Ever since AI has emerged as a field of study, researchers have dreamed of creating models to accelerate humanity’s drive for new knowledge.
The incredible power of these models to crunch through data and model things at various scales, go far beyond human comprehension.
Most exciting is the promise of AI taking on the role of a scientist. Taking a high-level objective defined by the researcher, experiments are autonomously run until they match the desired result.
Exciting as all this is though, AI’s takeover of science could have potential downsides. Neural networks, commonly used by scientists, are black boxes whose internal workings are hard to decipher.
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