Lenny Rachitsky
Jennifer Li, Sarah Wang, and Jamie Sullivan
Julie Zhuo
Olivia Moore and Brandon Barros
Patrick Collison, Tyler Cowen, and Patrick Hsu
Computational genomics pioneer Jimmy Lin explains what many machine learning-focused biotech companies and get wrong about hiring, data, and communication.
Caltech Professor Magda Zernicka-Goetz explains recent progress in building 'synthetic' embryos from stem cells, their applications, and what they can't do.
A GPT-3-like AI model for science would accelerate innovation and improve reproducibility. Creating it will require us to unlock scientific publications.
AI-created models of the brain are emerging that have applications in art, advertising, and health. Adoption of AR and BCI will further enhance model utility.
The first half of 2022 saw momentum gains for a movement at the intersection of web3 and science: decentralized science (DeSci).
Daphne Koller explains why some fail the academia-to-biotech transition and identifies what we'll need for AlphaFold-level successes across biology and biotech.
A Q&A with Nusqe Spanton, founder and CEO of Provectus Algae.
Shared lab space, collaborative projects, DAO-funded research, and other signs of big structural change in this traditionally centralized industry.
Labs classified as BSL-4 are being built all around the world, many in countries with a history of poor controls and oversight of research practices.
We were at an inflection point with the COVID pandemic, between old and new tech, science institutions, policy, more. So what can we learn from past for future?