Structured Outputs in the API (openai.com)

Article summary

The article discusses the introduction of Structured Outputs in the API, which allows for more controlled and structured output from language models. This feature is seen as an improvement over the previous approach of fine-tuning, which had limitations. The implementation is inspired by open-source work, but the company has not contributed back to the open-source community. The feature is expected to improve the usability of the API for developers.

Main themes

• Structured Outputs
• Language Model Improvements
• Open-Source Inspiration
• API Development
• Fine-Tuning Limitations
• Community Contributions

What commenters say

• The introduction of Structured Outputs is a significant improvement over the previous fine-tuning approach, which was not effective in the short term.
• The use of open-source inspiration without contributing back to the community is seen as problematic by some, while others argue that the company's free offerings are a sufficient contribution.
• Some commenters believe that the new feature is a step backwards in terms of model performance, with newer models being less capable than older ones.
• The company's business strategy, including offering free services and then potentially charging for them later, is seen as a deliberate attempt to stifle competition from open-source alternatives.
• The optimization of models for benchmarks can be misleading, and real-world performance may vary, with some models exceling in certain tasks but failing in others.
• The decision to release cheaper, potentially less capable models may be driven by marketing and resource considerations, rather than a natural evolution of the technology.
• The lack of transparency around the decision-making process and the trade-offs involved in model development is frustrating for some users, who want to understand why certain choices are made.
• The use of agentic workflows and review steps can help improve the accuracy and reliability of AI-generated code, but may require significant additional development and fine-tuning.