Typical problems include finding ways to place roads and buildings within certain constraints, or creating strategies to win custom board games. During competitions, participants receive a series of long problem descriptions and a few hours to write programs to solve them. The problem is from Codeforces, and the solution was generated by AlphaCode.Ĭompetitive programming is a popular and challenging activity hundreds of thousands of programmers participate in coding competitions to gain experience and showcase their skills in fun and collaborative ways. We hope this benchmark will lead to further innovations in problem solving and code generation. To help others build on our results, we’ve released our dataset of competitive programming problems and solutions on GitHub, including extensive tests to ensure the programs that pass these tests are correct - a critical feature current datasets lack. AlphaCode placed at about the level of the median competitor, marking the first time an AI code generation system has reached a competitive level of performance in programming competitions. We selected for evaluation 10 recent contests, each newer than our training data. We validated our performance using competitions hosted on Codeforces, a popular platform which hosts regular competitions that attract tens of thousands of participants from around the world who come to test their coding skills. Published on the cover of Science, our paper details AlphaCode, which uses transformer-based language models to generate code at an unprecedented scale, and then smartly filters to a small set of promising programs.
AlphaCode achieved an estimated rank within the top 54% of participants in programming competitions by solving new problems that require a combination of critical thinking, logic, algorithms, coding, and natural language understanding. The machine learning community has made tremendous progress in generating and understanding textual data, but advances in problem solving remain limited to relatively simple maths and programming problems, or else retrieving and copying existing solutions.Īs part of DeepMind’s mission to solve intelligence, we created a system called AlphaCode that writes computer programs at a competitive level. Solving novel problems and setting a new milestone in competitive programmingĬreating solutions to unforeseen problems is second nature in human intelligence – a result of critical thinking informed by experience. Following the paper’s publication in Science on, we’ve made minor updates to the text to reflect this.
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