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I got fooled by AI-for-science hype–here's what it taught me
I used AI in my plasma physics research and it didn’t go the way I expected.
Lorena Barba, a professor at GWU who has previously discussed poor research practices in what she has called “Scientific Machine Learning to Fool the Masses,” saw our results as “solid evidence supporting our concerns in the computational science community over the hype and unscientific optimism” of AI. Johannes Brandstetter, a professor at JKU Linz and co-founder of a startup that provides “AI-driven physics simulations”, argued that AI might achieve better results for more complex industrial applications and that “the future of the field remains undeniably promising and brimming with potential impact.” While current LLMs, according to DeepMind, “still struggle with the deeper creativity and reasoning that human scientists rely on”, hypothetical advanced AI systems might one day be capable of fullyautomating the scientific process.
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