How to teach the same skill to different robots
Peer-Reviewed Publication
Updates every hour. Last Updated: 17-May-2026 06:15 ET (17-May-2026 10:15 GMT/UTC)
A new study in the American Economic Journal: Applied Economics assessed life trajectories of children in Lesotho, Africa, across a wide range of educational and later-life outcomes. The study found that children who enrolled in primary school at an older age—despite an initial disadvantage in years of schooling—were more likely to remain in school through adolescence, obtained higher total years of schooling, and developed greater literacy than children who began primary school at younger ages. The older children were also more likely to delay marriage, have fewer children, hold higher-earning jobs, and accumulate greater wealth.
Warren Buffett advised that you should never invest in a business you can’t understand. But that hasn’t stopped many investors.
New research from the McCombs School of Business at The University of Texas at Austin might help them better understand the complications of companies they’re investing in. The study offers the most precise and comprehensive tool yet for measuring business complexity.
The tool, devised by Sara Toynbee, associate professor of accounting, simplifies the measurement by using artificial intelligence. It also finds that in areas such as structuring debt, complexity can sometimes be a good thing.
The Saitama Emissions Trading Scheme (ETS), launched in 2011, regulates large facilities whose annual energy consumption exceeds 1,500 kiloliters of heavy oil equivalent. Using facility-level panel data from 2007 to 2018, a new study finds that regulated facilities significantly reduced heavy oil consumption and city gas while slightly increasing electricity use, indicating a shift toward lower-carbon energy sources. Importantly, the scheme did not negatively affect employees. These findings provide valuable evidence for Japan's nationwide mandatory ETS scheduled to begin in 2026.
Check out this new research in Engineering! It introduces an adaptive edge-cloud collaboration method for intelligent machine tools, tackling large-scale computational tasks with complex data links. The method cuts task processing time, boosts energy efficiency and keeps data secure, with solid real-world validation on digital twin machining centers—great for next-gen smart manufacturing!