• AI for fairer and more accessible Para sport classification

    Para sport classification is essential for fair competition, but current methods rely on face-to-face assessments by highly trained experts. The process can be subjective, time-consuming and costly, creating barriers for athletes, particularly those in rural, remote and low- and middle-income countries.
  • How AI can help students learn

    A University of Queensland team has developed an evidence-based platform with embedded AI learning companions designed to question, scaffold and explain rather than simply answer questions – prioritising lasting understanding over immediate performance.
  • AI-Enabled Multilingual Access to Research

    Researchers at The University of Queensland have developed an agentic AI translation system that makes academic research accessible in multiple languages.
  • Australian Ad Observatory: Bringing Transparency to Digital Advertising

    The Australian Ad Observatory uses machine vision and citizen-donated data to improve transparency around online advertising, helping researchers, policymakers and the public better understand how digital platforms target and influence users.
  • CorpusMate: Bringing the Power of Real Language Data to Everyone

    CorpusMate combines artificial intelligence with 47 million words of authentic language data, making evidence-based language learning and research more accessible for teachers, students, researchers and language learners.
  • Preparing organisations for a future where AI may become conscious

    Artificial intelligence is becoming increasingly sophisticated, prompting debate about a question once confined to science fiction: could machines ever become conscious?
  • How virtual students can help train the next generation of teachers

    Many education students finish their training feeling unprepared to teach writing. A University of Queensland team is building affordable, AI-powered classroom simulations where trainee teachers can practise teaching lifelike student avatars before they ever stand in front of a real class – a platform that could be adapted to any subject.
  • AI that reasons across the world’s research literature

    The volume of scholarly literature is growing faster than any one researcher can keep up with, and making sense of it at scale is hard. Existing AI tools tend to do one narrow job well — retrieving papers or answering a question about a single document — but struggle to move fluidly from simple retrieval through to synthesising across many papers and generating new knowledge.

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