About us

Lambda Labs

Who we are

We're a team of deep learning engineers building the world's best workstations for corporations and universities.

Our workstations, servers, and cloud services power the work being done at the forefront of deep learning. Our clients include Amazon Research, Tencent, and Kaiser Permanente. MIT and Princeton count among our educational customers.

We integrate deep learning hardware plus software into a plug-and-play solution for professionals. We remove the need to research, assemble, and install optimal parts and libraries.

The Fortune 500 get their hardware from Lambda.

Helping the best conquer deep learning.

Our Story

2012

Lambda founded to help solve the difficult problem of teaching machines how to see and learn.

Facial Recognition Api

Our machine learning-powered Facial Recognition API launches.

2013

Lambda Hat

Our first foray into hardware with the Lambda Hat: A wearable camera that takes a picture every 10 seconds.

2015

Cloud Expansion

Our internal GPU cloud comes online. It powers millions of image recognition and transformation API calls a month.

2017

Workstations

Our launch of the Lambda QUAD Deep Learning GPU workstation and the Lambda Blade GPU server. The Lambda Blade becomes the world's first plug-and-play Deep Learning supercomputer for under $20,000.

the Enterprise takes notice

Lambda’s customers grow to include Apple, NVIDIA, LinkedIn, Tencent, Raytheon, Los Alamos National Labs, and many more.

GPU Cloud

Lambda launches GPU Cloud, a secure and dedicated GPU cloud service for the enterprise.

Our Vision

Lambda exists to provide the world with fast and affordable computation. We strive to optimize one metric: FLOPS / $.

With the metric of computational efficiency always in mind, Lambda helps make deep learning accessible to all. Lambda’s proudly pairs all products with 24/7 support from expert deep learning engineers. We're in the trenches with you.

That's why the greatest companies and research labs in the world work with Lambda Labs.

« With GPU acceleration, neural net training is 10-20 times faster than with CPUs. That means training is reduced from days or even weeks to just hours. »
– NVIDIA
CEO at Airbus