Insomnia is a blessing and a curse: a blessing, because in these times of tumult we need new ideas; a curse, because I’d rather sleep better and leave these worries to someone else. But leaving it to…

Worldwide most factories aim for low-cost and fast production ignoring resources and energy consumption. But, high revenues have been accompanied by environmental degradation. The United Nations reacted to the ecological problem and proposed the Sustainable Development Goals, and one of them is Sustainable Production (Goal 12). In addition, the participation of lightweight robots, such as collaborative robots, in modern industrial production is increasing. The energy consumption of a single collaborative robot is not significant, however, the consumption of more and more cobots worldwide is representative. Consequently, our research focuses on strategies to reduce the energy consumption of lightweight robots aiming for sustainable production. Firstly, the energy consumption of the lightweight robot UR10e is assessed by a set of experiments. We analyzed the results of the experiments to describe the relationship between the energy consumption and the evaluation parameters, thus paving the way to optimization strategies. Next, we propose four strategies to reduce energy consumption: 1) optimal standby position, 2) optimal robot instruction, 3) optimal motion time, and 4) reduction of dissipative energy. The results show that cobots potentially reduce from 3\% up to 37\% of their energy consumption, depending on the optimization technique. To disseminate the results of our research, we developed an AR game in which the users learn how to energy-efficiently program cobots.

A survey of 50 Nobel laureates asked about the greatest threats to mankind has revealed that environmental issues such as over-population and climate change are the biggest threat. Meanwhile, the threat of nuclear warfare and infectious diseases and drug resistance follows in second and third place. Distortion or the truth and ignorant political leaders also ranked highly, with President Donald Trump called out by name in this category. The survey drew responses from almost a quarter of the living Nobel prize winners for chemistry, physics, physiology, medicine and economics. A survey of 50 Nobel laureates posed the question: 'What is the biggest threat to humankind, in your view?

The smokestack of a refinery stands next to the Mantaro River in La Oroya, Peru. One of the things that has intrigued me the most about deep learning image cataloging algorithms is their ability to watch the world go by at scale each day through the incredible volume of news and social media images that are generated from every corner of the world and essentially generate a live ground truthed catalog of what's happening moment by moment. Of particular interest for disaster response and environmental monitoring is the ability of such algorithms to recognize imagery of flooding, drought, smog, litter, destruction, violence and other indicators of ongoing ground and air pollution and sudden natural disasters. What might a system look like? Two years ago I met Kadi Kenk, Head of Partnerships for "Let's do it" which is a social good organization founded in Estonia in 2008 that bills itself as a "social movement against trash."