Here’s how AI helped Google make remarkable scientific discoveries in 2024
Google has unveiled notable scientific breakthroughs made this year that were made possible thanks to advances in artificial intelligence (AI) technology. On Monday, Google DeepMind co-hosted the first edition of the AI for Science Forum in London with the Royal Society. During the event, the Mountain View-based tech giant summarized achievements such as using an AI model to predict protein structures, expanding its flood forecasting system and wildfire detection and tracking system. DeepMind also managed to build a system that can control plasma with a nuclear fusion reactor.
Google outlines its most important scientific breakthroughs in 2024
The tech giant declared that AI has played a key role in solving many confusing problems in science over the past year using computer techniques. The company also emphasized that AI is not a replacement for scientists, but can become a crucial assistant for them.
One of Google DeepMind’s biggest achievements was when the tech giant’s AI research division used its AlphaFold 2 AI model to predict structures of 200 million proteins. The company emphasized that this discovery has advanced the scientific community for decades, as determining the 3D structure of a single protein can take up to a year. In particular, Demis Hassabis and John Jumper, the people behind the project, received the 2024 Nobel Prize in Chemistry for this discovery.
Google also worked with Harvard’s Lichtman Lab to map a slice of the human brain with an unprecedented level of detail. Released this year, the project revealed previously invisible structures in the human brain.
In 2024, AI also helped Google improve its prediction and tracking systems. The company’s river flood forecasting system was widely expanded in 2024 and now covers 100 countries and 700 million people worldwide. The tech giant also partnered with the US Forest Service to develop the FireSat AI model that can detect and track wildfires as small as a classroom in 20 minutes.
GraphCast, a machine learning research model developed by Google DeepMind, can now predict the tracks of cyclones. The company claims it can predict such weather-related disruptions faster and more accurately compared to traditional weather simulation systems.
Advances were also made in mathematical reasoning and quantum computing. DeepMind’s AlphaGeometry AI system, launched in 2024, solved complex geometry problems at a level comparable to that of a human gold medalist at the Olympics. Google researchers also worked with UC Berkeley and Columbia University to run chemical simulations on a quantum computer to predict chemical reactivity and kinetics.
With an eye on sustainable energy, the tech giant announced the Graph Networks for Materials Exploration (GNoME), which discovered 3,80,000 materials that are stable at low temperatures, opening new avenues to make better solar cells, batteries and potential superconductors.
The tech giant also made breakthroughs in nuclear fusion, which is considered the energy of the future. In collaboration with the Swiss Plasma Center at the Swiss Federal Institute of Technology Lausanne, Google DeepMind has announced the development of an AI system that can control the plasma in a nuclear fusion reactor without any manual assistance. This is still a work in progress, but the company said it is a crucial step toward stable fusion and abundant clean energy.
