In recent years, data centers have undergone rapid transformation, driven by advancements in generative artificial intelligence (AI). Applications like ChatGPT, Midjourney, DALL·E, and Deepbrain, which respond to natural language inquiries, require enormous computational power and operate with very low latency levels. This places significant pressure on networks and computing data centers. These programs ‘learn’ by scouring large amounts of data making them extremely bandwidth-hungry.

An AI cluster could be described as one large compute entity, with networking the GPU, storage, and other compute similar to the traffic through a traditional backplane or motherboard may flow. This GPU-based architecture presents data center architects with the challenge of designing a contentionless network capable of meeting the density, latency, and bandwidth requirements of unpredictable AI/ML data traffic models.

To keep up in this highly demanding new era, data center operators must ensure they can meet the increased demands, making component choices crucial. Choosing advanced optical transceivers capable of handling bandwidth-intensive data flows is a key part of this. This means turning to the new breed of 400G and 800G transceivers.