Lambda Labs - Tensorbook

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TensorBook is a powerful laptop for Deep Learning. If you want the power of an NVIDIA GPU and the productivity of a portable system, the TensorBook is for you.

TENSORBOOK Accelerate your training a system optimized for Deep Learning; pre-installed with TensorFlow, PyTorch, Caffe, and more. A portable A.I. notebook with a powerful GPU. Simply best laptop for Deep Learning. The TensorBook is optimized for running TensorFlow training jobs with its powerful Pascal GTX 1070 GPU. SPECIFICATIONS • GPU = GTX 1070 8 GB vRAM. Pascal architecture • PROCESSOR = Intel i7 Intel Core™ i7-8750H, 6 Core @ 2.2 GHz • RAM = 16 GBDDR4 2400 MHz • STORAGE = 512GB SSD PERFORMANCE PROFILE The TensorBook is the world's only laptop for Deep Learning. You'll be training up to 50x faster than your current system with the TensorBook's powerful 8 GB GTX 1070 GPU. This unit is everything you need in a portable Machine Learning laptop. BUILT BY RESEARCHERS We build deep learning machines for researchers and corporations. Our salespeople are engineers. When you chat with us, there's no sales talk. We're a small team of experts who take pride in our machines.

Learn more at lambdal.com


2 Comments
  • Hendrick, Aug 03, 2018

    where can i buy this product in taiwan ?

  • Larry Kirschner, Apr 10, 2019

    I have the tensorbook and I don't recommend it. What I expected was a well designed system that would save me the time of installing and maintaining linux, and I was willing to pay a little bit of a premium to save the time. The problem/realities are these: 1) a lot of the supposed value proposition is that tensorflow/pytorch etc come already installed. I never use the host-installed versions of these things, I'm always in practice using a conda env or docker 2) It can't drive a second display. I tried connecting with both HDMI and minidisplay. I went to Best Buy and tried like 10 different monitors. I went as far as contacting their support and they were not particularly helpful. 3) You can't connect an eGPU because its usbc ports lack thunderbolt support. Sure, the laptop has a built in gpu, but I have use cases where I need 2 gpus--specifically, I'm working on an app that requires two docker containers/microservices and each needs its own gpu. I understand that "most users just use the single gpu that comes in the laptop," as I was told by lambda support, but why would you sell a super-premium machine-learning $4000 laptop in 2018/2019 and not include thunderbolt/make it impossible to connect an egpu?

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About The Company
Lambda Labs
  • Hardware & IoT
  • 3 Products
  • 0 Case Studies

GPU Workstations and Servers for Deep Learning.

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