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Birth of the Bionic Eye

In 2012, electrodes will bring eyesight to the blind

3 min read
Photo: David Yellen
Seeing the Sights: Barbara Campbell’s retinal prosthesis sends 30 images per second to her optic nerve.
Photo: David Yellen

When light hits Barbara Campbell’s eyes, it triggers no response in her retinas, and no signals flash up her optic nerves to her brain. A genetic disease killed off her retinas’ photoreceptor cells, leaving her completely blind by her 30s. But where her body failed her, technology rescued her. In 2009, at the age of 56, Campbell had an array of electrodes implanted in her left eye, and she now makes her way through the world more confidently, aided by bionic vision.

Her sight isn’t fully restored, not by a long shot, but the darkness has been replaced with rough shapes and patterns of light and dark. “The building where I live has a large light at the entranceway outside,” says Campbell, who lives in New York City. “I hadn’t been able to see that light in 16 years. Now, when I’m walking down the block, I can look up and identify the building.”

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The World’s Largest Camera Is Nearly Complete

The future heart of the Vera C. Rubin Observatory will soon make its way to Chile

3 min read
A large black cylinder with a glass lens in front rests on a sturdy white structure in a bright room.

The LSST camera, eventually bound for the Vera C. Rubin Observatory in Chile, sits on its stand in a Bay Area clean room.

Jacqueline Ramseyer Orrell/SLAC National Accelerator Laboratory

The world’s largest camera sits within a nondescript industrial building in the hills above San Francisco Bay.

If all goes well, this camera will one day fit into the heart of the future Vera C. Rubin Observatory in Chile. For the last seven years, engineers have been crafting the camera in a clean room at the SLAC National Accelerator Laboratory in Menlo Park, Calif. In May 2023, if all goes according to plan, the camera will finally fly to its destination, itself currently under construction in the desert highlands of northern Chile.

Building a camera as complex as this requires a good deal of patience, testing, and careful engineering. The road to that flight has been long, and there’s still some way to go before the end is in sight.

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Lab Revisits the Task of Putting Common Sense in AI

New nonprofit Basis hopes to model human reasoning to inform science and public policy

5 min read
ai hand and human hand touching pointer fingers
iStock

The field of artificial intelligence has embraced deep learning—in which algorithms find patterns in big data sets—after moving on from earlier systems that more explicitly modeled human reasoning. But deep learning has its flaws: AI models often show a lack of common sense, for example. A new nonprofit, Basis, hopes to build software tools that advance the earlier method of modeling human reasoning, and then apply that method toward pressing problems in scientific discovery and public policy.

To date, Basis has received a government grant and a donation of a few million dollars. Advisors include Rui Costa, a neuroscientist who heads the Allen Institute in Seattle, and Anthony Philippakis, the chief data officer of the Broad Institute in Cambridge, Mass. In July, over tacos at the International Conference on Machine Intelligence, I spoke with Zenna Tavares, a Basis cofounder, and Sam Witty, a Basis research scientist, about human intelligence, problems with academia, and trash collection. The following transcript has been edited for brevity and clarity.

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Modeling Microfluidic Organ-on-a-Chip Devices

Register for this webinar to enhance your modeling and design processes for microfluidic organ-on-a-chip devices using COMSOL Multiphysics

1 min read
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Comsol

If you want to enhance your modeling and design processes for microfluidic organ-on-a-chip devices, tune into this webinar.

You will learn methods for simulating the performance and behavior of microfluidic organ-on-a-chip devices and microphysiological systems in COMSOL Multiphysics. Additionally, you will see how to couple multiple physical effects in your model, including chemical transport, particle tracing, and fluid–structure interaction. You will also learn how to distill simulation output to find key design parameters and obtain a high-level description of system performance and behavior.

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