Register Now Investigating code generationĪ growing number of organizations are exploring code-generating AI. While Pol圜oder doesn’t match the performance of top code generators in every task, the researchers claim that Pol圜oder is able to write in C with greater accuracy than all known models, including Codex. To remedy this, researchers at Carnegie Mellon University - Frank Xu, Uri Alon, Graham Neubig, and Vincent Hellendoorn - developed Pol圜oder, a model based on OpenAI’s GPT-2 language model that was trained on a database of 249GB of code across 12 programming languages. For example, the training data for OpenAI’s Codex, which powers GitHub’s Copilot feature, hasn’t been made publicly available, preventing researchers from fine-tuning the AI model or studying aspects of it such as interpretability. But while research labs like OpenAI and Alphabet-backed DeepMind have developed powerful code-generating AI, many of the most capable systems aren’t available in open source. Learn MoreĬode generation AI - AI systems that can write in different programming languages given a prompt - promise to cut development costs while allowing coders to focus on creative, less repetitive tasks.
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