Federated learning has emerged as an approach for collaborative training among medical institutions while preserving data privacy. However, the non-IID […]
Category: Staff
Meta AI Introduces a Paradigm Called ‘Preference Discerning’ Supported by a Generative Retrieval Model Named ‘Mender’
Sequential recommendation systems play a key role in creating personalized user experiences across various platforms, but they also face persistent […]
ByteDance Research Introduces 1.58-bit FLUX: A New AI Approach that Gets 99.5% of the Transformer Parameters Quantized to 1.58 bits
Vision Transformers (ViTs) have become a cornerstone in computer vision, offering strong performance and adaptability. However, their large size and […]
Revolutionizing LLM Alignment: A Deep Dive into Direct Q-Function Optimization
Aligning large language models (LLMs) with human preferences is an essential task in artificial intelligence research. However, current reinforcement learning […]
Hugging Face Just Released SmolAgents: A Smol Library that Enables to Run Powerful AI Agents in a Few Lines of Code
Creating intelligent agents has traditionally been a complex task, often requiring significant technical expertise and time. Developers encounter challenges like […]
Meet the Pirates of the RAG: Adaptively Attacking LLMs to Leak Knowledge Bases
Retrieval-augmented generation (RAG) enhances the output of Large Language Models (LLMs) using external knowledge bases. These systems work by retrieving […]
Meet HuatuoGPT-o1: A Medical LLM Designed for Advanced Medical Reasoning
Medical artificial intelligence (AI) is full of promise but comes with its own set of challenges. Unlike straightforward mathematical problems, […]
Sepsis ImmunoScore: The First FDA-Authorized AI Tool for Early Sepsis Detection and Risk Assessment
Sepsis is a critical medical condition resulting from an abnormal immune response to infection, often causing organ dysfunction and high […]
CMU Researchers Introduce TNNGen: An AI Framework that Automates Design of Temporal Neural Networks (TNNs) from PyTorch Software Models to Post-Layout Netlists
Designing neuromorphic sensory processing units (NSPUs) based on Temporal Neural Networks (TNNs) is a highly challenging task due to the […]
Researchers from MIT, Sakana AI, OpenAI and Swiss AI Lab IDSIA Propose a New Algorithm Called Automated Search for Artificial Life (ASAL) to Automate the Discovery of Artificial Life Using Vision-Language Foundation Models
Artificial Life (ALife) research explores the emergence of lifelike behaviors through computational simulations, providing a unique framework to study “life […]