Positron AI

We’ve spent enough late nights fighting bloated GPUs to know something had to change. GPUs were a great starting point—but the chronic Nvidia shortages, massive power draw, and memory bottlenecks were killing our ability to deploy transformer models effectively at scale. We got…

I’m sure you know that GPUs often have famously poor memory bandwidth utilization for AI (in the order of 30%); with hardware optimization, it is perfectly possible to utilize more of that bandwidth than GPUs can/do (see: @positron_ai) (7/x)

Deploy your trained models instantly—zero rewrites. GPUs lock you into their ecosystem, forcing complex integrations, endless compiler headaches, and frustrating delays. We built Positron Atlas differently: zero rewrites, zero friction. Upload your Nvidia-trained Hugging Face…

Even the best-trained model fails if the deployment stack can’t keep up.  Most companies treat inference as an afterthought. They spend millions optimizing for training, then try to retrofit that same infrastructure to run real-world workloads, only to watch performance degrade…

The demand for inference is skyrocketing. That's why we focused on maximizing inference performance and designing the best memory bandwidth utilization ratio solution. Positron Atlas: the best AI accelerator designed exclusively and unapologetically for inference workloads. It's…

When was the last time you saw a sushi chef use a Swiss Army Knife to slice your sashimi? Exactly—because they use knives precision-made for cutting sushi. So why, when you need fast, efficient “inference,” are you using inefficient multi-purpose GPUs built to do everything…