Data Quality and Hardware: The Real Constraints of AI Development

Successful AI development depends primarily on data quality and computational infrastructure, not algorithm sophistication. The author reveals that both LLMs and reinforcement learning share a critical weakness: garbage-in, garbage-out. These practical insights are essential for anyone building AI systems, exposing the hidden costs that hype-driven coverage typically obscures.