Sparse attention and Performer variants let LLMs process long sequences efficiently by reducing memory use from terabytes to gigabytes. Learn how they work, where they shine, and which models to use.
Training data pipelines for generative AI use deduplication, filtering, and mixture design to turn raw data into high-quality training sets. Poor pipelines lead to flawed models-here’s how to build them right.
Learn how to choose between API and open-source LLMs in 2025 based on cost, performance, privacy, and team skills. Real-world data and benchmarks show which option works best for your use case.