· mit researchers developed an efficient approach for training more reliable reinforcement learning models, focusing on complex tasks that involve variability. · a graph-based ai model (center) recommended creating a new mycelium-based biological material (right), using inspiration from the abstract patterns found in wassily kandinsky’s painting, “composition vii” (left). · mit news explores the environmental and sustainability implications of generative ai technologies and applications. This could enable the leverage of reinforcement learning across a wide range of applications. · after uncovering a unifying algorithm that links more than 20 common machine-learning approaches, mit researchers organized them into a “periodic table of machine learning” that can help scientists combine elements of different methods to improve algorithms or create new ones. · how ai could speed the development of rna vaccines and other rna therapies mit engineers used a machine-learning model to design nanoparticles that can deliver rna to cells more efficiently.
Ai Is Discovering New Physics And Its Completely Unexpected
· mit researchers developed an efficient approach for training more reliable reinforcement learning models, focusing on complex tasks that involve variability. · a graph-based ai...
