Red teaming plays a pivotal role in evaluating the risks associated with AI models and systems. It uncovers novel threats, identifies gaps in current safety measures, and strengthens quantitative ...

Creating, editing, and transforming music and sounds present both technical and creative challenges. Current AI models often struggle with versatility, specializing in narrow tasks or lacking the ...

The rapid growth in AI model sizes has brought significant computational and environmental challenges. Deep learning models, particularly language models, have expanded considerably in recent years, ...

Reinforcement Learning (RL) represents a robust computational approach to decision-making formulated through the Markov Decision Processes (MDPs) framework. RL has gained prominence for its ability to ...

Semiconductors are essential in powering various electronic devices and driving development across telecommunications, automotive, healthcare, renewable energy, and IoT industries. In semiconductor ...

Predicting RNA 3D structures is critical for understanding its biological functions, advancing RNA-targeted drug discovery, and designing synthetic biology applications. However, RNA’s structural ...

Speech recognition technology has made significant progress, with advancements in AI improving accessibility and accuracy. However, it still faces challenges, particularly in understanding spoken ...

The field of structured generation has become important with the rise of LLMs. These models, capable of generating human-like text, are now tasked with producing outputs that follow rigid formats such ...

Despite the success of Vision Transformers (ViTs) in tasks like image classification and generation, they face significant challenges in handling abstract tasks involving relationships between objects ...

In an era of information overload, advancing AI requires not just innovative technologies but smarter approaches to data processing and understanding. Meet CircleMind, an AI startup reimagining ...

Neural Magic has released the LLM Compressor, a state-of-the-art tool for large language model optimization that enables far quicker inference through much more advanced model compression. Hence, the ...

Transformer architectures have revolutionized Natural Language Processing (NLP), enabling significant language understanding and generation progress. Large Language Models (LLMs), which rely on these ...