Traditional reading involves publishing text in lines and moving your eyes sequentially from word to word. For each word, the eye seeks a certain point within the word, which we call the “Optimal Recognition Point” or ORP. After your eyes find the ORP, your brain starts to process the meaning of the word that you’re viewing. With each new word, your eyes move, called a “saccade”, and then your eyes seek out the ORP for that word. Once the ORP is found, processing the word for meaning and context occurs and your eyes move to the next word. When your eyes encounter punctuation within and between sentences, your brain is prompted to assemble all of the words that you have read and processes them into a coherent thought.
When reading, only around 20% of your time is spent processing content. The remaining 80% is spent physically moving your eyes from word to word and scanning for the next ORP. With Spritz we help you get all that time back. For more in-depth scientific explanations on just about everything that you might want to know about how Spritz works, check out our Blog section.
Not too long ago, the NMC Horizon Report: 2014 Higher Education Edition was released, with the aim of examining emerging technologies for their potential impact on and use in teaching and learning within higher education settings. This is the eleventh time the New Media Consortium has put out this report, and it is interesting to look back …
Mention the term “wearables” and most people conjure up a fitness-tracking watch or some kind of futuristic fashion accessory. But wearables are much more. Consider, for instance, Mind-controlled wheelchairs or Stress-monitoring devices for autistic children!
DATA NOW STREAM from daily life: from phones and credit cards and televisions and computers; from the infrastructure of cities; from sensor-equipped buildings, trains, buses, planes, bridges, and factories. The data flow so fast that the total accumulation of the past two years—a zettabyte—dwarfs the prior record of human civilization. “There is a big data revolution,” saysWeatherhead University Professor Gary King. But it is not the quantity of data that is revolutionary. “The big data revolution is that now we can do something with the data.”
The revolution lies in improved statistical and computational methods, not in the exponential growth of storage or even computational capacity, King explains. The doubling of computing power every 18 months (Moore’s Law) “is nothing compared to a big algorithm”—a set of rules that can be used to solve a problem a thousand times faster than conventional computational methods could. One colleague, faced with a mountain of data, figured out that he would need a $2-million computer to analyze it. Instead, King and his graduate students came up with an algorithm within two hours that would do the same thing in 20 minutes—on a laptop: a simple example, but illustrative.
New ways of linking datasets have played a large role in generating new insights. And creative approaches to visualizing data—humans are far better than computers at seeing patterns—frequently prove integral to the process of creating knowledge. Many of the tools now being developed can be used across disciplines as seemingly disparate as astronomy and medicine. Among students, there is a huge appetite for the new field. A Harvard course in data science last fall attracted 400 students, from the schools of law, business, government, design, and medicine, as well from the College, the School of Engineering...
Last weekend we saw how doctors were using 3D printing to help them better understand heart issues, which were related to specific patients, prior to them operating. This week we got word of a new application for 3D printing within the cardiac field of medicine. This time it’s an embeddable device, which promises to change the way doctors monitor, as well as treat many heart conditions.
A team of doctors, led by Igor Efimov, PhD, at the School of Engineering & Applied Science at Washington University in St. Louis, have used an inexpensive 3D printer, one like those you would see in the homes of hobbyists, to create a device which may lead to major advances within the predictive cardiac medical field. The team of doctors, biomedical engineers, and material scientists
We live in a world of unending progress. But technological advancement poses as many difficult questions as it answers.
Editor's note: Every Sunday, Fortune publishes a favorite story from our magazine archives. This week, to mark our Future Issue, we turn to a feature from June 1955 by John von Neumann tackling the profound questions wrought by radical technical advancement—in von Neumann's day the atomic bomb and climate change. von Neumann was one of the twentieth century's greatest and most influential geniuses. The polymath and patron saint of Game Theorywas instrumental in developing America's nuclear superiority toward the end of World War II as well as in framing the decades-long Cold War with the Soviet Union. In his time, von Neumann was said to possess "the world's greatest mind." Here is his characteristically pessimistic look on what the future holds.
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Key evidence suggests that as hospital systems in the US reach a crisis point – involving the transition to value-based purchasing and tying Medicare and Medicaid dollars to performance – quality of care must improve. In many ways hospital employees have become the most important piece of the puzzle to improve efficiency, lower costs and improve outcomes. Disengaged employees in the US who turnover, for example, are estimated to cost as much as $11 billion annually due to lost productivity and poor results. As hospital leadership faces a new domain of uncertainty and demands, and must use innovative technologies to better understand and improve engagement and performance of employees, two gamers think they have the answer: real-time evaluation, fun gaming interaction and a culture of positive reinforcement. The team at AMPT Health is gambling that their new SaaS solution will revolutionize performance evaluation.
