MIT, UChicago, Harvard, Diffeo Researchers Use Bayesian Inference to Cook Up Multi-Agent Collaboration
MIT, UChicago, Harvard and Diffeo *Bayesian Delegation* multi-agent learning mechanism enables agents to coordinate behaviour on the fly
AI Technology & Industry Review
MIT, UChicago, Harvard and Diffeo *Bayesian Delegation* multi-agent learning mechanism enables agents to coordinate behaviour on the fly
With deep learning emerging as something of a panacea in the world of science, AI researchers and seismologists alike are leveraging the tech in pursuit of better aftershock forecast solutions.
Because training deep learning models requires intensive computation, AI researchers are always on the lookout for new and better hardware and software platforms for their increasingly sophisticated models.
Last month, Harvard Microrobotics Lab researchers introduced RoboBee X-Wing, a solar-powered micro-aerial vehicle that fits in the palm of your hand.
Anglian Water plans to install an AI-based energy storage machine system in its water treatment facilities. The system will provide a real-time energy consumption balancing service and increase the lifespan of storage machines. The AI system was designed by Open Energi and is expected to be full operational by next year.
Benjamin Sanchez-Lengeling from Harvard University and Alán Aspuru-Guzik from the University of Toronto have successfully applied machine learning models to speed up the materials discovery process. Their paper Inverse molecular design using machine learning: Generative models for matter engineering was published July 27 in Science Vol. 361.