Show notes
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?
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