Gamification is a trend that doesn’t seem to be going away any time soon. Incorporating game play elements into your classroom can help to create a dynamic, interactive environment that will help get and keep your students engaged in the material and excited to learn. It sounds great, right? But every trend will see a …
It’s not often that a week goes past when I don’t hear a new story of a company being ripped apart as it struggles to deal ever more demanding and fickle consumers. Marketing and sales, it’s usually said, have gone rogue leaving finance and IT to pick up the pieces. It’s obviously important to keep selling (and to keep generating revenue), but it’s equally important to do so in a safe and compliant manner (so that you’re still in business next year).
This situation has become bad enough that the analysts are now suggesting that a shift in operating model will be required to solve the problem. That sounds about right, and it looks like the trigger for the shift will be external pressure from regulators.
The problem, then, is to form a sensible picture of how this to-be operating model will function.
Coming up with some general statements about that nature of this new model is fairly easy: it will be more collaborative, it will favor services over assets, innovation will be important, and so on.
What is more important, and much harder to do, is to develop a picture of how the shift to a new operating model will change the roles and responsibilities within a business. How will we heal the rift between the front office – sales and marketing – and the back office – finance and IT?
Automated retail systems like ATMs, kiosks and self-service checkout lines marked the beginning of the robotic revolution. Over the course of fifteen years starting in 2001, these systems proliferated and evolved until nearly every retail transaction could be handled in an automated way. Five million jobs in the retail sector were lost as a result of these systems.
The next step was autonomous, humanoid robots. The mechanics of walking were not simple, but Honda had proven that those problems could be solved with the creation of its ASIMO robot at the turn of the century. Sony and other manufacturers followed Honda's lead. Over the course of two decades, engineers refined this hardware and the software controlling it to the point where they could create humanoid bodyforms with the grace and precision of a ballerina or the mass and sheer strength of the Incredible Hulk.
Decades of research and development work on autonomous robotic intelligence finally started to pay off. By 2025, the first machines that could see, hear, move and manipulate objects at a level roughly equivalent to human beings were making their way from research labs into the marketplace. These robots could not "think" creatively like human beings, but that did not matter. Massive AI systems evolved rapidly and allowed machines to perform in ways that seemed very human.
Humanoid robots soon cost less than the average car, and prices kept falling. A typical model had two arms, two legs and the normal human-type sensors like vision, hearing and touch. Power came from small, easily recharged fuel cells. The humanoid form was preferred, as opposed to something odd like R2-D2, because a humanoid shape fit easily into an environment designed around the human body. A humanoid robot could ride an escalator, climb stairs, drive a car, and so on without any trouble.
Once the humanoid robot became a commodity item, robots began to move in and replace humans in the workplace in a significant way. The first wave of replacement began around 2030, starting with jobs in the fast food industry. Robots also filled janitorial and housekeeping positions in hotels, motels, malls, airports, amusement parks and so on.
The economics of one of these humanoid robots made the decision to buy them almost automatic. In 2030 you could buy a humanoid robot for about $10,000. That robot could clean bathrooms, take out trash, wipe down tables, mop floors, sweep parking lots, mow grass and so on. One robot replaced three six-hour-a-day employees. The owner fired the three employees and in just four months the owner recovered the cost of the robot. The robot would last for many years and would happily work 24 hours a day. The robot also did a far better job -- for example, the bathrooms were absolutely spotless. It was impossible to pass up a deal like that, so corporations began buying armies of humanoid robots to replace human employees.
The first completely robotic fast food restaurant opened in 2031. It had some rough edges, but by 2035 the rough edges were gone and by 2040 most restaurants were completely robotic. By 2055 the robots were everywhere. The changeover was that fast. It was a startling, amazing transformation and the whole thing happened in only 25 years or so starting in 2030.
In 2055 the nation hit a big milestone -- over half of the American workforce was unemployed, and the number was still rising. Nearly every "normal" job that had been filled by a human being in 2001 was filled by a robot instead. At restaurants, robots did all the cooking, cleaning and order taking. At construction sites, robots did everything -- Robots poured the concrete, laid brick, built the home's frame, put in the windows and doors, sided the house, roofed it, plumbed it, wired it, hung the drywall, painted it, etc. At the airport, robots flew the planes, sold the tickets, moved the luggage, handled security, kept the building clean and managed air traffic control. At the hospital robots cared for the patients, cooked and delivered the food, cleaned everything and handled many of the administrative tasks. At the mall, stores were stocked, cleaned and clerked by robots. At the amusement park, hundreds of robots ran the rides, cleaned the park and sold the concessions. On the roads, robots drove all the cars and trucks. Companies like Fedex, UPS and the post office had huge numbers of robots instead of people sorting packages, driving trucks and making deliveries.
By 2055 robots had taken over the workplace and there was no turning back.
Talk about exponential progress in technology. If the Department of Energy’s Oak Ridge National Laboratory (ORNL) has its way, we will have a 3D printer capable of printing out polymer objects at speeds anywhere from 200-500 times faster than the 3D printers used in manufacturing facilities today. If that’s not enough to get you excited about where the 3D printing industry is headed, than maybe the fact that they are also looking to print items which are 10 times larger than those printed with machines today, will.