Unlocking the Future of AI: From LLMs to VLMs
As artificial intelligence evolves, our understanding of it must too. While we’ve grown accustomed to tools like ChatGPT, the landscape is shifting from Language Models (LLMs) to Vision-Language Models (VLMs). Why? Because today’s AI can process images, PDFs, and videos alongside text.
Key Highlights:
- Introduction of VL-JEPA: Emphasizes perception and prediction over constant narration.
- The Stenographer Trap: Traditional models treat understanding like dictation. VL-JEPA breaks free from this limitation.
- Empirical Success: Achieves state-of-the-art performance with just 1.6 billion parameters, surpassing larger systems.
- Selective Decoding: Stays silent during unchanging moments, optimizing efficiency.
The transition from LLMs to VLMs signals a new era in AI, where understanding comes before speaking. This innovative approach is vital for the development of embodied AI and robotics.
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