Neural Network Architectures

Researchers demonstrate that a single transistor can mimic neural and synaptic behaviors, bringing brain-inspired computing closer to reality.

How is an AI different from a neural net? How can a machine learn? What is an AGI? And will DeepSeek really change the game? Read on to find out.

Artificial Intelligence (AI) has made remarkable strides in recent years, yet according to machine learning expert Shreyas Subramanian, there is still much to uncover.

The enormous computing resources needed to train neural networks for artificial intelligence (AI) result in massive power consumption. Researchers have developed a method that is 100 times faster and therefore much more energy efficient.

Deep neural networks can quantify facial characteristics more accurately than previous methods, improving predictions of in-person attraction, according to a study published in Evolution & Human Behavior.

Artificial Intelligence (AI) is evolving at an unprecedented pace, with large-scale models reaching new levels of intelligence and capability. From early neural networks to today's advanced architectures like GPT-4,

In the modern era, artificial intelligence (AI) has rapidly evolved, giving rise to highly efficient and scalable architectures. Vasudev Daruvuri, an expert in AI systems, examines one such innovation in his research on Mixture of Experts (MoE) architecture.

Deep neural networks have hit a wall. An entirely new, backpropagation-free AI stack promises to be orders of magnitude more performant.