2 years ago

Category: Data, artificial-intelligence

The power of https://thenewstack.io/category/machine-learning/ has become increasingly evident in many aspects of our lives, whether it is the algorithms driving https://thenewstack.io/40-something-dude-asks-for-music-recommendation-redditors-point-to-the-algorithms/ and https://thenewstack.io/rebuilding-ai-toward-a-feminist-alexa/, or the complex computations that propel new discoveries in https://thenewstack.io/machine-learning-for-drug-discovery-using-the-google-kubernetes-engine/. The research team is proposing what they call the “Time Machine framework,” which will use AI to help decision-makers and experts from different disciplines to “go back in time” (so to speak) in order to compile pre-existing environmental data in a way that would allow them to quantifiably observe how environmental changes have impacted biodiversity and various ecosystems over long periods of time. A better understanding of such historical pieces of data over time will help better predict what kinds of mitigation strategies would work best.

“Only by quantifying the system-level biodiversity change before, during, and after pollution events, can the causes of biodiversity and ecosystem service loss be identified.”

“The Time Machine framework can be, in principle, extended beyond predictions based on the ecological and functional status of ecosystems,” suggested Orsini.