The AI Hype Index: Robot pets, simulated humans, and Apple’s AI text summaries
1 Mins read
Separating AI reality from hyped-up fiction isn’t always easy. That’s why we’ve created the AI Hype Index—a simple, at-a-glance summary of everything…
ByteDance Research Introduces 1.58-bit FLUX: A New AI Approach that Gets 99.5% of the Transformer Parameters Quantized to 1.58 bits
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Vision Transformers (ViTs) have become a cornerstone in computer vision, offering strong performance and adaptability. However, their large size and computational demands…
Revolutionizing LLM Alignment: A Deep Dive into Direct Q-Function Optimization
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Aligning large language models (LLMs) with human preferences is an essential task in artificial intelligence research. However, current reinforcement learning (RL) methods…
Hugging Face Just Released SmolAgents: A Smol Library that Enables to Run Powerful AI Agents in a Few Lines of Code
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Creating intelligent agents has traditionally been a complex task, often requiring significant technical expertise and time. Developers encounter challenges like integrating APIs,…
Meet the Pirates of the RAG: Adaptively Attacking LLMs to Leak Knowledge Bases
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Retrieval-augmented generation (RAG) enhances the output of Large Language Models (LLMs) using external knowledge bases. These systems work by retrieving relevant information…
Meet HuatuoGPT-o1: A Medical LLM Designed for Advanced Medical Reasoning
3 Mins read
Medical artificial intelligence (AI) is full of promise but comes with its own set of challenges. Unlike straightforward mathematical problems, medical tasks…
Sepsis ImmunoScore: The First FDA-Authorized AI Tool for Early Sepsis Detection and Risk Assessment
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Sepsis is a critical medical condition resulting from an abnormal immune response to infection, often causing organ dysfunction and high morbidity and…
CMU Researchers Introduce TNNGen: An AI Framework that Automates Design of Temporal Neural Networks (TNNs) from PyTorch Software Models to Post-Layout Netlists
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Designing neuromorphic sensory processing units (NSPUs) based on Temporal Neural Networks (TNNs) is a highly challenging task due to the reliance on…
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
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Artificial Life (ALife) research explores the emergence of lifelike behaviors through computational simulations, providing a unique framework to study “life as it…
AutoSculpt: A Pattern-based Automated Pruning Framework Designed to Enhance Efficiency and Accuracy by Leveraging Graph Learning and Deep Reinforcement Learning
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Deploying Deep Neural Networks (DNNs) on edge devices, such as smartphones and autonomous vehicles, remains a significant challenge due to their computationally…