Software simulates 370,000 steps in under 100 hours, potentially cutting demand for time on supercomputers by orders of ...

The historical pursuit of creating intelligent machines has culminated in the modern era of artificial intelligence. However, the efficacy of AI applications is contingent upon a nuanced understanding ...

A concept developed for computer science could have a key role in fundamental physics — and point the way to a new understanding of space and time. When physicist Leonard Susskind gives talks these ...

In computational complexity theory, P and NP are two classes of problems. P is the class of decision problems that a deterministic Turing machine can solve in polynomial time. In useful terms, any ...

Our era is defined by a constant flow of information. Data from smartphones, wearables and environmental sensors, connected to sharing and analysis platforms, accompany us daily, creating a digital ...

A major advance reveals deep connections between the classes of problems that computers can — and can’t — possibly do. At first glance, the big news coming out of this summer’s conference on the ...

Karlo Doroc receives funding from a University of Melbourne Graduate Research Scholarship from the Faculty of Business and Economics, a Kinsman Scholarship, and Australian Government Research Training ...

Deep learning has been successfully applied in the field of medical diagnosis, and improving the accurate classification of ...

One of the biggest prizes in maths has been awarded to two people for their “foundational contributions to theoretical computer science and discrete mathematics”. László Lovász at the Alfréd Rényi ...

Computational neuroscientists taught an artificial neural network to imitate a biological neuron. The result offers a new way to think about the complexity of single brain cells. Our mushy brains seem ...