large language models
64 mentions across all digests
Large language models are neural networks trained on vast text data used for tasks including mathematical reasoning, root cause analysis knowledge base construction, and clinical trial recruitment from patient narratives.
Introducing Background Temperature to Characterise Hidden Randomness in Large Language Models
Researchers introduce background temperature as a new parameter to measure inherent stochasticity in LLMs that standard temperature controls don't capture.
Simulacrum of Knowledge Work
LLMs have decoupled writing quality from substance, generating plausible-but-hollow content that forces expensive re-verification to distinguish genuine analysis from convincing simulacra.
What's missing in the 'agentic' story: a well-defined user agent role
Current AI agent discourse lacks the governance frameworks (standards, transparency, market competition) that web browsers use to protect user interests against producer incentives.
Agentic AI for Personalized Physiotherapy: A Multi-Agent Framework for Generative Video Training and Real-Time Pose Correction
Multi-agent AI system generates personalized exercise videos and delivers real-time pose corrections for unsupervised at-home physiotherapy, replacing human therapist oversight.
AFRILANGTUTOR: Advancing Language Tutoring and Culture Education in Low-Resource Languages with Large Language Models
LLMs enable culturally-aware language tutoring for underserved African communities, addressing the AI accessibility gap in low-resource linguistic regions.