Researchers at the Yale School of the Environment published a study “ Machine learning for sustainable development and applications of biomass and biomass-derived carbonaceous materials in water ...

Machine learning for sustainable development and applications of biomass and biomass-derived carbonaceous materials in water and agricultural systems: A review.

Machine learning accelerates catalyst discovery by combining theory, AI, and experiments to identify efficient materials for ...

While further testing is required, the research demonstrates machine learning’s potential to inform zoning and development decisions that align with emissions goals. By surfacing high-impact variables ...

A novel machine learning framework developed by IIASA researchers to estimate global rooftop area growth from 2020 to 2050 can aid in planning sustainable energy systems, urban development, and ...

Organizations are more likely to succeed in their AI efforts if they walk backwards from the solution to the problem.

Machine learning plays an important role in studying drug repurposing, especially since the occurrence of COVID-19, scientists around the world used machine learning-based approaches to signal ...

"As practical applications for machine learning rapidly increase, we expect that integrating the tremendous computational power of quantum in machine learning will offer transformative impact in ...

The potential for machine learning algorithms to accelerate drug formulation could reduce the time and cost associated with drug development, making promising new medicines available faster.

Historically, vaccine development is a lengthy and expensive process—often taking multiple years and millions of dollars to complete.