Browsing: ML News
Transformer models find applications in various applications, ranging from powerful multi-accelerator clusters to individual mobile devices. The varied requirements for inference in these settings make developers…
Multimodal graph learning is a multidisciplinary field combining concepts from machine learning, graph theory, and data fusion to tackle complex problems involving diverse data sources and…
Large language models are sophisticated artificial intelligence systems created to understand and produce language similar to humans on a large scale. These models are useful in…
Sequential decision-making problems are undergoing a major transition due to the paradigm shift brought about by the introduction of foundation models. These models, such as transformer…
Researchers from the National University of Singapore introduced Show-1, a hybrid model for text-to-video generation that combines the strengths of pixel-based and latent-based video diffusion models…
One of the biggest challenges in Machine Learning has always been to train and use neural networks efficiently. A turning point was reached with the introduction…
Researchers from Nvidia and the University of Illinois at Urbana Champaign introduce Retro 48B, a significantly larger language model than previous retrieval-augmented models like Retro (7.5B…
The development of functional proteins has long been a critical pursuit in various scientific fields, including healthcare, biotechnology, and environmental sustainability. However, conventional approaches to protein…
Machine learning is used in almost every aspect of our lives and across various fields. It’s a technology becoming increasingly prevalent and finding applications in many…
Unlocking AI Transparency: How Anthropic’s Feature Grouping Enhances Neural Network Interpretability
In a recent paper, “Towards Monosemanticity: Decomposing Language Models With Dictionary Learning,” researchers have addressed the challenge of understanding complex neural networks, specifically language models, which…