LabAI
15- to 20-Minute Training Helps People Spot AI-Generated Faces
University of Southampton researchers tested the DISCERN-AI session with more than 600 participants.
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Models, agents, applications: artificial intelligence put to work on real problems.
Here, artificial intelligence is judged on the evidence: what it does, for whom, at what cost. The section follows models and their measurable progress, agents doing real work, and above all deployments — a hospital screening more patients, a power grid better balanced, a public service answering faster. AI-as-spectacle, productless funding rounds and prophecy get no space.
We favour documented use cases with the numbers attached: how many examinations, what error rate, what savings. Non-Western players — Chinese, Indian, Emirati labs — are covered on the same footing as American ones, because much of the real deployment happens there. Every article cites its sources and separates the prototype from the service in production.
University of Southampton researchers tested the DISCERN-AI session with more than 600 participants.
BDH-CQ uses 150 million parameters and recurrent internal memory instead of written chains of thought.
City University of Hong Kong and Chinese University of Hong Kong researchers studied mice performing two tasks at once.
LL-Refiner handles lighting and scene structure at lower resolution before restoring fine details.
Researchers at Pusan National University developed two systems that combine specialized models for different kinds of movement.
Victoria University researchers trained two AI models on one million Reddit health-related threads.
University at Buffalo’s CrowdHydrology network spans 26 states and has collected more than 20,000 readings.
University students outside the US, including those in Japan, are eligible; the application deadline is December 31, 2026.
OpenAI showcased corporate and university research use cases for ChatGPT Work in Seoul's Samseong-dong district.