Evaluating Large Language Models Trained on Code

Codex: the friendly coder that writes Python from simple notes

Meet Codex, a system learned from public GitHub code that can turn short instructions into working programs.
It powers GitHub Copilot and sometimes writes code that would took hours for a person.
With smart sampling tricks it solved many problems—about 70.
2% when trying lots of options—showing this idea can work, often faster than older tools.
But it is not perfect, it stumbles on long step-by-step directions and can mix up which value should go where; these are real limitations to keep in mind.
For most people the tool feels like a helpful pair of hands, suggesting snippets and finishing small tasks, while developers still check and fix the results.
The big picture is exciting: tools like this could speed learning, boost productivity, and change how we build software, but also bring new questions about safety and jobs.
Try it curious, be careful, and expect mistakes—this tech helps, but doesn't replace human judgement yet.

Read article comprehensive review in Paperium.net:
Evaluating Large Language Models Trained on Code

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