AI Aims For Perfect Coding And With Multiple Solutions
Meet pass@k
And, so, the AI bot are fighting with each to be the one that gets everything right. So, no matter what problem we give them, they are competing to show that they can cope with your complex world of learning. The two core data sets used for the problems are HumanEval pass@1 accuracy and MBPP Pass@1.
With this, we have the pass@k metric, which can relate to a dataset of hand-written problems (“HumanEval”). The AI bot then reads the challenge and creates code. This code is then evaluated within a sandboxed environment for its success. The k element [2] relates to the generation of k code samples for every problem. Thus pass@1 produces one solution, while pass@10 produces 10 solutions.
Three examples of coding challenges for HumanEval pass@1 are:
At the current time, the leaderboard is [here]:
The leader is Reflexion: Language Agents with Verbal Reinforcement Learning, and which is based on GPT-4…
