As technology progresses, we generally expect processing capabilities to scale up. Every year, we get more processor power, faster speeds, greater memory, and lower cost. However, we can also use ...

As large language models (LLMs) continue their rapid evolution and domination of the generative AI landscape, a quieter evolution is unfolding at the edge of two emerging domains: quantum computing ...

There is an all-out global race for AI dominance. The largest and most powerful companies in the world are investing billions in unprecedented computing power. The most powerful countries are ...

Large language models (LLMs) are all the rage in the generative AI world these days, with the truly large ones like GPT, LLaMA, and others using tens or even hundreds of billions of parameters to ...

As recently as 2022, just building a large language model (LLM) was a feat at the cutting edge of artificial-intelligence (AI) engineering. Three years on, experts are harder to impress. To really ...

Large language models such as ChaptGPT have proven to be able to produce remarkably intelligent results, but the energy and monetary costs associated with running these massive algorithms is sky high.

Large language model AIs might seem smart on a surface level but they struggle to actually understand the real world and model it accurately, a new study finds. When you purchase through links on our ...

The rise of AI has given us an entirely new vocabulary. Here's a list of the top AI terms you need to learn, in alphabetical order.

Large language models (LLMs) use vast amounts of data and computing power to create answers to queries that look and sometimes even feel “human”. LLMs can also generate music, images or video, write ...

The proliferation of edge AI will require fundamental changes in language models and chip architectures to make inferencing and learning outside of AI data centers a viable option. The initial goal ...