While AI is often seen as automating human work, it still heavily depends on human involvement, especially in training models through reinforcement learning from human feedback (RLHF). Rapidata introduces a groundbreaking platform that transforms this process by distributing review tasks to millions of mobile app users globally in place of traditional ads, allowing instant feedback to AI labs. This dramatically accelerates AI model development from months to just days.
Founded by Jason Corkill, Rapidata addresses the long-standing issue of slow, fragmented human annotation workflows by leveraging existing mobile app audiences to collect high-quality, rapid feedback. The platform supports massive scale and speed with features like parallel processing of up to 1.5 million annotations per hour, global user reach, and quality control via trust profiles — all while maintaining user anonymity.
This innovation integrates human insights directly into AI training loops on GPUs in near real-time, enabling “online RLHF”. This reduces delays, improves model authenticity, and helps AI systems better capture subjective nuances such as taste and cultural context. Industry leaders acknowledge Rapidata as critical infrastructure for the next generation of AI, ensuring that human judgment remains a scalable, dynamic part of AI progress.
With an $8.5 million seed round and partnerships spanning popular apps, Rapidata is poised to shift AI development from static cycles to continuous, evolving feedback, bridging the gap between silicon-based AI and society’s complex human experience.
