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I am for ethical Ai. What about you?


Sophia interviews Stanford AI Researcher Tina White about how A.I. & Robotics can help stop the spread of Covid19 through contact tracing while preserving users’ privacy.

- What are you doing to stop the spread? 0:50
- What is contact tracing? How does it help stop the spread? 2:28
- How did you get the idea for your app? 2:54
- Why is privacy important to humans? 3:46.

Check out Tina’s app here: https://www.covid-watch.org/

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The One Love Machine band are a scrappy crew. They have an affinity for punk rock, and members of the band play the bass, drums and flute. Oh, and they’re all robots. The band is made up of scrap metal animatronics, created from salvaged junk from scrapyards around Berlin. For creator of the band Kolja Kugler, it’s all about giving new life to discarded objects.

Storage is just as important aboard the International Space Station as it is on Earth. While the space station is about the size of a football field, the living space inside is much smaller than that. Just as you wouldn’t store garden tools in a house when you could store them in a shed outside, astronauts now have a “housing unit” in which they can store tools for use on the exterior of the space station.

On Dec. 5, 2019, a protective storage unit for robotic tools called Robotic Tool Stowage (RiTS) was among the items launched to station as part of SpaceX’s 19th commercial resupply services mission for NASA. As part of a spacewalk on July 21, NASA astronauts Robert Behnken and Chris Cassidy installed the “robot hotel” where the tools are stored to the station’s Mobile Base System (MBS), where it will remain a permanent fixture. The MBS is a moveable platform that provides power to the external robots. This special location allows RiTS to traverse around the station alongside a robot that will use the tools it stores.

exterior view of portion of ISS, with blue-hued Earth in background

Proteins are essential to the life of cells, carrying out complex tasks and catalyzing chemical reactions. Scientists and engineers have long sought to harness this power by designing artificial proteins that can perform new tasks, like treat disease, capture carbon, or harvest energy, but many of the processes designed to create such proteins are slow and complex, with a high failure rate.

In a breakthrough that could have implications across the healthcare, agriculture, and energy sectors, a team lead by researchers in the Pritzker School of Molecular Engineering (PME) at the University of Chicago has developed an -led process that uses big data to design new proteins.

By developing machine-learning models that can review protein information culled from genome databases, the researchers found relatively simple design rules for building . When the team constructed these artificial proteins in the lab, they found that they performed chemistries so well that they rivaled those found in nature.