InfoQ

Busting AI Myths and Embracing Realities in Privacy & Security

Katharine Jarmul keynotes on common myths around privacy and security in AI and explores what the realities are, covering design patterns that help build more secure, more private AI systems.
GitHub

Z80-μLM: A Retrocomputing Micro Language Model

Z80-μLM is a 'conversational AI' that generates short character-by-character sequences, with quantization-aware training (QAT) to run on a Z80 processor with 64kb of ram. The root behind this project ...
IEEE

AIvaluate: A Multi-Agent Framework for Automated Answer Script Evaluation Using Large Language Models and Semantic Vector Indexing

Abstract: In conventional educational environments, it is labor-intensive, subjective, and susceptible to human error to hand-mark descriptive answers. This article ...
The Lancet

Mapping the susceptibility of large language models to medical misinformation across clinical notes and social media: a cross-sectional benchmarking analysis

aThe Windreich Department of Artificial Intelligence and Human Health, Mount Sinai Health System, New York, NY, USA bThe Hasso Plattner Institute for Digital Health at Mount Sinai, Mount Sinai Health ...