There are two important trends driving infrastructure changes that will impact the results of your AI investment.
In years gone by, we saw companies rush to cloud for ability and cost savings, lured by the frenetic news that cloud was going to change everything. It did, but it took a toll on many who failed to consider the changes being wrought in everything from compute to infrastructure to app services.
Today, the siren song of AI is attracting many who want to be “in before” the benefits start rolling in.
But let's learn from history this time. There are skills, technologies, and practices that need to be put in place to successfully see a return on your AI investment. The AI tech stack is still forming, but it is rapidly shaping up to include a broad range of technologies and capabilities that many organizations today do not possess.
There are several different versions of this stack, but most share this simple structure and nearly all of the components. And one of them, you'll note, is at the very bottom, almost like it’s foundational.
And in that layer – compute and foundation – you’ll note that what’s holding up the entire AI stack is, unsurprisingly, containers and hardware.
It is here that we see two key trends accelerating change that need to be considered – and likely incorporated into your own tech stack – before you sign that AI investment check.
#1 Compute Platform
If you didn't see this one coming, it's time to glance up and take a good look at the workloads deployed in Kubernetes across core, cloud, and edge.