AI acceleration hardware is becoming increasingly expensive, with next-generation chips demanding high power budgets and major infrastructure investment. For many startups and smaller enterprises, the cost and complexity of deploying AI at scale creates barriers long before software development even begins.
New silicon players such as FuriosaAI are trying to rethink that equation, focusing on efficiency, performance, and alternative approaches to the GPU-dominated market.
