Efficient training of language models to fill in the middle
OpenAI just solved a training problem that changes how developers build with LLMs.

Why it matters
OpenAI's 'fill in the middle' training technique demonstrates a fundamental advance in language model architecture and training efficiency—directly impacting how models can be deployed for code completion and multi-directional text generation at scale.
The key facts
4 to knowOpenAI research on efficient training methodology for bidirectional language model capabilities
Fill-in-the-middle (FIM) training approach improves model utility without sacrificing performance
Direct precedent for capability innovations that shipped in Codex and later Claude Code products
Published July 2022—foundational research that informed subsequent model architectures
Go to the source
OpenAI Blogopenai.com