Vision language models trained on traffic data help cities and transport networks move from reactive video monitoring to ...

Machine learning techniques that make use of tensor networks could manipulate data more efficiently and help open the black ...

Artificial intelligence has grown so large and power hungry that even cutting edge data centers strain to keep up, yet a technique borrowed from quantum physics is starting to carve these systems down ...

We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

From large language models to whole brain emulation, two rival visions are shaping the next era of artificial intelligence.

Language isn’t always necessary. While it certainly helps in getting across certain ideas, some neuroscientists have argued that many forms of human thought and reasoning don’t require the medium of ...

Large language models (LLMs) such as GPT-4o and other modern state-of-the-art generative models like Anthropic’s Claude, Google's PaLM and Meta's Llama have been dominating the AI field recently.

Artificial intelligence might now be solving advanced math, performing complex reasoning, and even using personal computers, but today’s algorithms could still learn a thing or two from microscopic ...

Large language models represent text using tokens, each of which is a few characters. Short words are represented by a single token (like “the” or “it”), whereas larger words may be represented by ...