Demystifying Synthetic Data in LLM Pre-training: A Systematic Study of Scaling Laws, Benefits, and Pitfalls — mentioned by Schiendelman

Thu, 25 Jun 2026 19:55:52 GMT

I don't think "data limited" is true anymore outside of very specialized cases (for instance: https://arxiv.org/abs/2510.01631). As weird as it sounds, training improves a lot with synthetic data. You do need business development to create those relationships. Saying they "have limited ___" mostly means they "haven't yet hired people who are good at ___". That's been changing already; the Claude app is steadily improving and handling more use cases simply through understanding which tools to use, Anthropic is building more relationships to create more tools, and all the frontier model…

Paper and discussion history. A mention is not an endorsement.

Demystifying Synthetic Data in LLM Pre-training: A Systematic Study of Scaling Laws, Benefits, and Pitfalls · HackerPapers discussions

Demystifying Synthetic Data in LLM Pre-training: A Systematic Study of Scaling Laws, Benefits, and Pitfalls — mentioned by Schiendelman