Part 3/13:
They highlight that current models depend heavily on compute resources, which are finite. While some experts argue that data constraints might become the primary bottleneck, computational power remains a critical factor. Interestingly, humans are remarkably efficient—our brains operate on mere watts, making them exponentially more data- and energy-efficient than AI in certain respects. Still, AI's capacity to process vast datasets—like GPT-4's knowledge equivalent to thousands of humans—makes it a formidable tool.
The central question remains: when, if ever, will AI's growth slow or stop? Current paradigms might sustain progress for another five to ten years, but the author emphasizes the need to prepare for diminishing returns and potential ceilings in AI development.