AI for science needs reasoning, not just data
AI is transforming science through tools like AlphaFold, which revolutionized protein structure prediction, but its success depends on rare datasets, limiting its applicability. Emerging AI agents, powered by large language models, offer a more generalist approach by simulating human scientific discovery, addressing reproducibility and open questions. These agents enhance research efficiency and enable exploration of unconventional ideas, though they face challenges like hallucinations and memory limitations that will improve over time.
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