connectivity opportunities for network operators

 Despite the current hype associated with the network impacts of AI, AI-driven traffic is still in its early days and not yet substantially augmenting data flows outside of data centers. However, additional connectivity capacity will be vital to sustain the growth of AI infrastructure and the evolution of AI models and applications. Securing such capacity is an integral part of investments that are already underway, creating tangible opportunities for network operators aiming to monetize AI demand. Now is the time to set out for success in AI infrastructure connectivity.

AI compute growth will translate into a 200-fold increase in power requirement

“Deep learning worked, got predictably better with scale, canada telegram data and we dedicated increasing resources to it.” Sam Altman’s words appropriately summarize the impressive evolution of AI models and its supporting infrastructure in recent years. Hyperscalers and AI powerhouses are investing billions of dollars to lead the AI race. They are building colossal AI training facilities to deliver ever more powerful large language models (LLMs). The compute load to train a cutting edge LLM is growing 4.7 times a year. This consistent trend points to a growth in training compute of leading AI models around 10,000 times over six years.

Network operators’ response

To capitalize on this opportunity, network operators are leveraging both technology and business model innovations. Historically, hyperscalers have favored building their own DCI networks. However, due to a combination of time-to-market pressures, business priorities, and regulatory constraints, they are increasingly open to alternative approaches for building their networks. On the other hand, service providers are seeking to meet hyperscalers’ demand through managed services, aiming to get more value from their existing fiber assets. That said, hyperscalers are very particular about design requirements, service levels, and the control and management of network assets, giving them influence over the evolution of the networks to support their AI infrastructure buildouts.

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