English 
Eyelet has launched a service that goes straight at one of the biggest blockers in AI right now. Getting GPUs when you actually need them.
The company is offering end to end support that covers procurement, setup, and ongoing operations on Google Cloud. No, it is not a complex idea, but it really presents a problem spot. AI teams are bogged down in infrastructure work rather than model-building time.
The service handles the full stack. From figuring out what GPU capacity is required, to securing it, to setting up the environment and keeping it running. That matters because access alone is not the problem. Using GPUs effectively needs cloud architecture skills that most AI teams do not have in house.
こちらもお読みください： マイクロソフトとエリクソン、5G Windows 11 PCを推進
The current situation exists because worldwide demand for GPUs exceeds available supply which results from the requirements of large language models and data-intensive operations. Companies need to postpone their projects or reduce their work because the existing infrastructure does not provide reliable performance.
Eyelet is positioning itself as the middle layer that removes this friction. Less time negotiating capacity, more time actually building AI. That shift is where most of the industry is heading. Infrastructure is no longer support. It is the constraint.
日本語