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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