“The human brain has 100 billion neurons, each neuron connected to 10,000 other neurons. Sitting on your shoulders is the most complicated object in the known universe.” — Michio Kaku, PhD. Since most ...

The ability to analyze the brain's neural connectivity is emerging as a key foundation for brain-computer interface (BCI) ...

“Over the past decade, deep-learning-based representations have demonstrated remarkable performance in academia and industry. The learning capability of convolutional neural networks (CNNs) originates ...

Machine learning models called convolutional neural networks (CNNs) power technologies like image recognition and language ...

Tesla did not build Dojo as a vanity project or a generic data center. It set out to create a purpose-built AI supercomputer ...

Over the last several years we have seen many new hardware architectures emerge for deep learning training but this year, inference will have its turn in the spotlight. For those chips that can manage ...

Artificial-intelligence (AI) research covers a number of topics, including machine learning (ML). ML covers a lot of ground as well, from rule-based expert systems to the latest hot trend—neural ...

The rise of dedicated chips and systems for artificial intelligence will "make possible a lot of stuff that's not possible now," said Geoffrey Hinton, the University of Toronto professor who is one of ...

Compared to a typical CPU, a brain is remarkably energy-efficient, in part because it combines memory, communications, and processing in a single execution unit, the neuron. A brain also has lots of ...

Neural network training could one day require less computing power and hardware, thanks to a new nanodevice that can run neural network computations using 100 to 1000 times less energy and area than ...