Published
U.C. Berkeley Ph.D. Student Researcher Evan Shelhamer describes what GPU acceleration with cuDNN, a new NVIDIA software offering that makes it easier for deep learning practitioners to advance their work, brings to Caffe, one of the world’s most popular and actively developed deep learning frameworks.
- Category
- Computing
Sign in or sign up to post comments.
Be the first to comment
Up Next
-
01:56
Industrial AI Enabled by Deep Learning with Baker Hughes and NVIDIA
-
1:08:46
NVIDIA Deep Learning Course: Class #1 – Introduction to Deep Learning
-
00:40
Deep Learning online course
-
00:47
What is AI, ML, and Deep Learning?
-
01:39
Research at NVIDIA: Improving Landmark Localization with a New Deep Learning Architecture
-
38:30
[SAIF 2019] Day2: Geometric Deep Learning for Forecasting and Semi-supervised Learning - Joan Bruna
-
03:25
Wide & Deep Learning with TensorFlow - Machine Learning
-
08:43
A Deep Look Into The INSANE Software That Runs Starlink
-
01:25
NVIDIA Vid2Vid Cameo Mission AI Possible: NVIDIA Researchers Stealing the Show
-
00:27
AI and Deep Learning at GTC 2017
-
06:29
GTC 2016: NVIDIA DGX-1, World's First Deep Learning Supercomputer (part 7)
-
16:06
GTC 2015: NVIDIA DRIVE PX Self-Driving Car Computer and Deep Learning (part 8)
-
02:36
The Deep Learning Revolution
-
10:02
NVIDIA CES 2015 press conference: Deep Learning (part 6)
-
02:18
Deep Learning Breakthroughs in Autonomous Driving with UC Berkeley
-
2:07:54
GTC Taiwan: AI, Deep Learning with NVIDIA CEO Jen-Hsun Huang
-
11:14
Artificial Intelligence, Machine Learning, and Deep Learning
-
02:35
NVIDIA DRIVE Sim Software Built on NVIDIA Omniverse
-
01:46
The Unprecedented Performance of NVIDIA’s DGX-1 for Deep Learning
-
01:31
MILABOT, a Deep Learning Chatbot by the Montreal Institute for Learning Algorithms
-
01:34
Accelerating Deep Learning Research with NVIDIA DGX Station A100
-
02:35
UC Berkeley Building Smarter Everyday Robots with Deep Learning
Loading...