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.
The golden ratio is one of those things you can study for years and be a amazed by.
>The golden ratio (≈ 1.618) and its related golden angle (137.5°) show up in nature because they maximize space, exposure, and flow.
The golden ratio is an algorithm, but it is also a natural law that systems of many different scales follow. Wherever we look we find examples of it. Without this algorithm the world is a much harder place to explain.
What many scientists starting to look for is these algorithms we have not identified in natural systems as an explanatory means of their workings. Also because they are algorithms they are things we can put into computer systems to increase efficiency, or may naturally emerge from evolutionary learning systems like AI in what we call emegence.
The golden ratio in nature is numerology. Biology is beautiful enough in itself without having the golden ratio shoehorned into it. <a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC10792139/" rel="nofollow">https://pmc.ncbi.nlm.nih.gov/articles/PMC10792139/
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?
pixl97 · · focus · HN ↗
>The golden ratio (≈ 1.618) and its related golden angle (137.5°) show up in nature because they maximize space, exposure, and flow.
The golden ratio is an algorithm, but it is also a natural law that systems of many different scales follow. Wherever we look we find examples of it. Without this algorithm the world is a much harder place to explain.
What many scientists starting to look for is these algorithms we have not identified in natural systems as an explanatory means of their workings. Also because they are algorithms they are things we can put into computer systems to increase efficiency, or may naturally emerge from evolutionary learning systems like AI in what we call emegence.
esafak · · focus · HN ↗
rolph · · focus · HN ↗
the better direction in my opinion, is the mutual reinforcement of coupled dynamic systems, that ends up giving us metabolism.