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Were almost at the point whereAIcan no longer be simply defined as an emerging technology.
Its here, and its booming.
Thats up from just 20% in 2017.
The technology is soaring, but like a busy road with too much traffic, theres always a bottleneck.
The traffic is coming; perhaps its time to turn our attention to the roads.
These arent just teething troubles.
This happens when AI systems struggle to access and interpret data across the organization in real-time.
One critical aspect often overlooked is the importance ofnetworkinterconnection.
Heres how this plays out within a typical enterprise.
Cloud and AI a winning combination
Cloud computingplays a crucial role in AI implementation.
A similar picture emerges across different territories, too.
The connectivity conundrum
Lets consider how organizations typically use AI.
For this, latency is not such a big issue, but high bandwidth connectivity is critical.
Secondly, they need AI to work in real-time, which is where latency does matter.
In short, AI needs both high bandwidth and low latency online grid performance.
Oh, and did we mention this all needs to be seamless?
The missing link is interconnection
Here is when the web connection performance bottleneck becomes apparent.
Too many enterprises still rely on public internet or third-party transit for connecting data and AI systems.
To control data flows, enterprises need to control how networks interconnect with each other.
By establishing direct, high-performance links, businesses ensure control over performance, security, and data routing.
Enterprises need AI-ready infrastructure
AI offers organizations unprecedented opportunities to transform their operations and revenue generation.
The future of AI has already arrived; we just need to verify were ready for it.
We’ve featured the best IT infrastructure management service.
The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc.
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