🧠 Researchers argue LLMs may never get us to AGI

🧠 Researchers argue LLMs may never get us to AGI 21 researchers from Stanford, Oxford, DeepMind, CMU and Meta have published a paper called “Visual General Intelligence” and its argument is pretty brutal: Scaling LLMs might not be enough. GPT-style models have shown that language can unlock impressive reasoning, but the researchers argue that text is ultimately a compressed description of reality. Words don’t directly teach a model how gravity works, how objects move, or how space behaves. Humans learn many of these things before they can even speak. A baby doesn’t read about gravity. It experiences it. The paper argues that future AI should be built around raw visual experience, images, spatial information and continuous video rather than treating vision as just another input for a language model. By learning directly from the visual world, AI could develop stronger internal models of physics, cause and effect, objects and environments. Source. @aipost 🏴