NEWS IN BRIEF: AI/ML FRESH UPDATES

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Boost AI Training with NeMo on Amazon EKS

The NVIDIA NeMo Framework simplifies distributed training of large language models, optimizing for efficiency and scalability. Amazon EKS is recommended for managing NVIDIA NeMo, offering robust integrations and performance features for running training workloads.

Revolutionizing Material Predictions with AI

Researchers from MIT developed a new machine-learning framework to predict phonon dispersion relations 1,000 times faster than other AI-based techniques, aiding in designing more efficient power generation systems and microelectronics. This breakthrough could potentially be 1 million times faster than traditional non-AI approaches, addressing the challenge of managing heat for increased efficie...

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.

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.

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.

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.