🖨️ How Will The Apple Reality Pro Headset Boost 3D Printing?
While most AR/VR companies certainly rely on 3D printing to some extent, at least at the level of product design, Apple’s latest product, specifically, may kickstart a niche segment of the industry known as “additively manufactured electronics (AMEs).” To those who have been following the 3D printing industry, the most obvious method for squeezing electronics into small spaces is to use AMEs. With 3D printing, it’s possible to spray conductive traces onto curved surfaces using a technology called Aerosol Jet, from Optomec, which allows electronic features to be incorporated into the structure of a product, rather than force entirely separate components into already tight spaces.
The Sandia National Labs spinout has sold Aerosol Jet printers to Google, Meta, Samsung and has all-but-confirmed that Apple is using the process, as well. By 2016, Taiwanese manufacturer Lite-On Mobile used these systems to spray antennas onto millions of mobile phones before its then-senior manager of Technology Development for Antennas, Henrik Johansson, left to work for Apple.
However, it isn’t Aerosol Jet alone that may be used by these companies to shrink devices. In December 2022, Meta acquired optics firm Luxexcel with a goal of using its lens printing process to create AR glasses. Luxexcel’s method produces optically clear polymers with the ability to integrate waveguides, necessary for transparent displays, into its lenses. It’s no coincidence then that the social media-turned-metaverse giant will be releasing the newest version of its Quest Pro headset late this year, a device said to rival Apple’s Reality Pro.
⭐ Hunting For Hardware-Related Errors In Data Centers
The data center computational errors that Google and Meta engineers reported in 2021 have raised concerns regarding an unexpected cause — manufacturing defect levels on the order of 1,000 DPPM. Specific to a single core in a multi-core SoC, these hardware defects are difficult to isolate during data center operations and manufacturing test processes. In fact, SDEs can go undetected for months because the precise inputs and local environmental conditions (temperature, noise, voltage, clock frequency) have not yet been applied.
For instance, Google engineers noted ‘an innocuous change to a low-level library’ started to give wrong answers for a massive-scale data analysis pipeline. They went on to write, “Deeper investigation revealed that these instructions malfunctioned due to manufacturing defects, in a way that could only be detected by checking the results of these instructions against the expected results; these are ‘silent’ corrupt execution errors, or CEEs.”
Engineers at Google further confirmed their need for internal data, “Our understanding of CEE impacts is primarily empirical. We have observations of the form, ‘This code has miscomputed (or crashed) on that core.’ We can control what code runs on what cores, and we partially control operating conditions (frequency, voltage, temperature). From this, we can identify some mercurial cores. But because we have limited knowledge of the detailed underlying hardware, and no access to the hardware-supported test structures available to chip makers, we cannot infer much about root causes.”