Mar 9, 2023
E6: The Computer Vision Revolution with Junnan Li and Dongxu Li of BLIP and BLIP2
As recently as January 2021, the challenge of "interpreting what is going on in a photograph" was considered "nowhere near solved." Today's guests Junnan Li and Dongxu Li changed that with their publication and open-sourcing of BLIP, which delivered state-of-the-art performance on image captioning and other vision-language tasks.
BLIP became the #18 most-cited AI paper of 2022, and now Junnan and Dongxu are back with BLIP-2, this time showing how small models can harness the power of existing foundation models to do multi-modal tasks.
We talked to Junnan and Dongxu about their research and how they see the trend toward connector models shaping the future.
(05:50) Convergence of AI techniques
(07:33) Evolution of BLIP to BLIP-2
(08:12) How BLIP-2 unlocked multimodal functionality
(12:43) The size, training dynamics, and optimization function of BLIP
(20:15) Practical/Business applications of BLIP
(29:43) Efficiency of BLIP-2 compared to other models
(41:52) Two-stage pre-training
(47:11) Architecture of Blip-2’s connector model
(58:52) Language models as the executive function of the brain
(01:07:32) Vision for an ultimate multimodal system and democratized pre-training for models
(01:12:59) Useful AI tools in these researchers’ day-to-day
(01:14:56) Upcoming projects
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@LiJunnan0409 (Junnan Li)
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Episode transcript at Cognitivervolution.ai
- Original BLIP demo
- BLIP 2 demo
- BLIP is the #18 most highly-cited paper in AI
- Image captioning comparison tool
- Understanding images with AI - for use in language models and image generation
- Image Aesthetics - Product & Model Reviews