What's missing for AGI
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What's missing for AGI
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Current transformer-based, self-supervised systems have driven massive gains, but important gaps remain on the path to AGI. Key missing pieces are continual, curiosity-driven learning; grounded multimodal perception; reliable, contextual long-term memory with forgetting; motivated (hot) executive control and dynamic attention; metacognition and coherent causal world-models; and robust fluid reasoning, planning and decision-making. Progress will require hybrid architectures (neuromorphic/Hebbian + gradients + symbolic modules), active-inference and intrinsic-motivation objectives, and new lifelong, embodied benchmarks to evaluate safety and competence.
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Current transformer-based, self-supervised systems have driven massive gains, but important gaps remain on the path to AGI. Key missing pieces are continual, curiosity-driven learning; grounded multimodal perception; reliable, contextual long-term memory with forgetting; motivated (hot) executive control and dynamic attention; metacognition and coherent causal world-models; and robust fluid reasoning, planning and decision-making. Progress will require hybrid architectures (neuromorphic/Hebbian + gradients + symbolic modules), active-inference and intrinsic-motivation objectives, and new lifelong, embodied benchmarks to evaluate safety and competence.
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https://huggingface.co/blog/KnutJaegersberg/whats-missing-for-agi-in-todays-tech-trajectories
https://huggingface.co/blog/KnutJaegersberg/whats-missing-for-agi-in-todays-tech-trajectories
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What's missing for AGI

Current transformer-based, self-supervised systems have driven massive gains, but important gaps remain on the path to AGI. Key missing pieces are continual, curiosity-driven learning; grounded multimodal perception; reliable, contextual long-term memory with forgetting; motivated (hot) executive control and dynamic attention; metacognition and coherent causal world-models; and robust fluid reasoning, planning and decision-making. Progress will require hybrid architectures (neuromorphic/Hebbian + gradients + symbolic modules), active-inference and intrinsic-motivation objectives, and new lifelong, embodied benchmarks to evaluate safety and competence.


https://huggingface.co/blog/KnutJaegersberg/whats-missing-for-agi-in-todays-tech-trajectories
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