Separating signal from noise in coding evaluations
4mo
- Published
- Collected
A new analysis from OpenAI reveals issues in SWE-Bench Pro, a popular coding benchmark, raising concerns about reliability and accuracy in evaluating AI models.
overfeed.news indexes and links. We publish a short excerpt — the full article stays at OpenAI News.
More from OpenAI News
Log in to follow this source
How Amplitude ships product improvements in 1–2 days with OpenAI
Built primarily on OpenAI models, Amplitude’s proactive product agent, Wave, identifies what to build, helps teams ship changes with coding agents, and measures the impact.
Gondola doubles revenue as its team builds more with Codex
Gondola helps creatives get credit and get hired, with Codex raising its lead engineer’s output by 50% and ChatGPT simplifying daily work.
Holiday Extras is rethinking what it can build with Codex
With Codex, Holiday Extras is turning customer expertise into better apps, higher booking conversion and new possibilities for growth.
Supporting research on AI and children’s safety
OpenAI commits $2 million to research on AI and children’s safety. The work supports shared tools to measure risks and opportunities for young people.