Markdown

VLM

VLM is the Acronym for Vision-Language Model

A type of artificial intelligence system that can jointly interpret and generate information from both images and text, extending the capabilities of large language models (LLMs), which are limited to text. It is an example of multimodal learning. Many widely used commercial applications now rely on this ability. OpenAI introduced computer vision capabilities to its GPT-4V variant of the GPT-4 model, enabling users to incorporate uploaded photographs or diagrams into their discussions with ChatGPT. It has since become an integral part of ChatGPT's standard offering. Similar capabilities were added to Google’s Gemini, Anthropic’s Claude 3 Opus, and Microsoft’s Copilot with Vision. Alongside these models, several open-source vision-language models, such as LLaVA, InstructBLIP, and MiniGPT-4, have been released by the research community, offering smaller-scale applications.

An AI model trained to understand and reason across both images and text at once, taking a picture, a question about it, or both together, and producing a text response, a description, or a structured answer. VLMs power tools that can describe photos, answer questions about a screenshot, read charts, or generate alt text automatically.

How a VLM Works

  • Vision Encoder: Converts an image into a numerical representation the model can process, often using a CNN- or transformer-based architecture.
  • Alignment Layer: Maps the image representation into the same space the language model uses for text, so the two modalities can be reasoned about together.
  • Language Model: An LLM that generates a text response grounded in both the image content and any accompanying text prompt.

Applications in Marketing

  • Automated Alt Text and Accessibility: Generating accurate image descriptions at scale for accessibility and SEO.
  • Creative and Ad Review: Automatically checking creative assets for brand compliance, content policy, or placement fit.
  • Visual Search and Cataloging: Letting customers search a product catalog with a photo, or auto-tagging product images at scale.