It was not so long ago that sequencing even tiny snippets of DNA was a costly, cumbersome process that required access to a state-the-art lab. Today, we are inching close to putting a DNA sequencer in every pocket.
Teleport is a telepresence robot that can be used by people with a disability to attend school or work remotely. It can be controlled using an internet browser, Android phone, and now brain control.
Very cool.
Scientists have developed a new 5D technique for analysing images, an advance that may make it easier to quickly find tell-tale signs of diseases from pictures taken using cell phones. Called “Hyper-Spectral Phasor” analysis, or HySP, it is much faster and far less expensive than current techniques, and may be useful for diagnosing and monitoring diseases by using cell phone images, researchers said.
Through the new imaging technology, researchers at the University of Southern California (USC) in the US have used fluorescent imaging to locate proteins and other molecules in cells and tissues. It works by tagging the molecules with dyes that glow under certain kinds of light – the same principle behind so-called “black light” images.
Continue reading “New 5D technique may help diagnose diseases from cell phone images” »
Pre-order at http://www.superpedestrian.com This is the first commercial version of the Copenhagen Wheel. Now available for sale.
Own a limited edition, hand-crafted Copenhagen Wheel, invented and built in Cambridge, MA.
The Copenhagen wheel Technical specifications:
MOTOR US: 350W / EU: 250W
WEELE SIZE 26″ or 700c rim
BATTERY Removable 48Volt Lithium
CONNECTIVITY Bluetooth 4.0
BATTERY LIFE 1000 cycles
SMARTPHONE OS iOS, Android
CHARGE TIME 4 hours
COMPATIBILITY Single Speed or 9/10 Speed Free Hub (email us your bike specs if you have doubts: [email protected])
TOP SPEED US: 20 mph
EU: 25 km/h
BRAKE TYPE Rim brake and regenerative braking (downhill and back-pedal)
RANGE Up to 50 km / 31 mi
WEIGHT 5.9 kg / 13 lbs
DROPOUT 135 mm
Continue reading “The Copenhagen Wheel official product release” »
If SANTOSH Ostwal and his wife, Rajashree Otswal, were to calculate the number of electricity units saved or the amount of water conserved in terms of money, thanks to their invention, it would be enough to set up a small power plant or building a small dam. The end to a farmer’s daily drudgery and sleepless nights, though, is hard to convert into currency. But then money is something the Ostwal couple have not seen much of in their long journey of taking technology to the farms.
Much before information and communication technology (ICT) for agriculture and rural development became buzzwords and ‘e’ got hyphenated to everything, the Ostwals, both engineers, ventured into wireless irrigation and mobile-to-mobile (M2M) communication systems for agriculture. A remotely controlled pump using the mobile phone and combing it with some clever electronics was the innovation that has made the lives of farmers easier.
The Ostwals’ invention has impacted the lives of four lakh farmers with 50,000 installations in the last 12 years. A smart and affordable device, Nano Ganesh, saves farmers from making treacherous trips in pitch dark to their farms at midnight to access their water pumps and operate them, a daily reality, especially with erratic power supply. When the tired farmer fails to go out and switch off the water pump, there’s wastage of water and electricity. In addition, the excess water damages the soil and crop, hurting them further. If that is not enough, there is the theft of water pumps and cables to be dealt with. These are the problems that the couple set to solve.
This kit by Royal College of Art graduate Heeju Kim uses sweets to recreate the tongue-tying experience of living with autism. Kim created three tools and a mobile application as part of the project, which is titled An Empathy Bridge for Autism.
A set of six awkwardly shaped lollipops and candies impede tongue movement in various ways. They make it hard for users to hold a conversation, conveying how unclear pronunciation has an impact on autistic individuals.
An augmented-reality headset is worn over the eyes and connects to a smartphone to alter the user’s perception of what’s in front of them. It restricts the view of their periphery, gives them double vision or obscures their focus with a patch of black.
Continue reading “Empathy kit to help users better understand autism” »
In 1965, Intel co-founder Gordon Moore published a remarkably prescient paper which observed that the number of transistors on an integrated circuit was doubling every two years and predicted that this pace would lead to computers becoming embedded in homes, cars and communication systems.
That simple idea, known today as Moore’s Law, has helped power the digital revolution. As computing performance has become exponentially cheaper and more robust, we have been able to do a lot more with it. Even a basic smartphone today is more powerful than the supercomputers of past generations.
Yet the law has been fraying for years and experts predict that it will soon reach its limits. However, I spoke to Bernie Meyerson, IBM’s Chief Innovation Officer, and he feels strongly that the end of Moore’s Law doesn’t mean the end of progress. Not by a long shot. What we’ll see though is a shift in emphasis from the microchip to the system as a whole.
Continue reading “Moore’s Law Will Soon End, but Progress Doesn’t Have to” »
In Brief
Foxconn Electronics, the Taiwanese manufacturing company behind some of the biggest electronic brands’ devices, including Apple’s iPhone, has announced that it will ramp up automation processes at its Chinese factories. The goal is to eventually achieve full automation.
In an article published in Digitimes, General Manager Dai Jia-peng of Foxconn’s Automation Technology Development Committee explains that the process will unfold in three phases.
Continue reading “Apple Manufacturer Foxconn to Fully Replace Humans With Robots” »
Apple’s first paper on artificial intelligence, published Dec. 22 on arXiv (open access), describes a method for improving the ability of a deep neural network to recognize images.
To train neural networks to recognize images, AI researchers have typically labeled (identified or described) each image in a dataset. For example, last year, Georgia Institute of Technology researchers developed a deep-learning method to recognize images taken at regular intervals on a person’s wearable smartphone camera.
Continue reading “Apple’s first AI paper focuses on creating ‘superrealistic’ image recognition” »
