Is it easier to teach astronauts to drill or teach drillers to be astronauts?
My money is on Eli Lilly leveraging AI to develop drugs vs Anthropic becoming Eli Lilly. Obviously teaching drillers to be astronauts is the better movie though.
I've found, from working with scientists and non-software specialists at NASA, universities, and various industries, that the big wins come from specialists learning to code as the vanguard, then a few engineers taking over for production. I think that's ever more true with AI assistance, and I'm not sure what is left for product-ization. All I know is it's changing fast.
It's always something I've hated, coming from software and working with experts. I always wanted to be the "software guy" who gets to learn the specialist engineering disciplines. It just felt like swimming upstream and the incumbent specialists always wanted to DIY.
Having said that, some subject-matter experts just don't have the stomach for it. They are so separated from software that they have a block to building even with AI. A good s/w-specialist pair is dynamite there.
> the big wins come from specialists learning to code as the vanguard, then a few engineers taking over for production
The best places to work are ones with high mutual respect between the 'R' and 'D' of R&D. When either camp dismisses the value of the other and everyone stops giving a little to make the handoff easier it just makes everyone miserable.
Yeah what goes unspoken in all these AI discussions is that there's a culture of collaboration that just evaporates when everyone is pushing their own ideas.
There's very little mutual discussion, brainstorming, anything. The slowness inherit in building software before made those discussions almost necessary, now they're post-hoc criticisms (PR "review") rather than fulfilling collaborations.
It's fine from a technical sense, but I do wonder what it does for culture.
"that the big wins come from specialists learning to code "
I used to work at startup that did video encoding. We had tons of computer vision scientists that refused to learn decent C++ coding practices. Their stuff never worked right and they didn't really contribute much. We also had a few scientists who were decent coders and pretty much all progress came from them.
I see the same with some data scientists. They want to do pure data science and refuse to do the coding to actually get their data. So they have to be spoon fed all the time and their progress is super slow.
This distinction has massive implications for Anthropic's valuation. If a pharma company uses Claude in computational drug development, their work product remains their IP, not Anthropic's.
Largely, most of the paper pushed in these big pharma companies is in regulation and compliance. So much so that it isn't that much of a stretch to say they are mostly regulatory compliance companies with a research division attached. It's not entirely true, of course, but it does fit a bit. Also, there are a lot of regulatory agencies out there, not just the FDA.
That regulatory function is quite personal and hands on. It's relationships built up over months and decades. AI, almost by definition, cannot replace it or augment. Sure, faster, better. But even then that backlog will grow to meet any gains.
Source: I have done (and have family members that do) compliance and regulation for larger phramas, including drugs and instruments that you have had (with near certainty) your medical reports analyzed and produced by.
Look at the background of those researchers: Demis was cogsci phd (and he is a general intelligence that can work on a wide range of scientific problems) and John Jumper has a masters and phd in chemistry. Their advisors and coauthors included some of the best-known ML people who worked on protein structure prediction previously. Personally I think they should have got the biology one, but they weren't unqualified scientifically speaking.
That's my bet as well, but not because Anthropic couldn't become Eli Lilly on intellectual/intelligence grounds.
The regulations, liability, and stringency of procedure in pharmaceuticals and healthcare in general simply won't gel with the SV mindset of "move fast and break things"/"forgiveness is easier to get than permission". A University of Missouri pathologist working with Jon Carreyrou put a SV biotech darling in literal prison despite a huge valuation. That sort of accountability is the exact thing founders seek to avoid, not court.
I don't think having the team of PhDs with infinite resources at Anthropic holding the place of drillers in your metaphor holds very well.
Eli Lilly might be the experienced horse carriage operator to Anthropic as the Ford motor company here instead. Or Blackberry when the iPhone was announced.
The biggest advantage Eli Lilly has is in navigating the FDA regulatory process, and at present, US Federal regulations & bureacracy can be pretty easily managed by putting one of Trump's sons or friends on the board or giving a 'donation'.
It’s going to have to be a partnership ideally where both companies collaborate and Eli Lilly provides the data and it’s lab resources and researchers from Anthropic do all of the LLM research.
My money is on Eli Lilly leveraging AI to develop drugs vs Anthropic becoming Eli Lilly. Obviously teaching drillers to be astronauts is the better movie though.