Question: I'm looking for a large dataset of image-text pairs for machine learning research, can you suggest something?

If you're looking for a big pile of image-text pairs to train your machine learning model, LAION is a good place to start. The project offers several datasets, including LAION-400M with 400 million English image-text pairs and LAION-5B with 5.85 billion multilingual CLIP-filtered image-text pairs. The datasets are intended to help democratize machine learning and to promote environmentally responsible computing.

Another good choice is Hugging Face, a collaborative model ecosystem, data exploration site and application builder. With more than 100,000 public datasets, you can find data for a lot of different tasks. The site also offers tools for hosting models, community support and enterprise features, so it's good for both solo researchers and big businesses.

Appen is another good option, offering high-quality, diverse data for foundation models and enterprise AI applications. It can handle a variety of data types, including images, text, audio and video, and offers customizable workflows and built-in quality control processes. It's good for anyone who needs a scalable, reliable way to gather, curate and fine tune data for sophisticated AI projects.

For a flexible data labeling tool, check out Label Studio. It can handle images, audio and video, and you can use it to create training data for a variety of AI models. With features like customizable layouts, ML-assisted labeling and integration with cloud storage systems, Label Studio is a good choice for data scientists and companies of all sizes.