Apple’s working on solving this problem, too, according to a report in Nikkei Asia. The newspaper says that Apple is working with TSMC, its primary processor manufacturer, to develop a new kind of augmented reality display that’s printed directly on wafers, or the base layer for chips.
If Apple does eventually reveal a big leap forward in AR display technology — especially if the technology is developed and owned by Apple instead of a supplier — Apple could find itself with multi-year head-start in augmented reality as it did when the iPhone vaulted it to the head of the smartphone industry.
Apple is also adding hardware to its iPhones that hint at a headset-based future. High-end iPhones released in 2020 include advanced Lidar sensors embedded in their camera.
Microsoft has invested heavily in these kind of technologies, purchasing AltspaceVR, a social network for virtual reality, in 2018. Before it launched Hololens, it paid $150 million for intellectual property from a smartglasses pioneer.
Facebook CEO Mark Zuckerberg speaks the most in public about his hopes for augmented reality. Last year, he said, “While I expect phones to still be our primary devices through most of this decade, at some point in the 2020s, we will get breakthrough augmented reality glasses that will redefine our relationship with technology.”
Artificial intelligence (AI) and machine learning are no longer fantastical prospects seen only in science fiction. Products like Amazon Echo and Siri have brought AI into many homes,
Kelly Calhoun Williams, an education analyst for the technology research firm Gartner Inc., cautions there is a clear gap between the promise of AI and the reality of AI.
Artificial intelligence is a broad term used to describe any technology that emulates human intelligence, such as by understanding complex information, drawing its own conclusions and engaging in natural dialog with people.
Machine learning is a subset of AI in which the software can learn or adapt like a human can. Essentially, it analyzes huge amounts of data and looks for patterns in order to classify information or make predictions. The addition of a feedback loop allows the software to “learn” as it goes by modifying its approach based on whether the conclusions it draws are right or wrong.
AI can process far more information than a human can, and it can perform tasks much faster and with more accuracy. Some curriculum software developers have begun harnessing these capabilities to create programs that can adapt to each student’s unique circumstances.
For instance, a Seattle-based nonprofit company calledEnlearn has developed an adaptive learning platform that uses machine learning technology to create highly individualized learning paths that can accelerate learning for every student. (My note: about learning and technology, Alfie Kohn in https://blog.stcloudstate.edu/ims/2018/09/11/educational-technology/)
GoGuardian, a Los Angeles company, uses machine learning technology to improve the accuracy of its cloud-based Internet filtering and monitoring software for Chromebooks. (My note: that smells Big Brother).Instead of blocking students’ access to questionable material based on a website’s address or domain name, GoGuardian’s software uses AI to analyze the actual content of a page in real time to determine whether it’s appropriate for students. (my note: privacy)
serious privacy concerns. It requires an increased focus not only on data quality and accuracy, but also on the responsible stewardship of this information. “School leaders need to get ready for AI from a policy standpoint,” Calhoun Williams said. For instance: What steps will administrators take to secure student data and ensure the privacy of this information?