Biology already has numerous “Millennium Problems” and the rewards are much more than $1M. For example, reverse Alzheimer’s Disease. Or less ambitious develop high fidelity in vitro and animal models of human disease.
Those don't have the property of being easily verified, which the problems proposed here do. I think that's a smart idea because it's a way to capture quick PR seeking AI-lab dollars for quite useful outcomes.
Being easily verifiable does not elevate something to the level of being a grand challenge. It really drives home the point that biology is not math or coding.
I guess to me the grandiosity here feels fake and unearned - like they vibe slopped it together without much input in the way of deep thought or expertise.
For example, synthesize arbitrary dna sequences > 3000 nt in length with error rate < 0.001 at > 95% purity. Easily verifiable, beyond the frontier, and generally useful.
Biology is a really really big field. Many problems in biology are that of math and coding. Just as a simple example look at the golden ratio in living organisms. Biology follows a lot of different algorithms because they are energy efficient and come with massive secondary benefits.
pfisherman · · focus · HN ↗
phreeza · · focus · HN ↗
pfisherman · · focus · HN ↗
I guess to me the grandiosity here feels fake and unearned - like they vibe slopped it together without much input in the way of deep thought or expertise.
For example, synthesize arbitrary dna sequences > 3000 nt in length with error rate < 0.001 at > 95% purity. Easily verifiable, beyond the frontier, and generally useful.
pixl97 · · focus · HN ↗
Biology is a really really big field. Many problems in biology are that of math and coding. Just as a simple example look at the golden ratio in living organisms. Biology follows a lot of different algorithms because they are energy efficient and come with massive secondary benefits.
root_axis · · focus · HN ↗
What is this example meant to illustrate?
SiempreViernes · · focus · HN ↗
pixl97 · · focus · HN ↗