Once a model is deployed, its internal structure is effectively frozen. Any real learning happens elsewhere: through retraining cycles, fine-tuning jobs or external memory systems layered on top. The ...
The AI world continues to evolve rapidly, especially since the introduction of DeepSeek and its followers. Many have concluded that enterprises don't really need the large, expensive AI models touted ...
The barrage of misinformation in the field of health care is persistent and growing. The advent of artificial intelligence (AI) and large language models (LLMs) in health care has expedited the ...
The global spread of health misinformation is endangering public health, from false information about vaccinations to the peddling of unproven and potentially dangerous cancer treatments.1,2 The ...
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. Ever-more ...
Small changes in the large language models (LLMs) at the heart of AI applications can result in substantial energy savings, according to a report released by the United Nations Educational, Scientific ...
Adam Stone writes on technology trends from Annapolis, Md., with a focus on government IT, military and first-responder technologies. State and local organizations need to make sense of a vast amount ...
Recently, there has been a lot of hullabaloo about the idea that large reasoning models (LRM) are unable to think. This is mostly due to a research article published by Apple, "The Illusion of ...
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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