@DreamscaleLabs (YC F26) is the first inference provider to serve NVIDIA’s DreamZero robot model over the cloud!
And we beat @nvidia's own reported inference speed by 8%, with just half the silicon.
DreamZero is a model that pioneered the new wave of “World Action Models” that has taken over generalist robotics today. It promises to generalize better to new tasks, learn physics from human video, and transfer well to new embodiments.
Normally, DreamZero requires 2x GB200 superchips (each costing $60K) or is painfully slow (waits 5.7s before moving 1.6s), which made it infeasible to deploy to robots in practice.
Now, with Dreamscale’s real-time cloud inference infrastructure, we’ve demonstrated fast, smooth motion on actual robots with sub-second latency.
As scaling laws become more relevant in robotics, frontier physical AI models are growing more computationally expensive than ever. With Dreamscale, we are finally making World Action Models (WAMs) accessible to startups and robot developers across the world.
Reach out if you are interested in cloud robot inference.
Robot brains can (and should) live in the cloud 🐑 ⚡
OpenAI's Astra showed us truely competent spatial reasoning arises out of enormous scale and data.
Skyrocketing dram costs, onboard energy limits and most painfully the need for generality afforded only by scaling are forcing us off board onto datacenter grade compute.
So we're now announcing @DreamscaleLabs , an applied research company engineering this future into a possible reality, gutting the latency and amping up the reliability necessary for safe remote operation.
Onwards to Physical AGI 🚀
@pentestduck@KDog112358@eternaI_entropy
Today we're incredibly excited to announce @DreamscaleLabs (YC F26)! We're an applied research company putting robot brains in the cloud.
Robot AI models are growing larger and on-board compute is getting increasingly inaccessible due to cost. We're taking a contrarian bet that the future is moving inference off the robot and into the cloud, while still meeting real-time deadlines required by robot motion.
We're building the real-time inference infrastructure that enables frontier physical AI models to run smoothly on your robot. We optimize for low latency across the full stack: from the model, down to the GPU kernels, and over the network.
Our mission is to unlock a future of safe and intelligent robots doing meaningful work, and we think this is only possible by letting you deploy and run robot models in the cloud.
Reach out to us at [email protected] or visit our website at https://t.co/AFAJApNM2H to learn more.
@KDog112358@AntoineNeedGPUs@eternaI_entropy