Thus, when an image includes two concepts (e.g. a lemon and an eggplant) while the text prompt only mentions one concept (e.g. lemon), CLIP attempts to account for the unmentioned concept (like the eggplant) by saying 'purple', a color commonly associated with eggplants.
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MULTIMODAL AI
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CLIP’s Strategy for Handling Unmentioned Visual Concepts in Images
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CLIP Training: Maximizing Image-Text Embedding Similarity
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This is because CLIP is trained using contrastive loss, where the goal is to maximize the similarity between the embeddings of images and text.
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Why CLIP Misidentifies Lemon Color: Purple Instead of Yellow
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When you ask CLIP the color of the lemon in the image below, CLIP responds with ‘purple' instead of 'yellow' (and vice versa). Why does this happen?
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Warning: Do Not Confuse Demo and Reality for Gemini
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As a reminder: believing that the Gemini video is reality and that it will really be like that is like believing that the images from the GTA VI trailer are real gameplay. Don't be fooled. (It's like believing 5 years ago that we could do that with our Google
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NOIR: Neural Signal Operated Intelligent Robots for Everyday Activities
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NOIR: Neural Signal Operated Intelligent Robots for Everyday Activities https://
bit.ly/3TbnWTi
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Gemini Multimodal Prompting: Creating with Image and Text
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Really happy to see the interest around our “Hands-on with Gemini” video. In our developer blog yesterday, we broke down how Gemini was used to create it. https://t.co/50gjMkaVc0
— Oriol Vinyals (@OriolVinyalsML) 7 décembre 2023
We gave Gemini sequences of different modalities — image and text in this case — and had it respond… pic.twitter.com/Beba5M5dHPReally happy to see the interest around our “Hands-on with Gemini” video. In our developer blog yesterday, we broke down how Gemini was used to create it. https://
developers.googleblog.com/2023/12/how-it
s-made-gemini-multimodal-prompting.html
… We gave Gemini sequences of different modalities — image and text in this case — and had it respond -
Google Introduces Gemini: Major New AI Model Advancement
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A significant #AI advance from @google
: Introducing Gemini: our largest and most capable #AI model https://
blog.google/technology/ai/
google-gemini-ai/
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Fine-tuning CLIP Model for Medical Image Search Applications
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GitHub – elsevierlabs-os/clip-image-search: Fine-tuning OpenAI CLIP Model for Image Search on medical images https://
bit.ly/3t56nd2
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Multi-modal RAG Public Benchmark Released
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Multi-modal RAG public benchmark Multi-modal LLMs are one of the most important emerging trends for the coming year. They promise to unlock new types of Q+A assistants over visual content, but multi-modal RAG architectures remain uncertain. We are releasing a small