In 2024, Google DeepMind scientists shared the Nobel Prize in Chemistry for a neural network, AlphaFold, which predicts the structures of proteins. It showed that AI could make groundbreaking scientific discoveries, but AlphaFold may not be the best template for accelerating science. Instead, another approach may hold the key: AI agents.
AlphaFold relied on a dataset of roughly 170,000 experimentally validated protein structures that took 53 years and roughly $21 billion worth of experimental work to assemble. Comparable datasets will be difficult or impossible to create in many fields.
AI agents can instead model the iterative, highly contingent process of actual research. While tools like AlphaFold apply a powerful approach to a limited question, agents are inherently generalists. They do not represent a new way to do science—instead, they digitally model the human process of discovery.
Read the full op-ed on how agents could accelerate scientific discovery.
Inside the “censorship-industrial complex” idea shaping US policy
For years, the idea of a “censorship-industrial complex” that suppressed conservative and populist speech spread in right-wing circles online. But now, the theory has made its way into the Trump administration.
Over the past nine months, MIT Technology Review investigated its origins and traced its rise. In a virtual Roundtables session on Thursday, August 13, senior reporter Eileen Guo and executive editor Amy Nordrum will explore what they discovered, where the theory is going, and what it could mean for the future of democracy and the internet.
Register here to join the session at 19:00 GMT / 2:00 pm ET / 11:00 am PT.
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