New laptop offers the industry’s most powerful mobile workstation for deep learning, enabling ML engineers to immediately focus on achieving breakthroughs in AI/ML anytime, anywhere
Lambda, the Deep Learning Company, in collaboration with Razer, released the new Lambda Tensorbook, the world’s most powerful laptop designed for deep learning, available with Linux and Lambda’s deep learning software. The sleek laptop, coupled with the Lambda GPU Cloud, gives engineers all the software tools and compute performance they need to create, train, and test deep learning models locally.
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Since its launch in 2012, Lambda has quickly become the de-facto deep learning infrastructure provider for the world’s leading research and engineering teams. Thousands of businesses and organizations use Lambda including: all of the top five tech companies, 97 percent of the top research universities in the U.S. including MIT and Caltech, and the Department of Defense. These teams use Lambda’s GPU clusters, servers, workstations, and cloud instances to train neural networks for cancer detection, autonomous aircraft, drug discovery, self-driving cars, and much more.
“Most ML engineers don’t have a dedicated GPU laptop, which forces them to use shared resources on a remote machine, slowing down their development cycle.” said Stephen Balaban, co-founder and CEO of Lambda. “When you’re stuck SSHing into a remote server, you don’t have any of your local data or code and even have a hard time demoing your model to colleagues. The Razer x Lambda Tensorbook solves this. It’s pre-installed with PyTorch and TensorFlow and lets you quickly train and demo your models: all from a local GUI interface. No more SSH!”
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An All-in-One Deep Learning Solution
The new Tensorbook comes pre-configured with a complete software environment from Lambda, including Ubuntu Linux with the Lambda Stack for training large workloads anytime, anywhere. The laptop features sleek, high-performance hardware from Razer, powered by NVIDIA RTX 3080, one of the most powerful mobile GPUs available for dedicated, uninterrupted compute at a moment’s notice and full compatibility with TensorFlow, PyTorch, cuDNN, CUDA, and other ML frameworks and tools.
“Razer’s experience in developing high performance products for both gamers and creators has been a crucial building block for the Lambda Tensorbook, a deep learning system for engineers,” said Travis Furst, Head of Razer’s Laptop Division. “The shared customer obsession is what drove us to collaborate with Lambda in developing this powerful, specialized device. We can’t wait to see the amazing breakthroughs that will be made by engineers and researchers while using a Tensorbook.”
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