So we probably won't be getting a direct simulation of a whole virtual cell at meaningful timescales any time soon. Oh, and it would require 20x current earth power generation. 3/3
Read the analysis/blog post here: diffuse.one/p/d1-009
Here's one measuring the frequency of sample sizes. Like how often people use 8 samples vs 12 samples for reporting research results. N=2 is apparently the most popular 2/3
I finished my estimate on required compute to make an atomic-resolution virtual cell: 10^38 FLOPs to simulate a human cell for 1 day. We should be able to do this simulation in 2074 using 200 TW of power. 1/3
Andrew White 🐦⬛
Andrew White 🐦⬛
Google scholar has a full-text index of nearly all research papers. You can use it to get counts for arbitrary phrases. I've been using this to measure popularity of things in science. For example, here's the popularity of Greek letters used in equations 1/3
read it here: diffuse.one/p/d2-002
It sounds insane, but remember there are 10^14 atoms in a human cell and 10^20 femtoseconds in a day. And across multiple simulation engines, it requires 10^4 FLOPs per atom x femtosecond 2/3
Making "AI Scientists" has become a hot topic lately. The first reference I could find was from 2008. The term has been used for 20 years! Like "Adam," an AI Scientist robot for studying yeast was published in 2009. I wrote a short post about the term and what it means now.
diffuse.one/p/w1-001
I've written up some thoughts on publishing for machines. 10M research papers are published per year and there are 227M total - machines will be primary producers and readers of publications going forward. Humans can simply not keep up. It's time to think about revising the scientific paper.
Our ether0 paper was accepted at NeurIPS 2025! Very proud of the FutureHouse team!
You can also look at it over time. Here's relatively popularity of different animal models in research over time.
Anyway, found this to be interesting. More details about it here: diffuse.one/p/d2-003 3/3
