Here’s the interesting part.
"We didn't do any LLMs. There is significant interest in that. There are lots of people trying those ideas out, but I think they're still in the exploratory phase," Desai told El Reg.
As it turned out, the researchers didn't need them. "We used a simpler model called a variational auto encoder (VAE). This model was established in 2013. It's one of the early generative models," Desai said.
By sticking with domain-specific models based on more mature architectures, Sandia also avoided hallucinations – the errors that arise when AI makes stuff up – which have become one of the biggest headaches associated with deploying generative AI.
"Hallucinations were not that big a concern here because we build a generative model that is tailored for this very specific task," Desai explained.
