AGI is Not Multimodal
Benjamin Spiegel on what disembodied definitions of AGI miss
"In projecting language back as the model for thought, we lose sight of the tacit embodied understanding that undergirds our intelligence." –Terry Winograd
The recent successes of generative AI models have convinced some that AGI is imminent. While these models appear to capture the essence of human intelligence, they defy even our most basic intuitions about it. They have emerged not because they are thoughtful solutions to the problem of intelligence, but because they scaled effectively on hardware we already had. Seduced by the fruits of scale, some have come to believe that it provides a clear pathway to AGI. The most emblematic case of this is the multimodal approach, in which massive modular networks are optimized for an array of modalities that, taken together, appear general. However, I argue that this strategy is sure to fail in the near term; it will not lead to human-level AGI that can, e.g., perform sensorimotor reasoning, motion planning, and social coordination. Instead of trying to glue modalities together into a patchwork AGI, we should pursue approaches to intelligence that treat embodiment and interaction with the environment as primary, and see modality-centered processing as emergent phenomena.
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This seems like a crucial point... if you put a human in a sealed and noise insulated black box and all that could reach them was black and white text on a screen you'd have something like the ceiling of capabilities for current LLM architecture? How richly would they be able to understand or engage with the ongoing world outside? While stanning scale and buying more GPUs may be the status quo for industrialists, seems extremely unlikely to yield anything more than that! Thanks for writing...