Slashgear: DeepSolar Project uses machine learning, satellite imagery to calculate US solar panels

Slashgear: DeepSolar Project uses machine learning, satellite imagery to calculate US solar panels. “As the use of renewable energy, in this case solar power, continues to rise in the US, there’s also a growing need to better understand not just how much of the country’s energy comes from solar, but also how many solar panels are in use and where they are installed. While the government and utilities can offer estimates on commercial installations, the lack of data on individual residential installations makes these inaccurate. That’s where Stanford University’s DeepSolar Project aims to help.”

Stanford: Stanford Libraries’ transformative gift creates hub highlighting Silicon Valley history

Stanford: Stanford Libraries’ transformative gift creates hub highlighting Silicon Valley history. “Exhibition areas will be located throughout Hohbach Hall and feature such items from the Silicon Valley Archives as design documents and drawings for Douglas Engelbart’s first computer mouse prototype and early audio and video recording technology from the Ampex Corp. collection. The spaces will allow staff to curate and display, in physical and digital forms, documents, photographs, equipment and ephemera from some of Silicon Valley’s largest companies.”

Stanford PACS: Glasnost! Nine Ways Facebook Can Make Itself a Better Forum for Free Speech and Democracy

Stanford PACS: Glasnost! Nine Ways Facebook Can Make Itself a Better Forum for Free Speech and Democracy. “Facebook could make nine ‘incremental’ changes to ensure it becomes a better forum for free speech and democracy, according to a new report by academics at the University of Oxford in the UK and Stanford University in the US. Proposals include: an external appeals body; more user control over News Feeds; and better content review and fact-check mechanisms.” The report is available for free download at this link.

Tech Xplore: Team locates nearly all US solar panels in a billion images with machine learning

Tech Xplore: Team locates nearly all US solar panels in a billion images with machine learning. “Knowing which Americans have installed solar panels on their roofs and why they did so would be enormously useful for managing the changing U.S. electricity system and to understanding the barriers to greater use of renewable resources. But until now, all that has been available are essentially estimates. To get accurate numbers, Stanford University scientists analyzed more than a billion high-resolution satellite images with a machine learning algorithm and identified nearly every solar power installation in the contiguous 48 states.”

Scope Stanford: New algorithm could accelerate diagnosis of genetic diseases using clinical records

Scope Stanford: New algorithm could accelerate diagnosis of genetic diseases using clinical records. “In a continued effort to speed up the diagnostic process of severe genetic diseases, Stanford’s Gill Bejerano, PhD, and his colleagues have developed a new algorithm that can quickly locate important disease-related information within a patient’s medical record.”

Stanford University: Stanford scholars are helping journalists do investigative journalism through data

Stanford University: Stanford scholars are helping journalists do investigative journalism through data. “A team of Stanford University scholars are launching a data-driven initiative to help journalists find stories at a lower cost, to support local newsrooms explore public interest issues and fight against misinformation.”

Slate: Facebook’s Crackdown on Misinformation Might Actually Be Working

Slate: Facebook’s Crackdown on Misinformation Might Actually Be Working. “Facebook’s efforts to reduce misinformation in its news feed since the 2016 election have opened the company to all manner of criticism, including allegations of political bias from both left and right. But a new study from researchers at Stanford University, New York University, and Microsoft Research suggests they might actually be working—at least, to some extent.”