Tech Xplore on MSN
A smarter way for large language models to think about hard problems
To make large language models (LLMs) more accurate when answering harder questions, researchers can let the model spend more ...
The research offers a practical way to monitor for scheming and hallucinations, a critical step for high-stakes enterprise deployments.
Tech Xplore on MSN
New Way To Increase Capabilities Of Large Language Models
Most languages use word position and sentence structure to extract meaning. For example, "The cat sat on the box," is not the same as "The box was on ...
Answer-prefix Generation (ANSPRE) generates an answer prefix for the prompt question and then retrieves relevant information from the knowledge base like Retrieval-Augmented Generation (RAG) to ...
MIT this week showcased a new model for training robots. Rather than the standard set of focused data used to teach robots new tasks, the method goes big, mimicking the massive troves of information ...
Concordia University researchers unveiled a new audio-tokenization method, FocalCodec, that compresses speech into compact tokens while preserving meaning and quality. Concordia University By using ...
Companies investing in generative AI find that testing and quality assurance are two of the most critical areas for improvement. Here are four strategies for testing LLMs embedded in generative AI ...
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 ...
It could assist the company in its efforts to embed AI in more and more of its products. As long as chatbots have been around, they have made things up. Such “hallucinations” are an inherent part of ...
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