IBM’s AI research division has released a 14-million-sample dataset to develop machine learning models that can help in programming tasks. Called Project CodeNet, the dataset takes its name ...

IBM’s AI group released CodeNet, a 14-million-sample dataset for training machine learning models to help software developers be productive.

The new model can autonomously handle programming tasks, including project development and handling codebase inquiries.

Apple researchers built UICoder through a feedback loop that generated, filtered, and retrained SwiftUI code, transforming scarce data into nearly one million working samples.

Open access, discoverability, reproducibility, code, datasets, and knowledge graphs. This is all good news for research, and machine learning research too, obviously.

A group of Apple researchers took a very interesting approach to get an AI to teach itself how to build good interfaces in SwiftUI.

BigCode, launched recently by Hugging Face and Service Now, is looking to address some of code-generating LLMs biggest pain points.

There are several available datasets for source code, but most are only useful for a few targeted tasks. Two popular datasets, GCJ and POJ, are compared to CodeNet in the above chart.