美語狂人雜記

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美語狂人手札 發表在 痞客邦 留言(0) 人氣()

美語狂人手札 發表在 痞客邦 留言(0) 人氣()

美語狂人手札 發表在 痞客邦 留言(0) 人氣()

美語狂人手札 發表在 痞客邦 留言(0) 人氣()

美語狂人手札 發表在 痞客邦 留言(0) 人氣()

美語狂人手札 發表在 痞客邦 留言(0) 人氣()

美語狂人手札 發表在 痞客邦 留言(0) 人氣()

美語狂人手札 發表在 痞客邦 留言(0) 人氣()

In this week’s online AI session, we discussed a research study using MRI-based “habitat analysis” to predict the progression of white-matter hyperintensities in patients with cerebral small-vessel disease and examine their relationship with cognitive decline.

Beyond the medical findings, the paper opened up a much larger question for our discussion:What happens to human expertise when computational systems can identify patterns hidden inside increasingly complex data?

AI can help us detect, classify, and predict. But interpretation is another matter. Understanding whether a pattern is meaningful, questioning the assumptions behind a model, and deciding how its findings should be used still require human knowledge and judgment.

Perhaps that is one of the most important ways to understand AI today:not as intelligence replacing intelligence, but as a new layer of intelligence that humans must learn to work with.

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美語狂人手札 發表在 痞客邦 留言(0) 人氣()

美語狂人手札 發表在 痞客邦 留言(0) 人氣()

美語狂人手札 發表在 痞客邦 留言(0) 人氣()