In this Future of Everything podcast on diversity in engineering, Sheri Sheppard, professor, mechanical engineering, who got her start in engineering working at GM, Ford and Chrysler discusses the need for engineering curriculum to have an interdisciplinary approach and explore the "peopleness" in challenges engineers work to solve.
A team of researchers from Stanford, Facebook AI Research, and McGill University has developed a tool that measures how much electricity a machine learning project uses and how much that means in carbon emissions.
Are individuals owed explanations when AI makes decisions that affect their lives? Kate Vredenburgh, HAI and McCoy Family Center for Ethics and Society postdoctoral fellow (seen at left), discusses what it would mean to implement such a right. If AI developers know they will have to justify their work during implementation the hope is this would create incentives for building more morally justifiable algorithms. Link
In the face of COVID-19 to keep workers safe and continue operations, companies have ramped up remote work and are aggressively automating some operations and exploring machine learning (ML). Prof. Erik Brynjolfsson, director of Stanford HAI's Digital Economy Lab, along with scientists from CMU and MIT, have identified tasks most suitable for ML. While more tasks in lower wage jobs could be replaced by ML, no occupation is immune.
To understand what it takes for sustainability efforts to deliver lasting benefits, Stanford scientists looked through some of the biggest sustainability efforts from the past 25 years to understand what makes solutions hold at large scale. Strong multi-stakeholder, multi-level coalitions formed around ambitious objectives are needed to create transformation at scale.
BEAM, Stanford Career Education, is hosting a virtual engineering alumni career fair with Stanford alumni from all engineering disciplines and degree levels seeking full and part time positions. If you are interested in learning more about the event, or to register, please click here to access Handshake, the Career Education platform. BEAM is offering a 15% discount to Stanford Affiliates.
Kyle Julian with the Stanford Intelligent Systems Lab, presents his Ph.D. defense on the use of neural networks on aircraft guidance and control systems. Julian outlines his work on neural network compression of score table policies, neural network verification and validation of image-based neural net. Link
At our May webinar, Grace Gao, assistant professor, aeronautics and astronautics and director of the Stanford Navigation and Autonomous Vehicles Lab discussed her work on reliable and safe positioning and navigation for autonomous systems. Gao provided examples of model-driven, data-driven and proof-based approaches for intelligently fusing GPS, LiDAR, vision and inertial measurements. View the webinar recording here.
The National Research Cloud, an initiative proposed by John Etchemendy and Fei-Fei Li, co-directors of the Stanford Institute for Human-Centered Artificial Intelligence (seen here at left) and backed by Stanford, CMU and Ohio State and tech companies including Google, Amazon, Microsoft and IBM received bipartisan support in both the House and the Senate.
Modern cars with superior vehicle engineering like electronic stability control are safer for legions of drivers but for those who prefer the more pure driving experience of machines of the past, older cars provide an understanding of handling that had less-than-friendly handling characteristics.
