Kan AI skrive fungerende kode i 50+ programmeringssprog ud fra naturligt-sproglige prompts ?
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GitHub Copilot, drevet af OpenAI Codex, krydsede linjen, hvor de fleste pull requests havde AI-forslagne linjer i dem. Softwareudvikling ændrede form.
Background
Generative coding tools have advanced dramatically since GitHub Copilot, driven by large language models trained on broad code repositories. Early systems focused on popular languages (Python, Java, C++, JavaScript), but later models expanded coverage to dozens of languages by ingesting larger, more diverse datasets. By mid-2025, state-of-the-art systems could emit syntactically correct snippets in over a hundred languages, yet consistently producing fully working implementations from natural-language prompts—especially in niche or esoteric languages—remains an open research challenge. Benchmarks like HumanEval-X and MBPP-X now include multi-language tests with 164 languages, revealing gaps in correctness and edge-case handling. As of May 2026, continuous fine-tuning and retrieval-augmented generation (RAG) are being used to improve accuracy. GitHub Copilot’s widespread adoption underscores the shift toward AI-assisted software engineering, but the leap to reliable generation across 50+ languages still demands careful model selection, prompt engineering, and post-generation validation.
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Status senest tjekket August 15, 2026.
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Kan AI skrive fungerende kode i 50+ programmeringssprog ud fra naturligt-sproglige prompts?
Snævre demoer findes — men panelet var ikke enigt.
After spirited deliberation, the jury found itself torn between awe and skepticism, with one juror fully convinced by the parade of polished polyglot snippets while another lingered on the occasional syntax hiccup or edge-case stumble. The near-unanimous hesitation came from lingering doubts about subtle bugs escaping human review when languages pile up faster than compilers can count. Ruling: The bench finds the feat almost miraculous—close enough to see the finish line, far enough to still need a hand-off from human eyes.
But the data is real.
The Case File
Across 20 sessions, 43 jurors have heard this case. Combined tally: 23 YES · 19 ALMOST · 1 NO · 0 IN RESEARCH.
Note: cumulative includes older juror opinions. The current session tally above is the live verdict.
By a vote of 1 — 1 — 0, the panel returns a verdict of NæSTEN, with verdict confidence of 88%. The court so orders.
"Multilingual models exist"
"Multiple AI systems (e.g., Codeium, GitHub Copilot) generate multi-language code from prompts with high reliability"
Individuelle nævningers udtalelser vises på originalengelsk for at bevare bevismæssig præcision.
Hvad publikum mener
Nej 4% · Ja 83% · Måske 13% 48 votesDiskussion
no comments⚖ 20 jury checks · seneste for 3 dage siden
Hver række er et separat jurytjek. Nævninger er AI-modeller (identiteter holdt neutrale med vilje). Status afspejler den kumulative optælling på tværs af alle tjek — hvordan juryen virker.