NEWS IN BRIEF: AI/ML FRESH UPDATES

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AI Assistant Chats Vulnerable to Hackers

AI assistants are accessing private thoughts and business secrets, with researchers uncovering a flaw in OpenAI's encryption. Attack can decipher responses with high accuracy, exposing sensitive topics and potentially compromising privacy.

The AI Challenge: Princess of Wales Photo Furore

AI exacerbates difficulty in detecting manipulated media; Princess Diana photo controversy highlights image doctoring sensitivity. Catherine's edited wedding photo scandal in 2011 foreshadows current unease with AI advancements.

Unraveling Causality: Harnessing Causal Graphs in Machine Learning

Article explores integration of causal reasoning into ML with causal graphs. Causal graphs help disentangle causes from correlations, essential in causal inference. ML lacks ability to answer causal questions due to spurious correlations, confounders, colliders, and mediators. Structural causal models (SCM) offer a solution by modeling causal relationships and accounting for complexities.

Enhancing Truthfulness in LLM Applications

Enhancing truthfulness in Retrieval Augmented Generation (RAG) outputs by mitigating hallucinations and reliance on pre-trained knowledge. Emphasizing groundedness and completeness in RAG outputs through fine-tuning Large Language Models and element-aware summarization, with scalable evaluation metrics like LENS and CoT.