Phi-3-vision, a 4.2 billion parameter model, can answer questions about images or charts. Phi-3-vision, a 4.2 billion parameter model, can answer questions about images or charts. is a reporter who ...

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 ...

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.

Imagine pointing your phone's camera at the world, asking it to identify the dark green plant leaves, and asking if it's poisonous for dogs. Likewise, you're working on a computer, pull up the AI, and ...

VLJ tracks meaning across video, outperforming CLIP in zero-shot tasks, so you get steadier captions and cleaner ...

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 ...

Hugging Face Inc. today open-sourced SmolVLM-256M, a new vision language model with the lowest parameter count in its category. The algorithm’s small footprint allows it to run on devices such as ...

As I highlighted in my last article, two decades after the DARPA Grand Challenge, the autonomous vehicle (AV) industry is still waiting for breakthroughs—particularly in addressing the “long tail ...

Foundation models have made great advances in robotics, enabling the creation of vision-language-action (VLA) models that generalize to objects, scenes, and tasks beyond their training data. However, ...