Yeah, it feels like we need a phase transition in the speed and practicality of the process. But I don't believe we need a single concrete lab tech.
Years ago when I did research, my impression was that there was complexity galore. A researcher on Drosophila developmental signaling would have a very disjoint knowledge domain than that of a researcher in horizontal gene transfer and antibiotic resistance. Both would exist in a different planet altogether than a clinician prescribing a cancer treatment. And the three of them would generally lack the tooling that somebody doing systems biology was used to.
So, to me, the key thing we need is some sort of "domain cement", or a good way to pull operative knowledge and usable skills from everywhere.
Isn't that what LLMs are shaping up to be? Once we manage to divorce the knowledge from the weights in some way we could have in effect a frontier model whose awareness was limited to the sum total of the scientific literature.
The answer I got was along the lines that they were simply going to get around to do the actual lab work at some point.
DNA synthesis technology hasn't really been a blocker for generative bio projects except at the full chromosome level.
And I think simply generating a full chromosome and booting it up without doing due diligence is probably a recipe for disaster.
We honestly aren't that far away from AI slop enzymes, AI slop ligases, and eventually AI slop bio weapons...
Why do you think that?
But there are a lot of analogies to computation in bio as a physical, atomic forces-driven, massively parallel computer, so it's possible there will be something related to electronics and computers that falls out. For example, there's also applications directly related to other fields including DNA storage of data and neuron-based computation.
Biology has had many of these over the centuries.
> But there are a lot of analogies to computation
People have been saying this since pretty much the start of computation and I don't think anything's ever come of it.