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Using 3D printing and porous silicon, researchers at the University of Illinois Urbana-Champaign have developed compact, visible wavelength achromats that are essential for miniaturized and lightweight optics. These high-performance hybrid micro-optics achieve high focusing efficiencies, while minimizing volume and thickness. Further, these microlenses can be constructed into arrays to form larger area images for achromatic light-field imagers and displays.

This study was led by and engineering professors Paul Braun and David Cahill, electrical and computer engineering professor Lynford Goddard and former graduate student Corey Richards. The results of this research were published in Nature Communications.

“We developed a way to create structures exhibiting the functionalities of classical compound optics but in highly miniaturized thin from, via non-traditional fabrication approaches,” says Braun.

Tesla CEO Elon Musk has alluded to an upcoming “tap to park” feature for the automaker’s Full Self-Driving (FSD) beta. While it isn’t clear when it’s expected to become available, some have already pointed out how useful such a feature could be.

On Friday, Musk responded to a post on X saying that Tesla is developing a feature in which the car identifies potential parking space options, letting users tap the one they want to use. Upon doing so, the driver will then be able to leave the vehicle before the vehicle parks in the selected space.

The statement came in response to another post claiming that a 360-degree bird’s eye view would be irrelevant in a world of self-driving vehicles, as the driver wouldn’t need to do anything at all for the vehicle to locate and park in a specific spot.


Abstract. Individual differences in the spatial organization of resting-state networks have received increased attention in recent years. Measures of individual-specific spatial organization of brain networks and overlapping network organization have been linked to important behavioral and clinical traits and are therefore potential biomarker targets for personalized psychiatry approaches. To better understand individual-specific spatial brain organization, this paper addressed three key goals. First, we determined whether it is possible to reliably estimate weighted (non-binarized) resting-state network maps using data from only a single individual, while also maintaining maximum spatial correspondence across individuals. Second, we determined the degree of spatial overlap between distinct networks, using test-retest and twin data.