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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 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 ...
ChemELLM, a 70-billion-parameter LLM tailored for chemical engineering, outperforms leading LLMs (e.g., Deepseek-R1) on ChemEBench across 101 tasks, trained on ChemEData’s 19 billion pretraining and 1 ...
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 ...
Explore the evolution of data engineering, focusing on agentic systems and AI pipelines for enhanced analytics and enterprise ...
In a landmark study, OpenAI researchers reveal that large language models will always produce plausible but false outputs, even with perfect data, due to fundamental statistical and computational ...
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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