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| https://next-gpt.github.io/ |
Researchers from the National University of Singapore have developed NExT-GPT, an exciting new AI system capable of multimodal understanding and generation across text, images, audio and video. This technology, presented in a paper at NeurIPS 2022, represents a major advance towards more human-like AI.
The Limitations of Current AI Systems
While AI has made rapid progress, most systems are limited to a single modality like text or images. Humans seamlessly combine multiple modalities for communication and cognition. Bridging this gap requires multimodal systems that can process and produce varied modalities.
Recent multimodal AI models are also limited to understanding multimodal inputs without generating new content beyond text. But real-world applications demand any-to-any conversions between modalities.
Introducing Any-to-Any NExT-GPT
NExT-GPT overcomes the above limitations via its groundbreaking any-to-any multimodal capabilities. Its key features are:
- Universal multimodal understanding - It can comprehend input content from text, images, audio or video.
- Any-to-any generation - It can produce outputs in any combination of the four modalities based on the inputs.
- Modular architecture - It combines a text-based AI core with multimodal modules connected via projections.
- Minimal training - It leverages pre-trained modules, only fine-tuning 1% of parameters for alignment.
- Instruction tuning - Special datasets teach NExT-GPT to follow complex multimodal instructions.
Testing NExT-GPT's Abilities
The researchers evaluated NExT-GPT on diverse tasks like text-to-image generation, image captioning and video-to-audio conversion. It achieved excellent results comparable to state-of-the-art specialized systems.
Human evaluation also confirmed NExT-GPT's exceptional cross-modal understanding and generation capacities when presented with challenging instructions.
The Road Ahead
NExT-GPT demonstrates the exciting potential of multimodal AI systems that are not limited by modality. The authors hope it will pave the path towards more capable and versatile AI models.
Key research directions include expanding NExT-GPT's modalities, tasks, architecture variations and instruction tuning data. There is also scope to improve the quality and controllability of its generative abilities.
Overall, NExT-GPT represents a milestone in developing AI that combines modalities as seamlessly as humans. It brings us closer to artificial general intelligence.
Checkout the Research Paper , Github and Demo for more details.
All the credit for this research belongs to the researchers who worked on this project.
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