How AI is saving billions of years of human research time | Max Jaderberg
Mar 7, 2025
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Max Jaderberg, Chief AI Officer at Isomorphic Labs and former research scientist at DeepMind, dives into the groundbreaking role of AI in scientific discovery. He reveals how AI compresses years of research into mere seconds, particularly in protein folding and drug discovery. Jaderberg discusses the incredible efficiency of models like AlphaFold 3, which simulate real-world experiments at lightning speed, freeing researchers to tackle complex challenges. His insights promise a future where AI transforms medicine, drug design, and research as we know it.
AI models like AlphaFold drastically reduce the time needed for protein folding research, saving researchers an estimated billion years of work.
The ability of AI to simulate biological processes enables innovative drug design, allowing for tailored therapies based on individual patient profiles.
Deep dives
AI Revolutionizing Drug Discovery
AI is revolutionizing drug discovery by dramatically speeding up the process of understanding protein structures. The development of neural networks, such as AlphaFold from DeepMind, allows for rapid predictions of protein shapes, solving a long-standing challenge in scientific research. This advancement has been hailed as a breakthrough, saving researchers an estimated one billion years of experimental research time, thereby freeing human resources to tackle more complex scientific questions. With ongoing improvements, AI can create virtual models that simulate biological processes, setting the stage for innovative drug designs.
Innovative Drug Design Through AI Analogues
AI analogues enable a new paradigm in drug design by allowing simulations of complex biomolecular systems. These AI models can accurately predict interactions within molecular machines, which is essential for creating drugs that can either enhance or inhibit biological functions. For instance, by analyzing how drugs impact DNA repair proteins, researchers can develop targeted therapies for cancer that exploit specific cellular mechanisms. This approach not only accelerates the drug development process but also enhances precision by tailoring treatments to individual patient profiles.
AI's Potential Beyond Drug Discovery
The applications of AI in scientific research extend beyond drug discovery into fields like material science and energy. By leveraging vast amounts of data to create AI analogues of real-world processes, researchers can engage in open-ended experimentation and discover new insights. This flexibility allows teams to tackle various scientific challenges concurrently, potentially accelerating advancements in multiple areas simultaneously. The integration of AI into scientific research is expected to usher in a new era of technological progress, inviting professionals from various fields to contribute to this transformative experience.
Can AI compress the years long research time of a PhD into seconds? Research scientist Max Jaderberg explores how “AI analogs” simulate real-world lab work with staggering speed and scale, unlocking new insights on protein folding and drug discovery. Drawing on his experience working on Isomorphic Labs' and Google DeepMind's AlphaFold 3 — an AI model for predicting the structure of molecules — Jaderberg explains how this new technology frees up researchers' time and resources to better understand the real, messy world and tackle the next frontiers of science, medicine and more.