AI systems

“So our take of that and my take is that semantic layer is just really good place for this context to live because you need to give this context to the humans. You need to give that context to the AI system anyway, right? So that's why you define metric once an…”

“The importance of supervising the process of AI systems, not just the outcomes. And so a big part of how, then, like, how Elicit is built is, We're very intentional about not just throwing a ton of data into a model and training it and then saying, cool, here'…”

“Like, the idea that there's going to be, like, a lot of offline compute and inference under the hood that helps make AI systems continuously self-improve is a sure bet.”

“So I would actually say that like a lot of the things to simulate are more aligned with like product KPIs or product metrics that actually make Whatever AI system you're building very sticky, rather than, you know, focusing more on, like, traditional safety se…”

“Fact checking a long document is still well outside the capabilities of most AI systems because, you know, for the attention reasons, but if you're working in sections, it's really easy to be like, while I'm here,”

“AI systems need to be model agnostic. They shouldn't care about which model that they use, and they should look at what I call actions, which is a combination of a model with a prompt and maybe a set of tools that it can use and say, what can an action do for …”

“The problem remains then and now is regulatory because you actually can't shift the burden Of the wrong clinical diagnoses from the physician to the AI system.”