Climate change is an increasingly pressing issue. We’re now in a COVID-19 world, and as climate risks increase, they will overlap with pandemic risks. Jurisdictions are already struggling to deal with flooding emergency shelters and cooling shelters in the face of the disease. As recent reports have shown, the rate of increase is accelerating and the expected temperature increases are going to be higher. We need better data and solutions.
Enter machine learning. Neural nets now exist on our smartphones doing facial recognition. They are in Teslas driving themselves down highways near you. They are improving the quality of massive data sets on coast sea level rise risks. They are rapidly transforming and accelerating the way in which complex and sophisticated software solutions are developed and delivered. They are sorting our trash and keeping our water supplies safe.
Into this world comes CleanTechnica’s groundbreaking report on the intersection of machine learning and clean technology. The primary author, Michael Barnard, a business and technical strategist and author with a career that has spanned four continents over the past 20 years, guides non-technical people through the key concepts that they should understand to see if machine learning techniques would accelerate their efforts. His case studies cover entrepreneurs, governmental studies and academic efforts around the world. And his use of a fictional robotic velociraptor guided by neural nets keeps the reading grounded but whimsically light-hearted. Previous CleanTechnica reports from Michael Barnard include a deep case study of an air carbon capture technology firm and its misleading claims and a global review of blockchain’s use in clean technology.
The foreword by Paul J. Werbos, Ph.D. Co-Director, Center for Intelligent Optimization & Networks, an early researcher into neural nets, a former Program Director at the US National Science Foundation and a former Brookings Fellow, lays out the deep concerns he has for climate change and the need for accelerated deployment of neural net technologies and transformative technologies to avoid them.
Policy makers around the world will find this useful to see what technological advances related to machine learning should be shaping their strategic initiatives. Investors will learn to separate the glitter from the meat of advanced neural net investment opportunities. Academics will see many opportunities for both new research and commercialization of their work. Entrepreneurs will see how they can exploit the newly democratized machine learning technologies to build new services and products.
Climate change is the most pressing concern of the 20th Century, even though COVID-19 has captured our attention this year. Machine learning and clean technologies are key to addressing it.
You can see a report preview here.