Machine learning is a popular topic in most industries these days, and it will come as no surprise that this is true for astronomy and astrophysics as well. University of Colorado PhD student Avery Schiff explores how a deep learning algorithm is being used to classify galaxy morphologies in this article from graduate student astronomy journal Astrobites.
The search for extraterrestrial life is bound to lead one place — underwater. To prepare for this reality, scientists from Harvard and the Woods Hole Oceanographic Institution are narrowing in on autonomous ocean-floor vehicles equipped with cutting edge cameras and sophisticated sensors that can wirelessly alert researchers hundreds of miles away when something of note happens. Pretty cool stuff? We’d say so.
David Latham of the Harvard-Smithsonian Center for Astrophysics is tasked with an incredible mission — overseeing the selection and study of planets that are viable candidates for life as captured by TESS (the Transiting Exoplanet Survey Satellite). In this interview with the Harvard Gazette, Latham discusses everything from TESS’s ground-breaking camera technology to the conditions required to foster life as we do (or don’t) know it.
Companies that contribute to (and use) open source software can gain a competitive advantage—even though they may be helping their competitors in the short run. The reason? Contributing to crowdsourced “public goods” that benefit other firms or industries can enable companies to gain valuable insights and compete more effectively in the long term. Call it the “Linux effect.”
When Professor Ethan Bernstein used wearable technology to track workers around their open office, he discovered many who were trying to avoid collaboration rather than engage in it. This research throws a wrench in the much-hyped claims that open office plans increase productivity and collaboration.
It’s a declaration we’ve all heard before: “We need more collaboration! We need to break out of our silos and build integrated, cross-functional teams!” But what if — when it comes to collaboration — there can be too much of a good thing? This is the hypothesis Professor Jeff Polzer set out to test with his research on collaborative overload, that is how the amount of collaboration relates to organizational productivity. Using digital trace data to analyze organizational productivity at scale, Professor Polzer finds some answers that may surprise you.
Despite mounting evidence that innovation tools such as crowdsourcing are better, faster, and cheaper, it is still difficult for organizations to embrace this change. Held at HBS, the first annual Crowd Academy brought together researchers and industry experts to further the conversation on crowdsourcing, open innovation, and the future of work.
