Yann LeCun, scientific leader in artificial intelligence at Meta, argues that the future of AI is not reduced to mere token prediction but to systems capable of understanding, reasoning, and interacting with a complex physical world. For LeCun, current language models are impressive but limited and simplistic tools compared to the ambition of creating machines that truly understand contexts, consequences, and objectives in real environments.
The necessary advancement involves multimodal architectures, world models that integrate visual, tactile, and spatial perception, and agents that can plan and execute actions. This implies research in symbolic and statistical reasoning, learning through interaction, and systems that combine software, sensors, and actuators to perform tasks in the physical world.
Although today the technology community is focused on large language models, LeCun predicts that in a few years the same engineers excited about the latest neural networks will turn their attention to seemingly obscure academic works that propose new ways of reasoning and linking representation and action.
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