Run: Ai is introducing virtualization technology for AI software powered by GPUs. In the early 21st century, we learned about Virtualization Technology, and since it was first introduced by VMware, we have Virtual Servers, or VMs that we hear about most often.
Now Run: Ai has now introduced a method that can be used to run AI software on GPUs. While a typical software program requires a CPU, the use of the GPU to run AI applications is known for their ability to run multiple processes simultaneously with Deep Learning and Neural Networks.
Since AI software uses this GPU for its work, the Virtualization concept itself has been able to bring GPU sharing to the status of many, many improvements.
Data Science and AI teams have the capability to run their own programs on the same GPU and RUN: AI has introduced a way to manage this GPU sharing via Kubernates.
RUN:AI The introduction of these Virtualization features into the Docker Kubernaters Plugin by Docker’s portability features makes it very easy to manage and manage workflows.
GPU Server hardware in one place can be used by the entire group to make it easier and more convenient for you.
The founder of Omri Geller points out that RUN: AI was founded in 2008 but has already raised over $ 13 million.
“The Abstraction Layer we have created has been able to close the gap between workloads and computer hardware. With this Abstraction Layer we are able to perform more than 100x (100x) efficiency, mainly due to the use of Deep Learning and Neural Networks. Time Saves This Distributed Resource Architecture. “
The business is based in Israel and has a full team of 25 people, including Americans, serving many customers worldwide.
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