Inaccurate, duplicate, and incomplete data continues to plague industries. Artificial intelligence is leveraged to mitigate these issues, but it has inherent limitations. AI datasets can contain mislabeled or irrelevant data.
Fraction AI is pioneering a new approach to data labeling by combining the efficiency of AI agents with human insights. The company recently completed a $6 million pre-seed funding round co-led by Symbolic and Spartan alongside strategic investments from Illia Polosukhin (Near), Sandeep Nailwal (Polygon), and other outstanding angel investors.
Fraction AI tackles the increasing challenge of producing high-quality data. Traditional methods depend solely on AI or humans. Fraction AI aims to use human understanding as guidance for AI agents. Funds from the round will go toward in-depth exploration and infrastructure upgrades to scale the cutting-edge hybrid approach, whose effectiveness is confirmed by research.
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We współpracy z: https://cryptodaily.co.uk/2024/12/improving-data-quality-via-collective-error-detection-and-creative-problem-solving
