Welcome to the TensorDock Blog!
Co-authored by everyone on our team, you might find some cool insights on here :)
Still, everyone speaks for themselves, so their opinions and statements do not reflect that of the company. Find official company information on our documentation website.
Orchestrate generative AI workloads using dstack on TensorDock
We're excited to announce that we're now supported by dstack, an open-source platform aimed at streamlining generative AI workload orchestration. Together, dstack and TensorDock are committed to drive the development and adoption...
TensorDock: Investing in a better future
As a startup, we have to make bets. We invest in our product, in new initiatives, and most importantly, our people. I'm excited to report back on some of our latest bets....
TensorDock Enters The Rap Industry
In order to break new barriers with TensorDock, our outreach team looked to a new industry, relatively unknown to most tech companies. We are proud to announce the first TensorDock rap, highlighting...
airgpu meets TensorDock
Sven started airgpu because GPU prices were getting pretty insane for people who just wanted to play their games. Sven first looked into AWS, Amazon Web Services, which have GPU services available...
We are live!
After exactly seven months in beta, on Thursday, we finally launched TensorDock Core Cloud! Launching a product is a sacred thing, so in this blog post, I explore where we started and...
TensorDock joins NVIDIA Inception
TensorDock, a cloud services provider built for easy high-performance computing deployments, today announced it has joined, a program designed to nurture startups revolutionizing industries with technological advancements.
Subscription Orders are Live!
Subscription servers are servers that are rented for a longer period of time (e.g. a month) than a typical hourly server. Already, you can order TensorDock subscription servers in 11 locations, with...
I'm Jonathan Lei, and I work at TensorDock. A blog can serve as a place for employees to make announcements and reflect on their experiences. For TensorDock, I want to make this...