Today we announced a landmark partnership with @EliLillyandCo to use our AI models to design recombinases for genetic medicine—a collaboration valued at up to $2.25 billion before royalties.
The goal: use Profluent's AI models to design recombinase editors capable of inserting long stretches of DNA at precise locations in the genome.
Read the press release for more: https://t.co/BGG7IXjAkW
Today we announced a landmark partnership with @EliLillyandCo to use our AI models to design recombinases for genetic medicine—a collaboration valued at up to $2.25 billion before royalties.
The goal: use Profluent's AI models to design recombinase editors capable of inserting long stretches of DNA at precise locations in the genome.
Read the press release for more: https://t.co/BGG7IXjAkW
While impressive in its own right, it’s worth remembering that predicting protein-drug interactions is like 0.01% of the drug discovery and development pipeline and the spare change part of it. Saying that that’s revolutionizing the process is like convincing someone, in Derek Lowe’s memorable words, that you’ve invented a revolutionary new car because its windows go up and down ten times faster.
This is an incredible story and worth a read.
Sid Sijbrandij (co-founder of GitLab, @sytses) was diagnosed with a rare bone cancer. It came back after chemo and radiation, and his doctors told him there was nothing left to try.
So he went “founder mode” on his health.
- Built a team of physicians and researchers.
- Ran every diagnostic possible, as often as possible.
- Developed 10+ personalized treatments including an mRNA cancer vaccine and engineered cell therapies.
- Ran treatments in parallel instead of one at a time.
- Used AI to analyze his scans, bloodwork, and tissue samples.
- Open-sourced 25TB of his own cancer data.
- Applied GitLab’s radical transparency philosophy to the whole thing.
Today he has no evidence of disease.
The harder question is that this took someone with vast resources assembling a full team to navigate a system designed to block exactly this kind of patient agency.
He’s now building a venture to make this path accessible to others.
Links in the reply. Check it out
So, there’s a $1.5 billion judgement against Anthropic for including 480,000 books in training their AIs. Five of my books are among them. Word is, there might be $1,500 payout per book, according to my agent Max Brockman.
I wrote him the following:
(1/) I am thrilled to announce a medical milestone– the world’s first live birth using @GametoGen's product, Fertilo, that matures eggs outside the body. On Saturday, December 7th, a healthy baby girl was born in Lima, Peru, after using the Fertilo protocol at our partner clinic @concebirperu. https://t.co/23UkuijGxs
Waymo's market share is now equal to Lyft within SF. Incredible.
Network effects is one of the best sources of defensibility. But it's proven to be not that important in ridesharing.
You need a minimum network size, but once you have that, there are diminishing returns. In each geo, Uber and Lyft need enough drivers to have reasonable wait times. Once wait times hit that acceptable threshold, the incremental driver doesn't improve the rider experience (eg if my Uber ride is coming in 2-4 minutes, I don't really care about the wait times getting faster).
When Waymo launched in August 2023, Uber and Lyft were at 66% and 34% share in SF.
15 months later in November 2024, Waymo is at 22% - the same as Lyft - with Uber at 55%.
Both Uber and Lyft lost low double digit % pts of market share, but it's more painful for Lyft. Lyft gave up ~1/3 of their share. Uber lost ~1/6.
This is just when comparing all rides with pickups and dropoffs inside Waymo’s SF operating boundary (ie excludes any ride to / from the airport).
Anecdotally, Waymo's wait times are longer than Uber and Lyft because they don't have enough cars on the road. But they are close enough to that acceptable threshold, that their superior product (clean, nice cars, quiet drivers, etc) tips the riders in their direction.
It's possible when Waymo puts more cars on the road and reduces wait times to be in line with Uber and Lyft, their share could climb even faster.
The good idea comes when one person feels comfortable enough to say something that might make them look stupid and their friend is open enough to recognize its potential.
The boosters of AI safety bills like SB1047 claim that open models will enable the production of biological weapons.
These claims are delusional. As a synthetic biologist and LLM engineer, I felt compelled to write why for anyone who might care:
https://t.co/PlBbF1gB76
"We estimate that the decline in Nuclear power Plants caused by Chernobyl led to the loss of approximately 141 million expected life years in the U.S., 33 in the U.K. and 318 million globally". https://t.co/vr8Z4XU9Vy
If you work in life sciences & have teenage/adult kids, they might think your company might be a bit evil b/c of what they hear about drug prices.
Show them this... w/ sound... & talk about how affordability is a function of insurance.
@IAmBiotech@AllergyAsthmaHQ@PhRMA