Developing powerful AI no longer necessitates enormous data centers packed with thousands of processors; a paradigm shift is underway.
Researchers are exploring distributed computing, where the training process is split between many smaller, less energy-intensive machines.
This approach promises to decrease reliance on massive, expensive infrastructure and reduce the environmental footprint of AI development substantially.
The future of AI training could involve decentralized systems, potentially eliminating the need for specialized hardware altogether.
