OpenScholar, a new open-source AI system developed by the Allen Institute for AI and the University of Washington, is transforming how researchers analyze scientific literature. As reported by Michael Nuñez for VentureBeat, the system processes over 45 million open-access academic papers to provide citation-backed answers to complex research questions. The AI combines advanced retrieval systems with a fine-tuned language model, outperforming larger proprietary systems like GPT-4o in accuracy and citation verification. OpenScholar’s distinctive feature is its ability to remain grounded in verifiable sources, addressing the common problem of citation hallucination that affects other AI models. The system is fully open-source, making it more cost-efficient and accessible to researchers worldwide, though it currently only processes open-access papers.