Artificial intelligence has become very powerful, but its large-scale use is often slowed down. AI models need massive amounts of data to train and operate. However, in many organizations, this data is scattered, slow to load, or difficult to share. The machines are powerful, but they spend time waiting for the data to arrive. This is precisely the problem that VAST Data and Nvidia (a US company and world leader in semiconductors for high-performance computing and artificial intelligence) are seeking to solve together. By combining VAST Data's data platform with Run:ai, a solution developed by NVIDIA to manage AI resources, companies can now access their data almost instantly, without copying, moving, or preparing files for each new project.
Previously, a team training multiple AI models in parallel often had to wait for data to become available, resulting in queues and wasted time. With the joint solution from VAST Data and NVIDIA, data is now ready to use and shared across all projects. Teams can start their work as soon as they need it, without blocking others. This collaboration also allows for smarter use of computing resources. Rather than reserving powerful machines for a single use at a time, multiple AI projects can run simultaneously, sharing resources seamlessly. For a company, this means less waste, better cost control, and the ability to move forward more quickly on strategic projects.
Furthermore, today, much of the environmental impact of AI comes from waste. Very powerful machines consume energy while waiting for data, running idle, or being misused. When a model takes a long time to load or when multiple teams get stuck with each other, electricity is consumed without producing results. By allowing AI models to access data faster and without duplication, the alliance between VAST Data and Nvidia reduces these downtimes. Machines work less time to do the same thing. This means fewer hours of unnecessary computation, and therefore less energy consumed.
