Lambda partnered with Razer to release Tensorbook, the world’s most powerful Linux-based laptop designed for deep learning. When paired with the Lambda GPU Cloud, engineers will have all the software tools and compute performance at their disposal to create, train, as well as test deep learning models locally. Currently, thousands of businesses and organizations use Lambda, including the top five tech companies, 97% of the top research universities in the U.S. (MIT, Caltech, etc.), and the Department of Defense.
The 4.4-pound laptop features a 15.6-inch (2560 x 1440) 165Hz refresh rate display, an Intel i7-11800 processor (8 cores, 2.3GHz to 4.6GHz), 64GB of DDR4 memory, an NVIDIA RTX 3080 Max-Q GPU with 16GB VRAM, 2TB of SSD storage, 1080p webcam, and Thunderbolt 4 / USB 3.2 / HDMI 2.1 ports. Unfortunately, it also comes with a hefty price tag, which starts a $3,499.99 USD.
- Powerhouse performance from AMD Ryzen 5 5500U mobile processor, 8GB DDR4 RAM, 256GB SSD storage, and AMD Radeon 7 Graphics
- The IdeaPad 3 14-inch laptop has 4-side narrow bezels that let you see more of the FHD (1920 x 1080) screen for wider viewing angles and less clutter
- Quieter and cooler with intelligent thermals, plus you can calibrate performance with Q-control, with 3 modes to match your performance needs
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. 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!,” said Stephen Balaban, co-founder and CEO of Lambda.
