Artificial Intelligence (AI) is being utilized by scientists in areas such as drug discovery and material development to speed up their research processes.
The application: AI has significantly reduced the time taken to develop potential drugs for diseases, demonstrated by Susana Vazquez-Torres, a graduate student at the University of Washington.
* Torres has used AI to identify candidate drugs for snakebite within a few months, a process which would traditionally take years.
* For protein design, specific AI technology, known as diffusion modeling, is being employed to construct proteins with desired shapes from scratch, increasing research speed and efficiency.
Technical challenges: While AI has revolutionised scientific discovery in some areas, not all fields have equally benefited due to certain limitations.
* Maria Chan from Argonne National Laboratory highlighted a lack of sufficient research to base AI calculations on in her work with materials for the renewable economy.
* The complexity of interactions within materials, at large and molecular scales, also makes them hard to study using AI.
Future of AI in sciences: Some experts believe AI will take on a more central role in scientific discoveries, with the potential to develop new hypotheses by analyzing scientific literature spanning decades.
* However, AI models will need to improve their reasoning abilities to avoid known issues of data fabrication and errors.
* It’s envisaged that AI could automate data reanalysis, providing updated results on ongoing issues like diseases or environmental change.
The human role: Despite increased automation, humans still play a vital role in determining the validity of AI-suggested lines of research, and in exploring the wide array of problems that AI can potentially help to solve.
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