Imagine how these two planes – the world of machines and the world of human systems – will work synergistically to realize the potential of new materials and the systems into which they will be integrated.
Imagine how these two planes – the world of machines and the world of human systems – will work synergistically to realize the potential of new materials and the systems into which they will be integrated.
Machine learning significantly reduces the time and cost involved in drug screening.
An artificial neural network based entirely on memristors is developed.
Hundreds of RNA‐binding proteins and their associated RNAs have been revealed, which enables the large‐scale prediction of RNA–protein interactions using machine learning methods.
Springer Nature have published a work written by AI.
Climbing these steps of the materials discovery ladder requires embracing a vast body of experiential knowledge accumulated over years of first-hand experimental and theoretical learning.
A calculation method based on a natural phenomenon helps to optimize lightweight laminates.
A brain-inspired, neuromorphic chip has the capability of self-learning and has been demonstrated the ability to compose music.
Scientists created flexible probabilistic bits from custom polymers, offering a new, energy-efficient path for AI and machine learning using classical physics.
Machine learning unveils the ideal structure of a quantum memristor, which could one day surpass current computing systems.