You’re probably already overspending on AI, using frontier models for basic tasks like summarizing or classifying text.
By running smaller, routine AI tasks - summarization, classification, etc. - on the idle compute already sitting in phones, laptops and connected devices, we were able to reduce energy demands for AI tasks by 400x compared to the same work done on a frontier model running in a data center.
More than 16,000 liters of data center cooling water saved in 48 hours.
From our edge network benchmark: 64 million AI requests on 16,932 devices, with no cooling water used.
https://t.co/rgnQUvvOnW
Turn a crawled page into labeled data on one API: an IAB category, the entities, and the topics and intent.
Built for scraping APIs, search APIs and data vendors.
https://t.co/yn9Wcn4hgy
Our mission: orchestrating the world's idle compute to accelerate AI.
ZeroGPU routes supported workloads to nearby available edge devices, putting idle compute to work closer to demand.
Try it with your workload: https://t.co/TrrVaPqshD
Introducing geo-aware, last-mile inference delivery across the ZeroGPU network.
CDNs brought content closer to users. We're doing the same for AI inference.
ZeroGPU geo-aware routing is live.
🌍 Network spanning 200,000+ devices
📍 140+ countries
⚡ 20% lower latency measured
1,900x less energy than a data center.
In our edge network benchmark, 64 million AI requests on idle devices used about 8 kWh. A data center would have used 15,353 kWh for the same requests.
https://t.co/rgnQUvvOnW
15,345 kWh less electricity than a data center would use, in 48 hours. That's more than the average home uses in a year!
From our edge network benchmark: 64 million AI requests on idle devices, about 8 kWh in total.
https://t.co/rgnQUvvOnW
Our small language model for summarization, llama-3.1-8b-instruct-fast, reads a whole call or email thread in one pass with a 128K token context window. No chunking.
Built for sales intelligence, contact centers and meeting notes.
https://t.co/Kz9FZ6f3D9
OpenAI CEO Sam Altman believes people owning RAM for their own PCs is a waste and instead should be saved for data centers
"It’s quite terrible to have everyone have a bunch of the world’s limited supply of DRAM sitting in their own computer."
OpenAI CEO Sam Altman believes people owning RAM is wasteful, and that it belongs in data centers instead.
"From a global allocation perspective, actually, it’s quite terrible to have everyone have a bunch of the world’s limited supply of DRAM sitting in their own computer."
@kshav73 Sam Altman wants everything in the cloud. But your PC's RAM is already paid for and mostly sits idle. That's why we pay people to put their idle compute to work instead!
@MTSlive OpenAI wants everything in the cloud. But a lot of the compute AI needs is already sitting idle in people's devices. That's why we pay the owners to put it to work. https://t.co/855dMH0Cn2
@CultureCrave ChatGPT wants the compute in the cloud. But there's already a ton of idle compute in laptops, desktops and phones that's built and paid for. That's why we pay device owners to run AI on it.
@WindowsCentral OpenAI wants everything in the cloud. But a lot of the compute AI needs is already sitting idle in people's devices. That's why we pay the owners to put it to work.
@VideoCardz Sam Altman wants the compute in the cloud. But there's already a ton of idle compute in laptops, desktops and phones that's built and paid for. That's why we pay device owners to run AI on it. https://t.co/855dMH0Cn2