Why Bio × AI Is the Story of the Decade — and Why This Blog Exists
TL;DR
Biology just became a data problem AI is unusually good at — protein structure, genome interpretation, and drug design are all being rewritten by models. Every Saturday I’ll pick one high-impact, recent development in that space and explain it TL;DR-first, then go as deep as you want. This is issue zero: what to expect and why.
Why this matters now
For most of history, biology moved at the speed of wet-lab experiments. In the last few years that changed: sequence and structure data got big enough, and models got good enough, that you can now predict biology instead of only measuring it. That shift touches medicine, agriculture, and how we understand life itself — and it’s moving fast enough that even people in the field struggle to keep up.
What to expect
Every week, one topic, chosen for impact and recency (I score candidates so I’m not just chasing headlines):
- TL;DR you can read in 20 seconds.
- Plain-language explanation for the curious non-specialist.
- “Go deeper” links for people who want the mechanism and the sources.
- My take — what’s real signal vs. press-release gloss.
Short versions go out on LinkedIn; the full write-up lives here.
Who this is for
Researchers, engineers, investors, and the merely curious. Beginners get an on-ramp; advanced readers get the depth and citations. Same post, two speeds.
What to watch next
Issue #1 drops next Saturday. Subscribe (coming soon) so you don’t miss it.
Sources
- This one’s an intro — real posts cite primary papers, code, and data.