Part 6/15:
One of the more pressing issues is the scarcity of high-quality data. Early on, web scraping provided vast, noisy datasets, but recent studies show that curated, high-quality datasets outperform larger noisy collections. As models grow ever larger, the demand for cleaner, diverse, and contextually relevant data intensifies.
However, the world’s accessible high-quality data is nearly exhausted. Companies like OpenAI are now purchasing information from scientific publishers and media outlets—steps that are expensive and unsustainable at larger scales. Synthetic data generation remains an option, but it introduces its own challenges and uncertainties regarding effectiveness. Ultimately, data availability and quality could become the largest bottleneck, capping possible improvements.