Wikimedia says that the dataset hosted by Kagal is “designed keeping in mind the machine learning workflows”, making it easier to use machine-elevant data for modeling, fine-tuning, benchmarking, alignment and analysis for AI developers. The content within the dataset is openly licensed, and by April 15, research summary, short details, image links, infobox data, and article section-meinous references or non-written elements such as audio files are included.
“As the machine comes for learning community equipment and testing, Kagal is very excited to be hosts for the Wikimedia Foundation’s data,” said Kagal partnership Branda Flyn. “Kagal is excited to play a role in keeping this data accessible, available and useful.”
