Tech Unveiled: 35 Intriguing Facts You Didn’t Know About Modern Technologies

26ARCHIMEDES Laser

ARCHIMEDES Laser

One of Jupiter's moons, Europa is known to have a huge ocean underneath its icy surface. NASA is developing an ice-penetrating technology called ARCHIMEDES that uses laser light to penetrate Europa’s crust and allow explorers to access its underlying ocean.



27. Thanks to 3D printing, NASA can basically “email” tools to astronauts.



28. Scientists have managed to recreate the voice of a 3000-year-old mummified Egyptian priest. They produced a 3D-printed voice box based on a precise scan of his vocal tract, and then used the vocal tract with an artificial larynx sound, synthesizing a vowel-like sound reminiscent of a sheep’s bleat.



29. A solar flare acts as an electromagnetic pulse and if the earth was hit by a large enough flare it could fry every microchip and piece of technology in existence.



30. Each person has a “walking signature” that can be detected by their smartphone’s accelerometer data. The signature persists even if you change phones.



31Lockpicking with Smartphones

Lockpicking with Smartphones

Researchers have figured out a way to break into locks by using a smartphone to record the sound of a key being inserted. They were able to narrow down the range from more than 330,000 keys to 3.



32. “Smart” toilets identify users through their fingerprints and distinctive features of their anoderm to analyze excreta using computer vision and deep learning. The data is then encrypted and stored in the cloud.



33. Cosmic rays can trigger bitflips (Soft Errors) in computers and other tech devices causing them to glitch in disastrous ways.



34. Smart Dust is a miniature sensing chip with an autonomous power supply, computing, and wireless communication in a space that is typically only a few millimeters in volume. With such a small size, these devices can stay suspended in an environment just like a particle of dust.



35. Artificial Intelligence can predict aftershocks better than trained seismologists. The machine learning process - termed “neural-network forecast” outperformed the traditional “stress-failure” method by allowing computers to consider additional variables, including stresses in metals.