Browsing: ML News

In a recent study, a team of researchers from MIT introduced the linear representation hypothesis, which suggests that language models perform calculations by adjusting one-dimensional representations…

Anomaly detection in time series data is a crucial task with applications in various domains, from monitoring industrial systems to detecting fraudulent activities. The intricacies of…

Google Cloud AI Researchers have introduced LANISTR to address the challenges of effectively and efficiently handling unstructured and structured data within a framework.  In machine learning,…

Digital pathology converts traditional glass slides into digital images for viewing, analysis, and storage. Advances in imaging technology and software drive this transformation, which has significant…

Advancements in AI have led to proficient systems that make unclear decisions, raising concerns about deploying untrustworthy AI in daily life and the economy. Understanding neural…

The memory footprint of the key-value (KV) cache can be a bottleneck when serving large language models (LLMs), as it scales proportionally with both sequence length…

Transformers have greatly transformed natural language processing, delivering remarkable progress across various applications. Nonetheless, despite their widespread use and accomplishments, ongoing research continues to delve into…

Reinforcement learning (RL) is predicated on agents learning to make decisions by interacting with an environment. RL has achieved remarkable feats in various applications, including games,…

Language models (LMs) are a cornerstone of artificial intelligence research, focusing on the ability to understand and generate human language. Researchers aim to enhance these models…

Machine learning interpretability is a critical area of research for understanding complex models’ decision-making processes. These models are often seen as “black boxes,” making it difficult…