Chan Zuckerberg is NOTORIOUS for overly ambitious claims, the Chan Zuckerberg Initiative started in 2015 with the bold statement they would "cure all disease in our lifetime." It's been 11 years. Have they cured 1 disease? Let alone ~all~ disease? No.

When Zuckerberg realized he probably wasn't going to hit this goal they quietly changed it to "within our children's lifetimes."

I used to work in their building and actually saw them change it on the wall and as "within our childrens" 3 years in. Stay posted, probably in 15 years they buy themselves some more time and make it "our children's children's lifetimes."

In, say, civil or aerospace engineering, science is understood well enough to allow your building or airplane to be modelled and tested using computer modelling, CAD software, FEM and CFD algorithms and so on. You can design a building or aircraft without ever building a single physical model, and it will stand (or fly), 99 times out of 100. It is oversimplification to a a degree, but sufficiently close approximation.

No such thing exists in biology, pharmaceutics, biotech and so on. The accuracy of computer models and simulation is not sufficient to produce results with single-digit percent accuracy for any metrics, hence long and complex Phase I-II-III trials. Maybe 1 out of 100 candidate drugs work.

Why? Because we do not have the same level of understanding for biological systems as we do for building or aircraft, or software. Amount of information is much larger, complexity is far greater, enzymes and cell signalling network make biochemistry even more non-linear. This makes the problem space vast. It is practically untapped domain and it can eat any amount of computation power and biologists, data scientists and software devs (manpower-wise).

Any incremental improvements in simulation, modelling and interpretation of biological system behaviour will generate downstream improvements in medicine, pharma, biotech. But general-purpose LLM AIs are not that useful in biology, you need more specialized solutions to improve both accuracy and performance of large number of algorithms that have tremendous computational complexity: computational chemistry, molecular dynamics, genomics->proteomics->interactomics->metabolomics (all of that for just intra-cellular behaviour - tissues, organism and organisms are multiple orders of magnitude harder).