Bio & Science


Why Applying Machine Learning to Biology is Hard – But Worth It

Jimmy Lin and Nicole Neuman

Computational genomics pioneer Jimmy Lin explains what many machine learning-focused biotech companies and get wrong about hiring, data, and communication.

What Synthetic Embryos Can and Can’t Do, Now and in the Future

Magda Zernicka-Goetz and Nicole Neuman

Caltech Professor Magda Zernicka-Goetz explains recent progress in building 'synthetic' embryos from stem cells, their applications, and what they can't do.

How to Build a GPT-3 for Science

Josh Nicholson

A GPT-3-like AI model for science would accelerate innovation and improve reproducibility. Creating it will require us to unlock scientific publications.

AI’s Next Frontier: Brains on Demand

Patrick Mineault

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.

Mid-year Recap: Web3 and Science Collide

Future Editorial

The first half of 2022 saw momentum gains for a movement at the intersection of web3 and science: decentralized science (DeSci).

The Two Things We’ll Need for the Next AlphaFold

Daphne Koller and Nicole Neuman

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.

Can Synthetic Biology and Pond Scum Deliver Carbon-Neutral Manufacturing?

Nusqe Spanton and Nicole Neuman

A Q&A with Nusqe Spanton, founder and CEO of Provectus Algae.

A Guide to Decentralized Biotech

Jocelynn Pearl

Shared lab space, collaborative projects, DAO-funded research, and other signs of big structural change in this traditionally centralized industry.

Global Labs Pose Major Threat — Here’s What U.S. Should Do

Scott Gottlieb

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.

Uncontrolled Spread: Science, Policy, Institutions, Infrastructure

Scott Gottlieb, Vineeta Agarwala, Marc Andreessen, and Vijay Pande

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?