How silicon photonics lights the way for data centers

Racing to scale AI requires massive capital investment in data centers, with McKinsey recently estimating that global data center spending could reach $7 trillion by 2030. Perhaps more importantly, though, scaling AI requires massive architectural investment from a technology standpoint.

Modern data center infrastructure was not designed to power the cloud computing revolution and the massive surge in AI usage and development on a global scale simultaneously.

Executive Vice-President, Chief Product Officer at Soitec.

This architectural strain is driven by rising expectations – the more AI is adopted, the more demand of it there is. Enterprises are excited by AI’s promise as a time-saver that can automate and streamline employee workflows and increase productivity. To facilitate the growing complexity of AI models and datasets, GPU density and bandwidth have increased in data centers.

These increases mean AI models that can be trained faster, have lower latency interference and more....

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