Building Generative AI models depends heavily on how fast models can reach their data. Memory bandwidth, total capacity, and ...

AI is brilliant, but it forgets. SaaS Unicorn founder Rob Imbeault thinks that’s the biggest problem in the stack.

Researchers from the University of Edinburgh and NVIDIA have introduced a new method that helps large language models reason more deeply without increasing their size or energy use. The work, ...

Artificial intelligence has learned to talk, draw and code, but it still struggles with something children master in ...

The world of AI has been moving at lightning speed, with transformer models turning our understanding of language processing, image recognition and scientific research on its head. Yet, for all the ...

What if your AI could remember every meaningful detail of a conversation—just like a trusted friend or a skilled professional? In 2025, this isn’t a futuristic dream; it’s the reality of ...

The idea of simplifying model weights isn’t a completely new one in AI research. For years, researchers have been experimenting with quantization techniques that squeeze their neural network weights ...

AI has turned computer memory from a cheap commodity into the hottest ticket in the chip world, and the shelves are starting ...

Keep AI focused with summarization that condenses threads and drops noise, improving coding help and speeding up replies on ...

The representation of individual memories in a recurrent neural network can be efficiently differentiated using chaotic recurrent dynamics.