As AI technology rapidly advances, the challenges of data acquisition are becoming increasingly prominent. Research from institutions like MIT reveals that open-source datasets such as C4, RefineWeb, and Dolma are facing stricter licensing agreements from the websites they scrape, posing significant challenges for AI training and academic research. The study found that even major AI companies like OpenAI are subject to strict limitations due to r....

OBIA includes 937 patients and 1.93 million medical images from the 301 Hospital, covering 9 modalities and 30 anatomical sites. OBIA realizes the de-identification, management, and quality control of imaging data, providing users with browsing, retrieval, and download services. OBIA fills the gap in the open sharing of biomedical imaging data in the country and helps promote the development of medical imaging AI.

Harvard and Columbia have released the open dataset OpenProteinSet, containing 16 million protein multiple sequence alignments and related data to support AI model training. AlphaFold 2 has achieved a milestone in the accuracy of protein structure predictions, but its proprietary data has limited progress for other researchers. OpenProteinSet includes MSAs for all proteins in the PDB, providing ample precomputed MSA resources for the protein machine learning community. This dataset can be used for various tasks in structural biology.

["The Allen Institute for Artificial Intelligence has released the open text dataset Dolma, aimed at promoting transparency and innovation in AI language models.", "Dolma, as the core of AI2's open language model initiative, provides researchers and developers with free data resources.", "The Dolma dataset boasts a scale of 3 billion tokens, operates under the mid-risk ImpACT license, and encourages users to provide contact information and usage feedback."]