PARTNERS ’ PERSPECTIVE
AI exchanges necessary to solve network bottlenecks
Ivo Ivanov , CEO DE-CIX
Network latency is proving to be a bottleneck for AI-heavy workloads with 33 % and more of elapsed time spent waiting for the network , implying that the network is the computer for AI workloads . It does not matter how well AI is deployed ; it will be limited by the best network setup . Ivo Ivanov at DE-CIX explains more .
According to a 2024 MIT Technology Review report into AI , a whopping 95 % of companies are already using AI in some form and half of companies expect to deploy AI across all business areas within two years . So , where are the cracks ?
While the AI boom continues and businesses are going all-in , important questions are being raised about the AI-readiness of businesses , particularly regarding connectivity and the infrastructure supporting it .
The same MIT report , while optimistic on the whole , reveals that of those businesses claiming to have deployed AI , three-quarters have not yet gone beyond pilot projects
One path businesses are taking is to ride the tide of two complementary megatrends : cloud computing and AI . and many are reporting challenges relating to data quality , 49 %, data infrastructure , pipelines , 44 %, and integration tools , 40 %. Network latency is also proving to be something of a bottleneck , particularly when it comes to AI-heavy workloads . According to Meta , more than 33 % of elapsed time in AI , ML workloads is spent waiting for the network , leading the Dell ’ Oro Group to conclude that the network is the computer for AI workloads .
In other words , it does not matter how well AI is deployed or how ready a business thinks it is for AI implementation , they will always be limited by their best network setup .
One path businesses are taking is to ride the tide of two complementary megatrends : cloud computing and AI . Cloud plays an important role in AI implementation , not least because migrating data lakes and warehouses to the cloud helps enterprises keep up with the accelerating growth of data . As many in its partner ecosystem have observed , AI success goes hand in hand with cloud migration and expansion .
According to Deloitte , four in five companies that have experienced the most success with AI also expanded their cloud investments as part of their AI strategy . The growing ecosystem , driven by market developments from its largest players , also points to this growing intersection between cloud and AI services , such as AWS ’ delivery of Generative AI capabilities through its
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