If India’s AI ambitions needed a pre-India AI Impact Summit flex, Sarvam AI delivered it loud and clear. Days before the ...

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 ...

The field of optical image processing is undergoing a transformation driven by the rapid development of vision-language models (VLMs). A new review article published in iOptics details how these ...

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 ...

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.

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 ...

Large language models, or LLMs, are the AI engines behind Google’s Gemini, ChatGPT, Anthropic’s Claude, and the rest. But they have a sibling: VLMs, or vision language models. At the most basic level, ...

In the race to develop AI that understands complex images like financial forecasts, medical diagrams and nutrition labels, closed-source systems like ChatGPT and Claude are currently setting the pace, ...

Neuroscientists have been trying to understand how the brain processes visual information for over a century. The development of computational models inspired by the brain's layered organization, also ...

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 ...