@rohanpaul_ai: Nvidia released this video of its photonics co-packaged optics (CPO) switch with Lambda. The AI race is not only about …

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Summary

Nvidia unveiled its photonics co-packaged optics switch with Lambda, aiming to reduce power consumption and failure points in large GPU clusters for AI workloads.

Nvidia released this video of its photonics co-packaged optics (CPO) switch with Lambda. The AI race is not only about stronger GPUs, but about wasting far less power while those GPUs talk to each other. With co-packaged optics (CPO), NVIDIA is putting the light-based communication parts much closer to the main networking chip, instead of placing them as separate plug-in modules at the edge of the switch. From NVIDIA's official blog on this "co-packaged optics (CPO) connects directly to the token economy. Network power is overhead: it keeps GPUs connected but doesn't generate tokens. Network failures are also overhead: they turn provisioned GPU capacity into idle capacity. CPO addresses both by reducing network power draw and removing a large class of pluggable optical components from the fabric. A 128,000-GPU data center using traditional pluggable transceivers requires roughly 655,000 discrete transceiver modules across the switching fabric. Each one is a potential failure point. CPO removes that component class entirely. Agentic workloads change the pressure on the network. A traditional inference request is relatively self-contained. An agentic request can involve planning, retrieval, tool use, multiple model calls, and follow-up reasoning. More data moving across the cluster. More points where network latency or failure affects the outcome. Multi-agentic inference needs elastic and resilient data movement, so GPUs are not waiting for data, while maintaining tokens per second and fast time to first token."
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Nvidia released this video of its photonics co-packaged optics (CPO) switch with Lambda.

The AI race is not only about stronger GPUs, but about wasting far less power while those GPUs talk to each other.

With co-packaged optics (CPO), NVIDIA is putting the light-based communication parts much closer to the main networking chip, instead of placing them as separate plug-in modules at the edge of the switch.

From NVIDIA’s official blog on this

“co-packaged optics (CPO) connects directly to the token economy. Network power is overhead: it keeps GPUs connected but doesn’t generate tokens. Network failures are also overhead: they turn provisioned GPU capacity into idle capacity. CPO addresses both by reducing network power draw and removing a large class of pluggable optical components from the fabric.

A 128,000-GPU data center using traditional pluggable transceivers requires roughly 655,000 discrete transceiver modules across the switching fabric. Each one is a potential failure point. CPO removes that component class entirely.

Agentic workloads change the pressure on the network. A traditional inference request is relatively self-contained. An agentic request can involve planning, retrieval, tool use, multiple model calls, and follow-up reasoning. More data moving across the cluster. More points where network latency or failure affects the outcome.

Multi-agentic inference needs elastic and resilient data movement, so GPUs are not waiting for data, while maintaining tokens per second and fast time to first token.“

NVIDIA AI Infrastructure (@NVIDIAAIInfra): 📣 Get a first look at the NVIDIA Photonics co-packaged optics switch with @LambdaAPI.

At NVIDIA GB300 NVL72 scale, the network doesn’t just move data between GPUs — it determines how fast your cluster thinks. Co-packaged optics cut switch power, reduce failure points, and

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