NEWS IN BRIEF: AI/ML FRESH UPDATES

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Unveiling the Power of Large Language Models in Chatbots

LLMs, powered by NVIDIA GPUs, enable chatbots to converse naturally and assist in various tasks like code writing and drug discovery. Their versatility and efficiency make them essential for industries like healthcare, retail, finance, and more, revolutionizing knowledge work.

AI-Powered Audio and Text Chat Moderation for Online Communities

Online gaming and social communities utilize voice and text chat for communication. AWS services like Amazon Transcribe and Comprehend offer solutions for audio chat moderation, balancing simplicity, latency, cost, and flexibility. Sample code available on GitHub for toxic content detection in audio conversations.

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.

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.

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.