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 ...
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 closely explore the rapidly emerging ...
What if you could demystify one of the most fantastic technologies of our time—large language models (LLMs)—and build your own from scratch? It might sound like an impossible feat, reserved for elite ...
The U.S. military is working on ways to get the power of cloud-based, big-data AI in tools that can run on local computers, draw upon more focused data sets, and remain safe from spying eyes, ...
A new community-driven initiative evaluates large language models using Italian-native tasks, with AI translation among the ...
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 ...
There’s a paradox at the heart of modern AI: The kinds of sophisticated models that companies are using to get real work done and reduce head count aren’t the ones getting all the attention.
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 ...
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