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“The day I hear a song of the quality of the Beatles, I will say: ‘Okay, we are done’. And I’ve never heard anything like that. Never.” Dr François Pachet is an AI researcher and musician, and one of the most influential figures in AI and music. His innovative contributions have defined the field over […]
What if AI were designed not only to optimize choices for individuals, but to help groups reach decisions together? At IJCAI 2025 in Montreal, I had the pleasure of speaking with Professor Kate Larson of the University of Waterloo, a leading expert in multi-agent systems whose research explores how AI can support collective decision-making. In
Interview with Kate Larson: Talking multi-agent systems and collective decision-making Read More »
How can we train neural networks efficiently to be more consistent with background knowledge? Neural networks are remarkably good at recognising patterns in data, from images to language, but they often fail to respect rules and relationships that are obvious to humans. For instance, a neural network may learn to recognise road agents, their action,
Learning from logical constraints with lower- and upper-bound arithmetic circuits Read More »
Drug repurposing often starts as a hypothesis: a known compound might help treat a disease beyond its original indication. A good example is minoxidil: initially prescribed for hypertension, it later proved useful against hair loss. Knowledge graphs are a natural place to look for such hypotheses because they encode biomedical entities (drugs, genes, phenotypes, diseases)
Rewarding explainability in drug repurposing with knowledge graphs Read More »
