Healthcare and pharma companies like Amgen have two distinct categories of AI need: accelerating pure R&D work involving massive scientific datasets, and automating the heavy administrative and document-authoring burden required to get an approved drug to market.

12:05with Amgen to understand what are their  needs. And it's really interesting, like, when I look at those healthcare companies, I feel  like they are two big buckets of needs. One is, like, pure R&D. It's like, you know, you're  seeing, like, a massive amount of data and, like, you have super smart scientists who are trying to,  you know, come by, test out things, you know. So, that's one bucket. A second bucket is, like, you  know, much more, like, you know, common across

12:27other industries. It's, like, pure, like, you  know, admin, document authoring, document-scribing work, which is, you know, by the time, like, your  R&D team has essentially locked the recipe of a medication, getting that medication to market is  a ton of work. Like, you have to submit to, like, value regulatory bodies, get a ton of reviews.  And you know, when we looked at essentially those problems, what we knew, what models were capable  of, we saw, like, you know, a ton of benefits,

12:54a ton of opportunities to automate and, you  know, augment essentially the work of those teams. And so, yeah, Amgen has been, like, a top  customer of GPT-5, for instance. Wow. I mean, this could be hundreds of millions of lives if a  new drug is developed faster. Yeah, exactly. Huge impact. So that's, you know, that's, I think,  one good example of, like, a kind of impact on which you need to enable enterprises, like, to  do it. Right. You know? And so I think we're

13:19going to do more and more of those. And yeah,  frankly, like, you know, on a personal level, like, it's a delight, you know. If I can play,  like, you know, a tiny role, essentially, like, doubling, like, you know, the kind of medication  that people, you know, get in the real world, that feels like, you know, a pretty good, like,  you know, achievement. Huge. Huge, huge. I know

13:34you had one as well. So one of my favorite  deployments that we've done more recently, actually, is with the Los Alamos National Labs. So  this is the, like, government, national research lab that the U.S. government is running in Los  Alamos, New Mexico. It's also where, you know, the Manhattan Project happened back in the 40s  and 50s, back when it was the secret project. So, you know, after that, they ended up formalizing  it as a city and a program, and then now it's a

13:58pretty sizable national laboratory. This one is  very interesting because one, just the depth of impact here is, like, unimaginable for me, it's  like on the scale of Amgen and some of these other larger companies. But, you know, obviously  they're doing a lot of actual new research there, so a lot of new science. They're doing a lot of  stuff with our Defense Department and Defense use cases as well. So very intense, you know, very  intense stuff. But the other thing that's actually