ZeroBench, The AI Benchmark That Exposes Large Multimodal Models Weaknesses

In today’s world of artificial intelligence, benchmarks are essential for measuring AI models’ performance, especially in visual tasks that test reasoning and perception. However, large multimodal models (LMMs) struggle with image interpretation and often have weaker spatial understanding. Despite these limitations, LMMs score highly on many existing visual benchmarks, which quickly become outdated as models […]

Meta AI Launches Apollo: A Family of Video-LMMs Large Multimodal for Understanding Videos

Artificial intelligence (AI) is rapidly advancing, and within this dynamic landscape, video understanding stands as a pivotal area of innovation, exemplified by Meta AI, in collaboration with Stanford researchers, has unveiled Apollo, a family of video-centric Large Multimodal Models (LMMs). Designed to tackle the intrinsic complexities of video data—spanning both spatial and temporal dimensions. Recognizing […]