The Mind AI

Introduction to AI Scaling Laws Artificial intelligence development increasingly depends on three key scaling laws: pre-training, post-training, and test-time scaling. These principles guide how AI models improve in capability and efficiency. Understanding these laws helps explain how AI systems evolve to better automate tasks and optimize workflows. Pre-Training: The Foundation of Smarter AI Pre-training involves initially training AI models on large datasets before they are used for specific tasks. This stage builds a broad understanding and general skills within the model. For automation, pre-training enables AI to handle diverse inputs and situations, laying the groundwork for smarter, more flexible workflows. Post-Training Enhancements After pre-training, AI models undergo post-training processes such as fine-tuning and reinforcement learning. These techniques tailor the model to particular tasks or environments. In workflow automation, post-training improves precision ...