AI Can Revolutionise Science

Uploaded on 2024-11-22 in TECHNOLOGY-Key Areas-Artificial Intelligence, FREE TO VIEW

Artificial Intelligence (AI), one of science’s greatest achievements, is poised to come full circle to revolutionise science itself. As currently applied science, human ingenuity and new technologies offer deep insights into some of humanity’s biggest questions.

However, while we often think of scientific progress as fast and unrelenting, some commentators believe the pace of progress has slowed.

While the scientific community continues to debate the cause of this slowdown, much of today's technology, from jets to manufacturing processes, is not significantly different than half a century ago. But now, breakthroughs in developing fields like Artificial Intelligence (AI) and Quantum Computing have dramatically accelerated the pace of scientific discovery in areas including Healthcare and Cybersecurity.

The influence of AI has spread to nearly every area of science, from biology and chemistry to geology and physics. Many researchers who employ AI techniques also enjoy a “citation premium,” meaning that their papers become more influential amongst their peers. These breakthroughs are built on decades of collaboration between researchers, technologists, policymakers, civil organisations and many people from across society. They offer a blueprint for how applying AI to science can dramatically improve human life.

In recognition of this, The Royal Society - a fellowship of many of the world's most eminent scientists - is in partnership with Google DeepMind to co-host the first AI for Science Forum. This event in London brings together the scientific community, policymakers, and industry leaders to look at the transformative potential of AI to accelerate science and the role of public-private partnerships in innovation.

The Forum is intended to consider how AI can be used to accelerate the pace of scientific progress, including research in the following areas:

Protein Structure Prediction: Experts have described demystifying protein folding as a "grand challenge" for decades. In 2022, Google DeepMind shared the predicted structures of 200 million proteins from their AlphaFold 2 Model. Previously, determining the 3D structure of a single protein typically took a year or more, AlphaFold can predict these shapes with remarkable accuracy in minutes.

It does this by releasing the protein structure predictions in a free database, this has enabled scientists around the world to accelerate progress in areas like developing new medicines, fighting antibiotic resistance and tackling plastic pollution and predicting the structure of life molecules.

Healthcare Research on The Human Brain: Few things have held more mystery throughout time than the human brain. Developed over 10 years of research, Google has been working with other organisations, to map a tiny piece of the human brain to a level of detail never previously achieved. This project, released in 2024, revealed never-before-seen structures within the human brain. And the full dataset, including AI-generated annotations for each cell, has been made publicly available to help accelerate research.

Saving Lives with Accurate Flood Forecasting: When Google’s flood forecasting project began in 2018, many believed it was impossible to accurately deliver flood forecasting at scale, given the scarcity of data.
But researchers were able to develop an AI model that achieves reliability in predicting extreme riverine events in unmeasures watersheds at up to a five-day lead time with reliability matching or exceeding that of nowcasts (zero-day lead time).

In 2024, Google Research expanded this coverage to 100 countries and 700 million people globally, and improved the AI model so it offers the same accuracy at a seven-day lead time as the previous model had at five.

Spotting Wildfires to Help Firefighters Stop Them: Wildfires are increasingly upending communities around the world due to hotter and drier climates. In 2024 Google Research works with US Forest Services an AI model and new global satellite constellation designed specifically to detect and track wildfires the size of a classroom by providing higher-resolution imagery within 20 minutes. This will allow fire authorities to respond more quickly, potentially saving lives, property and natural resources.

Accurate Fast Weather Prediction: In 2023, Google DeepMind launched and open sourced the model code for GraphCast, a machine learning research model that predicts weather conditions up to 10 days in advance more accurately and much faster than the industry gold-standard weather simulation system (HRES).

GraphCast can also predict the tracks of cyclones (and associated risks like flooding) with greater accuracy, and accurately predicted Hurricane Lee would hit Nova Scotia three days before traditional models.

Advancing Mathematical Reasoning: AI has always struggled with complex math due to a lack of data and reasoning skills. Then, in 2024, Google DeepMind announced AlphaGeometry, an AI system that solved complex geometry problems at a level approaching a human Olympiad gold-medalist, a breakthrough in AI performance and the pursuit of more advanced general AI systems.

The subsequent Gemini-trained model, AlphaGeometry 2 was combined with a new model AlphaProof, and together they solved 83% of all historical International Mathematical Olympiad (IMO) geometry problems from the past 25 years. In demonstrating AI’s growing ability to reason, and potentially solve problems beyond current human abilities, this moved us closer to systems that can discover and verify new knowledge.

Using Quantum Computing to Predict Chemical Reactivity & Kinetics: Google researchers worked with UC Berkeley and Columbia University to perform the largest chemistry simulations to date on a quantum computer. The results, published in 2022, were not only competitive with classical methods, but they also did not require the burdensome error mitigation typically associated with quantum computing.

The ability to conduct these simulations will offer even more accurate predictions of chemical reactivity and kinetics, which is a precursor for applying chemistry in new ways to help solve real-world challenges.

Accelerating Materials Science: In 2023, Google DeepMind announced Graph Networks for Materials Exploration (GNoME), a new AI tool that has already discovered 380,000 materials that are stable at low temperatures, according to simulations. At a time when our world is looking for new approaches to energy, processing power and materials science, this work could pave the way to better solar cells, batteries and potential superconductors.

Plus, to help this technology benefit everyone, Google DeepMind made GNoME’s most stable predictions available via the Materials Project on their open database.

Nuclear Fusion & Clean Energy: Controlling and using the energy that fuels stars, including our own sun, has been beyond the realm of science. In 2022, Google DeepMind announced that it developed AI that can control the plasma inside a nuclear fusion reactor autonomously. By collaborating with the Swiss Plasma Center at EPFL, Google DeepMind built the first system capable of autonomously stabilising and shaping the plasma within an operational fusion reactor, taking a critical step toward stable fusion and abundant clean energy for everyone.

Conclusion

New AI technologies are influential across a range of different industries. For individuals, they provide an excellent opportunity to improve life conditions, while for businesses, implementing new technologies in AI is the way to increase profits and enhance the customer experience.

Image: Unsplash

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