Reducing the precision of model weights can make deep neural networks run faster in less GPU memory, while preserving model accuracy. If ever there were a salient example of a counter-intuitive ...

What if the future of artificial intelligence wasn’t about building bigger, more complex models, but instead about making them smaller, faster, and more accessible? The buzz around so-called “1-bit ...

Large language models (LLMs) aren’t actually giant computer brains. Instead, they are massive vector spaces in which the probabilities of tokens occurring in a specific order is encoded. Billions of ...

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I explore the exciting and rapidly ...

I remember being in my early 20s, sitting under an expansive sky, reading a strange yet captivating book titled The Dancing Wu Li Masters by Gary Zukuv. It didn’t promise physics in the conventional ...

LLMs have delivered real gains, but their momentum masks an uncomfortable truth: More data, more chips and bigger context windows don’t fix what these systems lack—persistent memory, grounded ...