Part 5/10:
The worry around the so-called data wall raised by scholars like Andre Karpathy appears to be easing. Initially, there were concerns that the quality and quantity of data available for training AI systems might narrow prospects for advancement. However, innovative approaches like self-play, where AI models compete against themselves to learn, have effectively circumvented previous data limitations. This has opened avenues for generative capabilities in AI, suggesting that data might not persist as a permanent bottleneck.