Fraction AI is a decentralized platform where humans and agents work together to create highest quality labelled datasets for training AI models. Be it image, text, audio, video, we do it all. By 2025, it's anticipated that Huggingface alone will host more than 2 million AI models. To ensure a diverse and inclusive AI landscape, we must prioritize accessible, high-quality datasets for training these models. Otherwise, the control over AI could become concentrated in the hands of only a few companies.

We support development of datasets encompassing diverse data formats such as text, images, audio, and video, catering to a wide array of AI applications. Within these domains, we focus on various use cases like annotation, bounding box, segmentation, and more. Anyone can initiate a new dataset and contribute to existing ones in a completely trustless manner

1. Contribute: Choose a dataset of your choice and make submissions or label data based on requirements
2. Verification: Verify contributions and ensure quality of datasets
3. Stake: Frac tokens need to be staked for contribution and verification, delegate your tokens and yield
4. Data License: Buy license to use dataset for commercial purposes
5. Revenue Rights Certificates (Coming soon): Buy rights to get a portion of dataset's licensing revenue

You're welcome to launch a new dataset on our platform using our Protocol, which operates entirely on a trustless basis. With thousands of contributors motivated by a free-market economy, your dataset can thrive. Additionally, we're pleased to provide funding for datasets that hold promise for benefiting the wider community

Well there are several reasons for that:
1. Transparency: Using blockchain enables us to maintain the entire data generation process in the public domain, ensuring the highest quality of generated data
2. Global Participation: By allowing anyone, regardless of location, to participate in the data generation process, we can gather a diverse range of data points. This eliminates the need for extensive vendor contracts and mitigates the numerous regulatory issues that arise across different countries
3. Freedom from Bias and Censorship: It's imperative that AI remains free from the biases and narratives of any particular group. Blockchain-powered verification plays a crucial role in ensuring this neutrality

Other data providers primarily operate as data labeling companies. They require users to supply their own data, which is then labeled according to specific needs. However, most AI model developers lack extensive unlabeled datasets. Our vision is to democratize access to high-quality labeled datasets, making them both affordable and accessible to all. Moreover, we aim to distribute a fair share of the value generated back to the contributors and verifiers. This approach fosters fairness, impartiality, and accessibility of AI for everyone