In this episode, we discuss the current state and challenges of environmental controls in an AI and HPC fueled data centre and at the edge. Let’s start by discussing some of the current use cases and some of the near term use cases for AI and HPC in the Federal Government space.
What are some of the traditional uses cases for HPC and AI that the Federal Government uses currently?
· What are some of the identified use cases that have been difficult to implement?
· What challenges have stalled those implementations historically?
· How has the current state of HPC and AI changed so that some of those use cases can now be realized?
· What needs to be done so the federal space can implement the remainder?
· How have traditional HPC and AI technologies changed and how has that made things easier for implementations?
· How have things become more complex or challenging?
· What types of investments are being made for infrastructure to support modern HPC and AI platforms?
· How has the density of HPC and AI created challenges for IT teams?
· How are large hosting providers and public cloud providers handling AI at scale challenges?
· What has the advent of Generative AI done to change the HPC and AI landscape?
· Let’s talk about deterministic vs probabilistic models. How are they different?
o How does this difference make them more suitable to different use cases?
· When we think about data governance and AI governance it becomes a bit of safety vs innovation. How do we create a healthy balance between those two?
· How can we mitigate risk but still drive forward innovation of AI?
· As we look to the next 2 to 3 years what are some of the new use cases that you think will drive investment and also provide value?