Multimodal
Vision-language model
A vision-language model processes images and text together.
Quick definition
A vision-language model processes images and text together.
- Category: Multimodal
- Focus: cross-modal understanding
- Used in: Analyzing screenshots or images with text questions.
What it means
It is used for image captioning, visual Q&A, and more. In multimodal workflows, vision-language model often shapes cross-modal understanding.
How it works
Multimodal models align text, vision, and audio signals so one system can reason across modalities.
Why it matters
Multimodal features unlock workflows across text, audio, and images.
Common use cases
- Analyzing screenshots or images with text questions.
- Transcribing speech and summarizing meetings.
- Generating voice responses from text outputs.
Example
Analyze a screenshot and summarize issues.
Pitfalls and tips
Noisy inputs lead to unreliable results. Provide clear images, clean audio, and explicit instructions.
In BoltAI
In BoltAI, this appears when working with audio, images, or voice.
