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 ...

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 ...

Deepseek VL-2 is a sophisticated vision-language model designed to address complex multimodal tasks with remarkable efficiency and precision. Built on a new mixture of experts (MoE) architecture, this ...

B, an open-weight multimodal vision AI model designed to deliver strong math, science, document and UI reasoning with far less training data and compute than much larger systems.

Microsoft's Phi-4-reasoning-vision-15B uses careful data curation and selective reasoning to compete with models trained on ...

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 ...

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.

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 ...

Aman is the cofounder & CEO of Unsiloed AI, an SF-based, YC-backed startup building vision-based AI infrastructure for unstructured data. Much of enterprise data is in unstructured formats such as PDF ...