It's really a matter of iterating on the problem and validation right?
Models make progress on coding and math because they can write tests and proofs to an extent. Many industries that are more 'physical' and require performing experiments lack that instant feedback loop. Find a way to close that loop and AI begins to look useful.
But try and convince companies to invest on closing that loop just to see if the current models work well on their problems or not? Tough sell.
So Anthropic just shows them, hey look, this is possible and if you don't do it I will.. so they fold.
>Models make progress on coding and math because they can write tests and proofs to an extent. Many industries that are more 'physical' and require performing experiments lack that instant feedback loop.
This is basically what they targeted with this approach. They can't automate the experiments since they are often bespoke towards certain goals or even feelings and assumptions based on sage technician knowledge that isn't really taught in any one place. Instead, they tried to automate the process of searching for candidate targets to then test in downstream lab experiments.
Seems exciting, but this sort of thing has been done for a while with just about every single ml classifier method out there for all sorts of biological data. Just yet another way to slice the pie.
Lands as an active threat. Maybe they're serious about this research or not, but for sure medical companies doing this sort of research will consider upping their AI budget and connecting their labs, etc. to avoid "falling behind".
So, the AI labs benefit either from achieving something they could market or from the peer-pressure imposed to companies in the sectors they get their nose in.
Could one make in theory a regular monospaced font to just render glyphs past 80 chars of a line as bad as possible?
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