Out-of-pocket spending for insulin by Medicare beneficiaries after monthly caps
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Updates every hour. Last Updated: 28-May-2026 03:15 ET (28-May-2026 07:15 GMT/UTC)
NTU Singapore is embarking on an ambitious effort to transform its undergraduate education with artificial intelligence (AI). By 2030, NTU Singapore aims to embed AI into 40% of the courses across all 52 undergraduate degree programmes the University offers. This is an eightfold increase from 5% today. Half of these courses will use AI to personalise learning. The other half will teach students how to build, deploy, and manage AI agents to solve real-world problems. The goal is to produce graduates who can not only learn continuously with AI tutors but can also create and work effectively with AI agents.
To power this aspiration, from August 2026, NTU will give all undergraduates full access to a suite of premium Google AI tools, such as Gemini Enterprise, Google AI Studio, and Vertex AI. Students will also receive computing credits to build and deploy their own AI agents for learning and problem-solving. Each year, they can choose to create dozens of such AI agents to support their studies. These agents are portable – NTU graduates can continue to use and improve them even after they enter the workforce to enhance their productivity. This feature will make the University’s graduates highly competitive in the job market.
A new study from Sultan Qaboos University shows how artificial intelligence can map hidden connections within legal systems, revealing that key provisions in Oman’s Labour Law of 2023 act as highly influential “hubs” whose amendment could trigger wide-ranging legal effects. Published in The Journal of Engineering Research, the research uses Arabic-language NLP and network analysis to offer policymakers a powerful, evidence-based tool for anticipating the real impact of legal reforms — with implications extending to legal systems worldwide.
Drawing on an analysis of 71 childcare policy documents across eight Chinese megacities, the study identified key pathways to advancing universal childcare in the context of population decline. It highlighted two approaches to government responsibility—state-led and family-supportive—and outlines four supply modes. The findings offer comparative insights for improving policy design and support ongoing efforts to build an inclusive, high-quality childcare system in China.
SEED-SET is a new evaluation framework that can test whether recommendations of autonomous systems are well-aligned with human-defined ethical criteria. It can also pinpoint unexpected scenarios that violate ethical preferences.