BRMs thus naturally induce strategic creators' collective behaviors

Why apply AI to figure skating? Skaters can always keep pushing, higher, faster, stronger. OOFSkate is all about helping skaters figure out a way to rotate a little bit faster in their jumps or jump a little bit higher. The system helps skaters catch things that perhaps could pass an eye test, but that might allow them to target some high-value areas of opportunity. The artistic side of skating is much harder to evaluate than the technical elements because it's subjective.

Does progress on ImageNet transfer to real-world datasets?

Apple and Google agree to change app stores after'effective duopoly' claim Apple and Google have agreed to make changes to their app stores in the UK following an intervention from the UK markets regulator. According to the Competition and Markets Authority (CMA), the tech giants have committed to not giving preferential treatment to their own apps and will be transparent about how others are approved for sale, among other agreements. It comes seven months after the regulator said Apple and Google had an effective duopoly in the UK over their dominance in the sector. The CMA's head Sarah Cardell said the proposed commitments will boost the UK's app economy and were the first of many measures. The ability to secure immediate commitments from Apple and Google reflects the unique flexibility of the UK digital markets competition regime and offers a practical route to swiftly address the concerns we've identified, she said.

AI is coming to Olympic judging: what makes it a game changer? As the International Olympic Committee (IOC) embraces AI-assisted judging, this technology promises greater consistency and improved transparency. Yet research suggests that trust, legitimacy, and cultural values may matter just as much as technical accuracy. In 2024, the IOC unveiled its Olympic AI Agenda, positioning artificial intelligence as a central pillar of future Olympic Games. This vision was reinforced at the very first Olympic AI Forum, held in November 2025, where athletes, federations, technology partners, and policymakers discussed how AI could support judging, athlete preparation, and the fan experience.

Machine learning research has long focused on models rather than datasets, and prominent datasets are used for common ML tasks without regard to the breadth, difficulty, and faithfulness of the underlying problems. Neglecting the fundamental importance of data has given rise to inaccuracy, bias, and fragility in real-world applications, and research is hindered by saturation across existing dataset benchmarks.