Part 4/12:
The limits to AI efficiency have led to core reflections on computational systems. Models can struggle with complex calculations, yet leveraging synthetic data eases this bottleneck. For AI to become even more efficient, iterative improvements in algorithms, hardware, and quality data generation are all crucial. Encouragingly, the conversation indicated that while computational resources may appear to be soft bottlenecks, they shouldn't inhibit innovation.