DatalogyAI, a startup specializing in artificial intelligence data curation, announced today that it has successfully secured $46 million in early-stage funding. This funding round comes just three months after the company’s initial seed funding of $11.65 million.
The Series A funding was led by Viv Faga and Astasia Myers from Felicis Ventures, with participation from existing investors such as Radical Ventures and Amplify Partners, as well as new investors including Elad Gil, M12, and the Amazon Alexa Fund. With this latest round of funding, DatalogyAI has now raised a total of nearly $57.7 million.
The startup aims to democratize data research by addressing a significant challenge in generative AI development: the need for curated datasets to inform large language models like OpenAI’s GPT-4 and Google LLC’s Gemini Pro. DatalogyAI offers tools to automate much of the dataset curation process, including identifying relevant information, suggesting dataset augmentation techniques, and optimizing data batching for model training.
Founder and CEO Ari Morcos emphasizes the importance of efficient training datasets in improving the quality and performance of AI models while minimizing computational costs. Smaller AI models result in lower compute costs, a crucial factor considering the substantial expenses associated with training and running large models.
DatalogyAI’s tools enable developers to efficiently filter and streamline datasets, removing redundant or harmful data and improving the overall quality of training samples. Additionally, the startup’s technology can assist in labeling unlabeled data and identifying potentially harmful data patterns.
The funding will allow DatalogyAI to expand its team, particularly focusing on hiring more researchers and engineers. The company also plans to enhance its compute capabilities to further advance the frontier of data curation possibilities.