Eric Topol

Because it's very thoughtful that you're thinking already about that.

And of those 40 some authors around the world, do you have the sense that you all work together to achieve this goal?

Is there kind of a global bonding here that's going to collaborate?

Yeah, no, it's really quite extraordinary how you kick this thing off and the paper is the blueprint for something that we're all going to anticipate that could change a lot of science and medicine.

I mean, we saw, as you mentioned, Steve, how that deep visual proteomics saved lives.

It was what I wrote as spatial medicine, no longer spatial biology.

And so the way that this can change the future of medicine, I think a lot of people

just have to have a little bit of imagination that once we get there with this AIVC, that there's a lot in store that's really quite exciting.

Well, I think this has been an invigorating review of that paper and some of the issues surrounding it.

I couldn't be more enthusiastic for your success and ultimately where this could take us.

Did I miss anything during the discussion that we should touch on before we wrap up?

Yeah.

Thanks so much.

Well, thank you both and all of the co-authors of this paper.

We're going to be following this with great interest.

And I think for most people listening, they may not know that this is in store for the future.

Someday we will get there.

I think one of the things to point out right now is the models we have today, the large language models based on transformer architecture,

they're going to continue to evolve.

We're already seeing so much in inference and ability for reasoning to be exploited and not asking for prompt with immediate answers, but waiting for days to get back a lot more work from a lot more computing resources.