RAG

Transformers and Beyond: Advances in NLP Transformers sparked a new era in NLP, and researchers continue to push the envelope. Models are bigger, but real progress comes from better training data, smarter objectives, and safer deployment. The goal is reliable language understanding and useful behavior across domains. This post surveys current trends and practical ideas for developers and researchers. Scaling laws show that larger models often perform better, but costs rise quickly in compute and energy. Teams balance model size with data quality, robust evaluation, and alignment toward user needs. Research also explores efficiency tricks to reduce latency while keeping accuracy high. ...