Courts and scholars are experimenting with artificial intelligence tools to help establish the ordinary meaning of words and phrases in statutes and contracts. A tone of cautious optimism—one ...
Support for AI among public safety professionals rose to 90% in 2024, with agencies rapidly adopting large language models (LLMs) to streamline operations and improve engagement. LLMs are being used ...
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A better method for identifying overconfident large language models
Large language models (LLMs) can generate credible but inaccurate responses, so researchers have developed uncertainty quantification methods to check the reliability of predictions. One popular ...
Researchers find large language models process diverse types of data, like different languages, audio inputs, images, etc., similarly to how humans reason about complex problems. Like humans, LLMs ...
What the firm found challenges some basic assumptions about how this technology really works. The AI firm Anthropic has developed a way to peer inside a large language model and watch what it does as ...
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, ...
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 ...
While the speed remains impractical for daily use, this proof of concept demonstrates how new inference engines are ...
Are tech companies on the verge of creating thinking machines with their tremendous AI models, as top executives claim they are? Not according to one expert. We humans tend to associate language with ...
“I’m not so interested in LLMs anymore,” declared Dr. Yann LeCun, Meta’s Chief AI Scientist and then proceeded to upend everything we think we know about AI. No one can escape the hype around large ...
A major artificial-intelligence conference has rejected 497 papers — roughly 2% of submissions — whose authors violated AI-use policies in their peer reviews of other articles submitted to the meeting ...
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