Aug 13, 2025 · 2 min read · Pre-training uses massive datasets and computational resources—often thousands of GPUs running for weeks or months—making it a domain dominated by top AI companies. Post-training is much lighter in cost and time (often days instead of months) and foc...
Join discussion
Aug 14, 2025 · 2 min read · Turning a base model into a reasoning model is essentially a post-training + data problem. The model’s architecture can stay the same — what changes is how it’s fine-tuned, what data it sees, and what training objectives you use. Here’s the typical p...
Join discussion