Research POV: Yes, AGI Can Happen – A Computational Perspective

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The post argues that current AI systems are significantly underutilizing existing hardware, with Mean FLOP Utilization (MFU) often around 20% for training and single digits for inference. It posits that better software-hardware co-design and innovations like FP4 training can unlock substantial performance gains, challenging the idea that AI progress is solely limited by hardware constraints. It also notes that future compute generations have not yet been fully integrated into AI development, and that current models already demonstrate significant utility in complex tasks.