
What happened
PsiQuantum announced a new device that routes data between GPUs without converting photons into electrical signals, which executive vice president Robert Soderbery said would let separate server racks behave as one.
Why it matters
Eliminating optical-to-electrical conversions could cut the heat, energy and bulk generated by optical switches in large AI data centers, addressing a networking bottleneck during training of large models.
WHO IT HITSData center network architects and AI infrastructure teams at hyperscalers and large model trainers, who currently rely on optical switches that generate heat and consume energy during GPU-to-GPU data transfer, may see an alternative for rack-to-rack connectivity.
Summaries like this, every morning.
AI data centers have scaled by networking hundreds of thousands of GPUs, but the copper links between them have become the weak point, especially during training runs that demand heavy coordination. Optical cables are increasingly used, yet they still require converting light to electrical signals and back again billions of times per second, generating heat and bulk through the optical switches involved.
PsiQuantum's device sidesteps those conversions entirely, which Robert Soderbery said would let data flowing between GPUs in separate racks match the speed and latency of GPUs inside one rack. That matters because server racks are approaching limits on compute density, size and energy efficiency, so stretching performance across racks could offer a way around physical constraints.
The company is not alone in pursuing photonics for data center networking. Google already operates a purely optical circuit switching system using MEMS mirrors, while Lightmatter has pushed for standardization and Nvidia has invested billions in optics companies like Lumentum and Coherent. PsiQuantum's entry suggests the race to move data center networking from copper to light is drawing in quantum computing players as well.
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