NExT-GPT: First Any-to-Any Multimodal LLM 🤖

NExT-GPT is the first end-to-end Multimodal Large Language Model (MM-LLM) that can take inputs in arbitrary combinations of text, image, video, and audio and generate outputs in any of the same modalities. In short, it is the first any-to-any MM-LLM model.

In this video I go through some of the NExT-GPT model architecture, the proposed alignment techniques like Encoding-side LLM-centric Alignment,
Decoding-side Instruction-following Alignment, Modality-switching Instruction Tuning, and the MosIT dataset.

Hope it's useful. Please leave your comments for any clarifications.

Website: https://next-gpt.github.io
Paper Link: https://arxiv.org/pdf/2309.05519
Code: https://github.com/NExT-GPT/NExT-GPT

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📖 Deep Learning by Ian Goodfellow - https://amzn.to/3Wnyixv
📙 Pattern Recognition and Machine Learning by Christopher M. Bishop - https://amzn.to/3ZVnQQA
📗 Machine Learning: A Probabilistic Perspective by Kevin Murphy - https://amzn.to/3kAqThb
📘 Multiple View Geometry in Computer Vision by R Hartley and A Zisserman - https://amzn.to/3XKVOWi

WHO AM I?
I am a Machine Learning Researcher/practitioner who has seen the grind of academia and start-ups equally. I started my career as a software engineer 15 years ago. Because of my love for Mathematics (coupled with a glimmer of luck), I graduated with a Master's in Computer Vision and Robotics in 2016 when the now happening AI revolution just started. Life has changed for the better ever since.

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