If you want to understand the universe, you can start by reading the greats: Feynman, Weinberg, Curie, Hofstadter, Kant, Spinoza, Turing, and all the great scientists and philosophers who pushed the boundaries of human knowledge. expanded and on whose shoulders modern civilization stands
But during this journey you will also discover that despite all this incredible progress, there are amazing limits to what we know. We’re still no closer to answering some big questions, like the nature of time, consciousness, or the fabric of reality.
To make progress toward answering these profound questions, new tools and methods will almost certainly be needed. Artificial intelligence (AI) is one such tool, and we’ve always believed that it actually does Final A tool to help accelerate scientific discovery.
We have been working towards this goal for over 20 years. DeepMind (now Google DeepMind) was founded with the mission of responsibly creating Artificial General Intelligence (AGI), a system that can perform almost any human-level cognitive task. The great promise of such systems is that they can then be used to advance our understanding of the world around us and help us solve some of society’s biggest challenges.
In 2016, we saw AlphaGo, the first AI system to defeat a world champion in the complex game of Go, and its famous creativity. Move 37. In Game 2, we realized that there are techniques and methods to start using AI to tackle open-ended problems in science.
At the top of the list was the 50-year grand challenge of protein folding. Proteins are the building blocks of life. They underlie every biological process in every living thing, from your muscle fibers to the neurons that fire in your brain. Each protein is specified by its amino acid sequence (roughly its genetic sequence) and spontaneously folds into a three-dimensional structure. The shape of a protein is important because it tells you a lot about what the protein does—information that’s important for things like understanding diseases and drug discovery.
Predicting the 3D shape of a protein directly from its 1D amino acid sequence is known as the “protein folding problem”. This is incredibly challenging because the average protein is predicted to have more possible ways to fold than there are atoms in the universe.
Finding the structure of a protein experimentally can take years of painstaking and expensive work. It can usually take a graduate student their entire PhD to develop just one structure. After a monumental collective effort spanning several decades, structural biologists have determined nearly 170,000 of these structures and deposited them in the Protein Data Bank (PDB).
AlphaFold was our solution to this problem—and it was recognized with this year’s Nobel Prize in Chemistry. AlphaFold learns a complex model of a protein from structures in the PDB and other relevant data. It can then, within minutes, predict the structure of a novel protein to atomic precision (i.e., within an average atom’s width). Because AlphaFold is so fast and accurate, over the course of a year, we were able to use it to predict the structure of almost every protein known to science: more than 200 million proteins—a task that took approx. It must have taken a billion years. At the time of the Ph.D.
To make the most beneficial impact on society, we have made AlphaFold and all its predicted structures freely and openly available to everyone in the world, in partnership with the European Bioinformatics Institute (EMBL-EBI). Made available. In just three years, more than 2 million researchers in 190 countries have used it to advance their groundbreaking work, from designing enzymes to tackle plastic pollution to creating a molecular syringe that delivers therapeutic proteins. able to be delivered directly into human cells, leading to the development of an effective malaria vaccine. Resistance, and more. We established Isomorphic Labs to build on these successes and use AI to revolutionize the drug discovery process, making it faster and less expensive. We call it: science at digital speed.
In fact, with AI as a tool, scientists are making great strides in almost every field of scientific endeavor. At Google DeepMind and Google Research, working with academic colleagues, we control the shape of plasma in fusion reactors, discover fast matrix multiplication algorithms, make mathematical discoveries, discover new materials, explore quantum dynamics, Using AI to understand behavior Brain, draft the first reference pengenome, advance the mapping of the synaptic level of the human brain, and improve weather forecasting.
Such developments are beginning to have very real, beneficial effects on people’s lives. For example, flood forecasting is becoming a frequent and urgent problem due to climate change. Yet only a small fraction of the world’s rivers have flow gauges that can provide a direct form of early warning. Using publicly available data, we used AI to accurately predict river floods up to seven days in advance. Scaling up from an initial pilot in Bangladesh, our Early Warning Flood Hub platform now covers hundreds of millions of people in more than 80 countries around the world, including in vulnerable and data-poor regions.
Of course, as we take bold leaps in scientific advancement, we must also accept our collective responsibility to build AI in a way that benefits humanity and avoids potential harm and misuse. . Along with scientists and technologists, we need to make sure to bring philosophers, ethicists, social scientists, and national scientific academies into the conversation about the future of AI.
A safe and prosperous future with AI is only possible if industry works together with government, academia and civil society to move forward. This includes working towards a regulatory framework that fosters innovation and advances AI-enabled opportunities that benefit everyone.
AI will be one of the most transformative technologies ever invented. We should approach it seriously and respect it. While there are many challenges to overcome, both technical and ethical, we believe that with enough time and care, human ingenuity will solve them. We have to be both bold and responsible.
As AI itself accelerates the pace of development, new discoveries will build on each other in a virtuous cycle. We may be on the threshold of a new golden age of discovery, bringing us closer than ever to understanding some of the deepest mysteries of the universe and our place in it.
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