Explore how vision-language-action models like Helix, GR00T N1, and RT-1 are enabling robots to understand instructions and act autonomously.

Vision language models (VLMs) have made impressive strides over the past year, but can they handle real-world enterprise challenges? All signs point to yes, with one caveat: They still need maturing ...

MIT researchers discovered that vision-language models often fail to understand negation, ignoring words like “not” or “without.” This flaw can flip diagnoses or decisions, with models sometimes ...

In recent years, foundation Vision-Language Models (VLMs), such as CLIP [1], which empower zero-shot transfer to a wide variety of domains without fine-tuning, have led to a significant shift in ...

Imagine a world where your devices not only see but truly understand what they’re looking at—whether it’s reading a document, tracking where someone’s gaze lands, or answering questions about a video.

A search robot developed by researchers in Germany can reportedly track missing objects in ...

Meta’s Llama 3.2 has been developed to redefined how large language models (LLMs) interact with visual data. By introducing a groundbreaking architecture that seamlessly integrates image understanding ...

Crucially, these tests are generated by custom code and don’t rely on pre-existing images or tests that could be found on the public Internet, thereby “minimiz[ing] the chance that VLMs can solve by ...