Archive: 2025/08

In 2025, enterprises are using large language models to automate customer service, detect fraud, review contracts, and train employees. Success comes from focusing on accuracy, security, and data quality-not model size.

Checkpoint averaging and EMA stabilize large language model training by combining multiple model states to reduce noise and improve generalization. Learn how to implement them, when to use them, and why they're now essential for models over 1B parameters.

Data residency for global LLM deployments ensures personal data stays within legal borders. Learn how GDPR, PIPL, and other laws force companies to choose between cloud AI, hybrid systems, or local small models-and the real costs of each.