Researchers from NVIDIA and Aalto University have released StyleGAN3, removing a major flaw of current generative models and opening up new possibilities for their use in video and animation.
This curriculum provides an overview of free online resources for learning about deep learning. It includes courses, books, and even important people to follow.
Visualizing your training data is the foundation of every successful deep learning project. It’s important to both identify potential flaws in the ground truth labels, and to look for insights that will guide your choice of model architecture.
This post discusses the Total Cost of Ownership (TCO) for a variety of Lambda A100 servers and clusters. We calculate the TCO for individual Hyperplane-A100 servers, compare the cost with renting a AWS p4d.24xlarge instance, and walk through the cost of building and operating A100 clusters.
Instructions for getting TensorFlow and PyTorch running on NVIDIA's GeForce RTX 30 Series GPUs (Ampere), including RTX 3090, RTX 3080, and RTX 3070.
PyTorch benchmarks of the RTX A6000 and RTX 3090 for convnets and language models - both 32-bit and mix precision performance.
This tutorial shows you how to install Docker with GPU support on Ubuntu Linux. To get GPU passthrough to work, you'll need docker, nvidia-container-toolkit, Lambda Stack, and a docker image with a GPU accelerated library.
Lambda secured $24.5M in financing, including a $15M Series A equity round and a $9.5M debt facility that will allow for the growth of Lambda GPU Cloud and the expansion of Lambda's on-prem AI infrastructure software products. Read more details in the post.
Lambda Labs today announced it has been selected as the 2020 NVIDIA Partner Network (NPN) Solution Integration Provider of the Year. Lambda is a leading provider of AI-optimized hardware infrastructure to F500 enterprises, startups, and government entities.
We’re excited to announce today that Lambda GPU Cloud is the first public cloud to offer instances with 2x & 4x RTX A6000 GPUs.
PyTorch & TensorFlow benchmarks of the Tesla A100 and V100 for convnets and language models - both both 32-bit and mix precision performance.
PyTorch and TensorFlow training speeds on models like ResNet-50, SSD, and Tacotron 2. Compare performance of the RTX 3090, 3080, A100, V100, and A6000.
1, 2, or 4 NVIDIA® Quadro RTX™ 6000 GPUs on Lambda Cloud are a cost effective way of scaling your machine learning infrastructure. With the new RTX 6000 instances you can expect: a lower initial price of $1.25 / hr, 2x the performance per dollar vs a p3.8xlarge, and up-to-date drivers & frameworks.
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