A UCONN researcher wants to go backwards in time; Samsung's new TV rotates from horizontal to vertical; A new blockchain app illuminates the coffee supply chain; 3,500 ancient copper coins were returned from the US to Mexico; and a Steem essay describing the architecture of artificial neural networks
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- Meet the scientist trying to travel back in time - UCONN's Ron Mallet has been inspired by the idea of space travel ever since his childhood in the 1950s, when he was impacted by two events: the death of his father, and reading some of Einstein's writings. Einstein's work reveals that a sort-of time travel into the future is possible by traveling at very high speeds. In a common thought experiments, an Astronaut flies away and back at the speed of light during a two year trip. Upon returning to Earth, because the relative speed was so much slower, local time has passed far more quickly. Effectively, the astronaut has traveled into the future. The past, however is trickier. According to Mallet, the key to the past is gravity. According to Einstein's theory, gravity isn't really a force. Instead, large objects create gravity by twisting or warping space. So, the idea is that by twisting space the right way, a loop could be created where information could pass forwards and backwards through time. This is commonly known as a "worm hole". Mallet's unique twist is that he imagines using the gravity from a "ring laser" to control the necessary bending of space. He also says that he has done the math to prove that this could work, although it may not be implemented during our lifetimes. A limitation to the technique is that it would only enable time travel back to the time when the device was turned on. Time travel to before that time would still be impossible. -h/t RealClear Science
- Samsung just revealed a new rotating TV that's like a giant smartphone for your living room - Samsung revealed a TV that is expected to be seen at this week's Consumer Electronic Show (CES) conference. The TV can rotate horizontally and vertically in order to resemble the orientation of a cell phone. When synchronized with your smartphone or tablet, it will match that device's orientation.
- IBM and Fair Trade Initiative Demo Blockchain-Based Coffee Tracking App - At the Consumer Electronics Show (CES) on Monday, January 6, IBM and Farmer Connect demonstrated a blockchain-powered application that lets consumers learn about the supply chain of their coffee beans before purchasing. The Thank My Farmer application lets customers scan a bar-code and view an interactive map to show the journey their coffee took before being offered for sale. Founder and president of Farmer Connect, David Behrends, says that the app will be available to the general market place some time in 2020. One of the app's goals is to "humanize" coffee by giving consumers insights into the supply chain, and it also allows customers to make direct contributions to providers before the final retailer. A final goal is to improve sustainability for the coffee industry. Although the app was made through a partnership with IBM, it is not part of IBM's Food Trust Network. Instead, it utilizes some of the tools from the network in a stand-alone, independent ecosystem.
- US returns 3,500 copper coins that were in use more than 500 years ago - In a ceremony on December 30, the US returned 3,500 copper coins to Mexico. The coins are believed to have been used during the 13th to 16th centuries in the area of Mexico that is now covered by Michoacán and Guerrero. The coins had been legally purchased by a collector in the 1960s, but the subsequent participation by the US and Mexico in the UNESCO treaty now requires that such artifacts be returned to their countries of origin. Mexico notified the US of the existence of the coins when they were listed in a 2013 auction in Spain. The identity of the collector was not disclosed, but the two FBI agents who handled the case participated in the ceremony, as did the Consul General of Mexico in Miami. -h/t archaeology.org
- STEEM How AI Works: Part 2: Neural Networks - In this post, @bootlegbilly describes the operation of the artificial neural network. The post begins by describing the biological neuron, which has dendrites to receive information and axons to send it. The connections between neurons also vary in strength. The article goes on to describe how the computer mirror of this architecture, the perceptron, which takes input in a range between 0 and 1, and emits weighted output according to an internal function. As with biological neurons, the perceptrons need to be in networks in order to learn. Although there are many models for this network design, this post focuses on the feedforward network, or multi-layer model. In this model, a signal is passed to a layer of perceptrons, and they - in turn - modify the signal according to their internal functions and pass it along to another layer. This can be repeated into more layers until, eventually, a processed signal emerges to reflect the neural network's "decision". In a previous post, @bootlegbilly discussed the genetic algorithm. In a future post, the author promises to demonstrate how to combine them to implement a learning system. (A 10% beneficiary setting has been applied to this post for @bootlegbilly.)
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