Andreas Stuhlmüller: belief

Transcript context

…c review, which solves is one of those where I just don't think it makes sense for pharma companies to try and build this thing that every company has to do the same way and is actually very involved. Other types of certain, especially in the early stage research or even in development, certain kind of predictive models make sense that a pharma company would want to build in-house. And then on the clinical trial point, I think why not have both? And I think we'll try, there's a lot of interest in kind of digital twins and simulating trial effects digitally as much as possible to draw, design the trial well. And I'm sure there are certain trials where with the right regulatory framework and kind of operational improvements, we might be able to take a lot more bets. I think especially like in rare diseases where you have a kind of, where a trial is actually almost like a treatment option, being much more flexible there. And then I think in other domains, depending on the type of drug and what we already know about, it's toxicity profile would probably want to hold a higher bar. So again, my hope is that it's great to have multiple tools and options and choices. And so maybe we can just build more tools, make the tools better, and then build a good framework for like when you reach for what tool? I think there are many cases where you just can't do everything at once. So like if you think about clinic trials from the participant perspective, right? Usually you can participate in like one or at most two. And often there are many that you could participate in, but you still need to choose which of those do you go with. And so I think that's a tough planning problem. And likewise, I think as a company, you have a certain amount of resources and they can be deployed one way or the other. I still find, especially as a company that is trying to be extremely mission focused and how do we actually, in the short time that we have, make an impact on the quality of reasoning and the impact of AI on reasoning quality, I think by default, you're probably just not going to accomplish that. And even if you hill climb on user metrics, then you're probably just not going to accomplish that. So you need to think pretty carefully about how to get that to work. Your call out of the patient perspective is a really useful reframing there because it's one thing to say, yeah, as a pharmaceutical company, maybe we can have both, we can run all the trials or certainly as a SaaS company, I can potentially launch all the features whether or not I should, I maybe could. But if you've got cancer, you've only got one body and you've only, you can't take all the drugs, right? And that would obviously be ill advised. So that I do think is a really, at least for now, where until the transhuman uploading future, whatever appears, we are going to continue to face these very stark choices about what should I do with my own individual body as a human, knowing that there's not like a second copy of it and there's not really the ability to kind of diversify across paths in many cases. Are there any examples of that you could share at the company level, especially if there's something where this sort of company model and recursive self-improvement paradigm way of working has led, at least in your counterfactual analysis, to a different approach than you might have taken were you just gathering around the table and sharing your intuitions like people used to do.…

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