 158XXXX1080 |
16 | 陈予力 | 151XXXX8117 |
17 | 翁泽钦 | 173XXXX0270 |
18 | Shen Jianming | 135XXXX8955 |
19 | Mr. Cai | 137XXXX0996 |
20 | Pang Yunhe | 136XXXX9069 |
21 | Zhao Weidong | 138XXXX6974 |
► Wonderful content review
The theme of this live class is "NVIDIA Technology Creates the Road to Intelligent Driving in the Future". Now, please review the highlights of this live broadcast with Xiaoli.
► Wonderful Q&A
Q1
NVIDIA Is technology mainly used in the automotive field?
NVIDIA is a company that uses GPU or parallel computing to accelerate workloads in various fields. In the automotive field, using end-to-end technology, NVIDIA can provide everything from autonomous driving model training (conducted in the data center) to model application and vehicle end, such as vehicle-mounted chips and the upper-layer software stack of the vehicle-mounted chips. Therefore, NVIDIA's technology is not only used in the automotive field.
Q2
In what aspects does NVIDIA's DRIVE Sim perform autonomous driving simulation?
is first based on simulation of physical properties to create a safe, scalable and cost-effective autonomous driving simulation platform. The second is to rely on Omniverse to realize real-time rendering of in . The third is the generation of synthetic data for autonomous driving. Data from cameras, radar , lidar and even ultrasound are generated on Omniverse's DRIVE Sim platform to generate simulation data to assist in further training of the perception network for autonomous driving. Is there any solution for the
Q3
V2I scenario? There are many solutions related to
. V2I technology is currently mainly used in communication collaboration between vehicles and roads. For example, today's road infrastructure will be equipped with NVIDIA Jetson series products. In addition, some X86 architecture products will also be used, using NVIDIA RTX GPUs to do some front-end inference calculations. . In addition, we will also use the EGX solution, which uses the X86 architecture and high-end computing cards, such as NVIDIA A100 Tensor Core GPU or NVIDIA A30 GPU, to communicate with the data center through the external network for data exchange. There are corresponding solutions for V2I scenarios both at the edge and at the data center.
