134 summarised stories about AI Code Generation, each linking back to the original source. Browse all topics →
OpenAI 5 months ago 31
NVIDIA engineers and researchers use Codex with GPT-5.5 to accelerate development of production systems and convert research concepts into executable experiments. The system enables faster iteration cycles for building deployed applications and testing research hypotheses. Teams can reduce time spent on routine coding tasks, freeing capacity for higher-level design and problem-solving work.
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19 October 2026
NVIDIA’s decision to open-source Run:ai under Apache 2.0 is the day’s most consequential signal: AI compute is getting treated less like proprietary infrastructure and more like inspectable, forkable plumbing. The release puts Run:ai’s Kubernetes GPU orchestration code on GitHub and, in the local build, spins up a five-node Kind cluster pinned to Kubernetes v1.32.5 with eight simulated Tesla-A10 GPUs. That means teams can now audit scheduling behavior, adapt deployment patterns, and self-host without a paid subscription—though the community edition still stops short of NVIDIA enterprise support. In practice, it moves GPU fleet management closer to the software engineers who already live inside CI/CD pipelines, rather than keeping it behind enterprise procurement gates.
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