NEWS IN BRIEF: AI/ML FRESH UPDATES

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Embracing AI: The Future of Art

Tate Modern's Electric Dreams exhibition explores artists embracing AI as opportunity, not threat, showcasing their longstanding relationship with technology. Director Catherine Wood highlights the symbiosis between art and technology, emphasizing their enduring connection.

Mastering Deep Quantile Forecasting

Quantile forecasting predicts distribution extremes for better decision-making in sectors like finance and supply chain management. Tensorflow, NeuralForecast, and Zero-shot LLMs offer advanced models for precise quantile estimates, enhancing operational efficiency.

Ensuring AI Trustworthiness: Pre-Deployment Assessment

Researchers from MIT and the MIT-IBM Watson AI Lab developed a technique to estimate the reliability of foundation models, like ChatGPT and DALL-E, before deployment. By training a set of slightly different models and assessing consistency, they can rank models based on reliability scores for various tasks.

The Climate vs. AI: Energy Showdown

Artificial intelligence companies aim to achieve great feats, but the energy needed threatens environmental goals. Can AI's energy problem be solved in time? Hear from the Guardian's Jillian Ambrose and Alex Hern.

Microsoft CTO Stands Firm on LLM Scaling Laws

Microsoft CTO Kevin Scott emphasizes the potential of large language model scaling laws in driving AI progress. Scott played a crucial role in the $13 billion technology-sharing deal between Microsoft and OpenAI, highlighting the impact of scaling up model size and training data on AI capabilities.

GloVe Embeddings: The Key to Codenames Hacking

Using a GloVe embedding-based algorithm, achieve 100% accuracy in the game "Codenames" by automating the roles of spymaster and operative. Representing word meaning with pre-trained GloVe embeddings to maximize accuracy in decoding clues and choosing words efficiently.

VerifAI: Biomedical QA with Verified Answers

VerifAI project, funded by the EU, creates a unique generative search engine for biomedical domain using LLMs. Focus on hallucination detection sets it apart from other RAG-based products, addressing the issue of misleading text.