Teaching Science to Machines
Updated: Jan 25
AI-based ‘speed-readers’ are useful because
the scientific literature is so vast. By one estimate,
new papers are published worldwide at
a rate of 1 million each year — that’s one every
30 seconds. It is practically impossible for
researchers to keep up, even in their own narrow
disciplines. So, some seek to computationally
tame the flood.
The algorithms powering such tools typically
perform two functions — they extract scientific
content and provide advanced services, such as
filtering, ranking and grouping search results.
Algorithms extracting scientific content often
exploit natural language processing (NLP)
techniques, which seek to interpret language as
humans use it, Colavizza explains.
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