Another one this week: NYSE celebrated Fluidstack's $830M Series A confirmation with a Trading Floor Takeover. Thank you @NYSE.
We're hiring across all departments: https://t.co/gW777NE8ka
A nice moment for the team this week: @nasdaq featured Fluidstack’s $830M Series A on their Times Square tower.
We’re hiring across all departments: https://t.co/gW777NE8ka
A nice moment for the team this week: @nasdaq featured Fluidstack’s $830M Series A on their Times Square tower.
We’re hiring across all departments: https://t.co/gW777NE8ka
In January, Fluidstack raised an $830M Series A at a $7.5B valuation, led by Situational Awareness, with participation from world-leading investors.
Fluidstack builds infrastructure for the leading AI labs - our goal is to be the fastest on the planet at deploying hundreds of gigawatts of compute.
As we stand at the event horizon of the singularity, humanity’s best chance is if democracies, with error correcting institutions, free speech, and checks on power, imbue those same principles into superintelligence. Whoever deploys frontier compute infrastructure fastest will decide whether Al expands human freedom or shrinks it.
We are hiring - come join us.
In January, Fluidstack raised an $830M Series A at a $7.5B valuation, led by Situational Awareness, with participation from world-leading investors.
Fluidstack builds infrastructure for the leading AI labs - our goal is to be the fastest on the planet at deploying hundreds of gigawatts of compute.
As we stand at the event horizon of the singularity, humanity’s best chance is if democracies, with error correcting institutions, free speech, and checks on power, imbue those same principles into superintelligence. Whoever deploys frontier compute infrastructure fastest will decide whether Al expands human freedom or shrinks it.
We are hiring - come join us.
hosting an @fluidstack event with @asciimike and @ArjChi on tuesday 7/19 in SF.
the decade ahead: a dinner on the future of AI infrastructure
we build supercomputers for the world’s leading AI labs. the steel, the electrons, and the silicon. @AnthropicAI chose us to lead their $50B compute buildout, and our job is to deliver it fast: datacenters the size of central park, printed in months.
building at this pace takes everyone. construction leads, electricians, software engineers, operators, dealmakers. there’s a seat for all of them at this table.
come to dinner. we’re hiring across every department and this beats any job portal.
space is limited, apply below
https://t.co/gHhT4F1nhN
@chrisbarber strong list, a lot of great companies
I will say fluidstack is the smartest group of people ive ever worked with and it's not even close. talent density here is absurd
Our latest hackathon winner: RackScout, an AR copilot for the data hall. Put on the headset and the hall annotates itself - a glowing path to the rack you need, checklists pinned to the hardware, racks turning green as they go production-ready.
the hardest problems in AI right now arent in the model. they are in the gigawatts.
@fluidstack is hiring across the board — production, software, product, controls, PMs, and more
if you want to build the infrastructure behind frontier AI, DM me here or on linkedin
https://t.co/VFQCbUyasj
TeraWulf Announces Anthropic Lease at Justified Data Campus and Sale of Majority Interest in Abernathy Joint Venture to Fluidstack 🚀
https://t.co/m9XL9yMv5R
Selling compute capacity has become an entirely new business line for many companies
We see that @Meta has declared they're going to sell their compute capacity, allow customers to use models on their platform, and charge per token.
We have @awscloud@Azure@googlecloud@OracleCloud selling a variety of GPU compute, with #awsbedrock offering a bring your own model approach.
We also have the #neocloud @CoreWeave@crusoe@fluidstack@nebiusai@nscale who are building out and selling compute capacity.
The most important thing to notice is that, is that there is competition in the market place. Customers will have options. Innovation will push all the players to become more energy efficient, work with multiple chip manufacturers like @Broadcom, @nvidia, @AMD, and custom silicon like @amazon Trainium and @Google TPUs.