Skip to content Skip to sidebar Skip to footer

Long-Context Multimodal Understanding No Longer Requires Massive Models: NVIDIA AI Introduces Eagle 2.5, a Generalist Vision-Language Model that Matches GPT-4o on Video Tasks Using Just 8B Parameters

In recent years, vision-language models (VLMs) have advanced significantly in bridging image, video, and textual modalities. Yet, a persistent limitation remains: the inability to effectively process long-context multimodal data such as high-resolution imagery or extended video sequences. Many existing VLMs are optimized for short-context scenarios and struggle with performance degradation, inefficient memory usage, or loss…

Read More

Sensor-Invariant Tactile Representation for Zero-Shot Transfer Across Vision-Based Tactile Sensors

Tactile sensing is a crucial modality for intelligent systems to perceive and interact with the physical world. The GelSight sensor and its variants have emerged as influential tactile technologies, providing detailed information about contact surfaces by transforming tactile data into visual images. However, vision-based tactile sensing lacks transferability between sensors due to design and manufacturing…

Read More

Evaluating potential cybersecurity threats of advanced AI

Artificial intelligence (AI) has long been a cornerstone of cybersecurity. From malware detection to network traffic analysis, predictive machine learning models and other narrow AI applications have been used in cybersecurity for decades. As we move closer to artificial general intelligence (AGI), AI's potential to automate defenses and fix vulnerabilities becomes even more powerful. But…

Read More