In natural language processing (NLP), Retrieval-Augmented Generation (RAG) is emerging as a powerful tool for information retrieval and contextual text generation. RAG combines the strengths of ...

Large language models (LLMs) and image generators face a critical challenge known as model collapse. This phenomenon occurs when the performance of these AI systems deteriorates due to the increasing ...

Generating versatile and high-quality text embeddings across various tasks is a significant challenge in natural language processing (NLP). Current embedding models, despite advancements, often ...

The Free Energy Principle (FEP) and its extension, Active Inference (AIF), present a unique approach to understanding self-organization in natural systems. These frameworks propose that agents use ...

The intersection of contract law, artificial intelligence (AI), and smart contracts tells a fascinating yet complex story. As technology takes on a more prominent role in transactions and ...

AMD has recently introduced its new language model, AMD-135M or AMD-Llama-135M, which is a significant addition to the landscape of AI models. Based on the LLaMA2 model architecture, this language ...

Large language models (LLMs) have gained significant attention in machine learning, shifting the focus from optimizing generalization on small datasets to reducing ...

One of the central challenges in spatiotemporal prediction is efficiently handling the vast and complex datasets produced in diverse domains such as environmental monitoring, epidemiology, and cloud ...

Weight decay and ℓ2 regularization are crucial in machine learning, especially in limiting network capacity and reducing irrelevant weight components. These techniques align with Occam’s razor ...

Multi-agent AI frameworks are essential for addressing the complexities of real-world applications that involve multiple interacting agents. Several challenges include managing and coordinating ...

Cardiotocography (CTG) is a non-invasive method used to monitor fetal heart rate and uterine contractions during pregnancy. This data can help identify potential complications early on, such as fetal ...

Approximate nearest neighbor search (ANNS) is a critical technology that powers various AI-driven applications such as data mining, search engines, and recommendation systems. The primary objective of ...