AI systems are running out of data. What comes next?
A new paper argues that the era of training AI on massive datasets is ending, forcing companies to shift toward AI agents that learn by doing rather than memorizing. This matters because the next generation of competitive advantage may depend on building systems that reason and act independently—not just answer questions from training data.
Originaltitel: The End of Pretraining for Large Language Models: The Future of Agentic and AI Reasoning Beyond Peak Data
Artificial intelligence (AI) has entered a transformative era, as traditional pretraining paradigms face the constraints of “peak data.” This article explores the implications of a “post-pretraining” era, where AI systems transcend static data dependency and evolve into agentic AI entities.