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"Over the last five years, technology has been rapidly changing and expanding in every field imaginable. Smart phones are now capable of acting as standalone computer devices that can take pictures, search the Internet, send emails and text messages and yes, they even make phone calls. While it might seem that the technology of today has reached its limits, it is still actually spreading its proverbial wings. Only twenty or so years ago, personal computers were becoming small enough and affordable enough for families to buy them for home use. Since then, the world of technology has shown no signs of slowing down and practically every device available today is somehow tied to computer technology. It seems hard these days to fathom the original size of computers and how small they have become in the last ten years, but within the last five years they have become even smaller and somehow more powerful and faster than ever before! The Internet allows people to connect with family, friends, and work colleagues from across the globe in the push of a button. Communication options have literally exploded in the instant avenues of text and video based chat as well as the near instantaneous method of email. Gone are the days where one had to post a letter and wait a week or more for a response and long distance phone calls are unnecessary for anyone with a computer, a webcam, and a speedy Internet connection. Automobiles are now being manufactured with standard GPS and emergency call features for the convenience and safety of drivers and their passengers, making the days of carrying a map completely unnecessary and improving the peace of mind of anyone who must travel the roads alone or at night. Computerized cars are now potentially at risk in much the same fashion as a personal computer as a moderately skilled hacker can theoretically take over basic functions of a vehicle - including its engine. Yes, technological advancement has changed our lives completely, and not al

"SAN FRANCISCO - 3-D printing, used to construct everything from art to toys to spare parts for the space station, may one day produce human organs at a hospital near you. click image to enlarge A 3-D printed prosthetic nose and ear are displayed at an industry show in London in November. The technology may eventually help reduce organ shortages. Bloomberg News photo by Chris Ratcliffe Select images available for purchase in the Maine Today Photo Store The 20-year-old technology uses liquid materials that become hard as they print out three-dimensional objects in layers, based on a digital model. Current medical uses are in dentistry, for hard-material crowns, caps and bridges, as well as prosthetics. Last year, a 3-D printer was used to create a structure from moldable polymer that replaced more than 75 percent of a patient's skull. Now, Organovo Holdings Inc. is using 3-D printers to create living tissue that may one day look and act like a human liver, able to cleanse the body of toxins. Drugmakers and cosmetic companies already plan to use 3-D printed human tissue to test new products. Eventually, the technology may help reduce organ shortages and cut transplant rejections as patients receive new organs constructed from their own cells. "3-D printing is like a new tool set," said Organovo Chief Executive Officer Keith Murphy. "You can make a living tissue you can grow outside the body. That's the core of our technology. How can you be smart about doing that?" Organovo already is preparing to sell strips of liver tissue to drugmakers this year to be used to test toxicity of potential treatments, Murphy said in a telephone interview. The San Diego-based company's five- and 10-year goals are first to use a patient's own cells to print tissue strips that can be used to patch failing organs, and finally to be able to create entire new organs. The first 3-D printer was produced in 1992. Since then, a variety of materials have been used as the t

"Rather than being programmed to anticipate every possible answer or action needed to perform a function or set of tasks, cognitive computing systems are trained using artificial intelligence (AI) and machine learning algorithms to sense, predict, infer and, in some ways, think." This source provides a method for the bottom-up approach to AI, which is letting the computer learn like an infant instead of teaching it how to respond to certain cases. Cognitive computing will most likely be mentioned in our project when we talk about the technological singularity. This article is trustworthy because it is written by IBM, one of the world innovators in technology and computing.

"The superior energy density of antimatter annihilation has often been pointed to as the ultimate source of energy for propulsion. Unfortunately, the limited capacity and very low efficiency of present-day antiproton production methods suggest that antimatter may be too costly to consider for near-term propulsion applications." Antimatter is not the same thing as dark matter or the lack of matter altogether. A single teaspoon of antimatter can destroy the metropolitan area of New York City. Antimatter is extremely difficult to harness, and prohibitively expensive as of now. However, in the future, antimatter may be able to be used to power rockets into the depths of outer space. This concept was discussed in Physics of the Future.

In any realistic learning application, the entire instance space will be so large that any learning algorithm can expect to see only a small fraction of it during training. From this small fraction, a hypothesis must be formed that classifies all the unseen instances. If the learning algorithm performs well then most of these unseen instances should be classified correctly. However, if no restric- tions are placed on the hypothesis space and no "preference criterion" 1124] is supplied for comparing competing hypotheses, then all possible classifications of the unseen instances are equally possible and no inductive method can do better on average than random guessing [261. Hence all learning algorithms employ some mechanism whereby the space of hypotheses is restricted or whereby some hypotheses are preferred a priori over others. This is known as inductive bias I hope to use this source to learn more about how artificial intelligence learns, as I have read in other places that the kind that learns from the "bottom up" learns by making mistakes and learning from them. AI, if to be truly intelligent, is probably going to have to learn the way we did; by experience and example. In Kaku's book, he mentions the differences between two artificially intelligent robots that he "met". One, STAIR, had a limited database and was programmed to do what it did. Another, LAGR, piloted itself through a park, bumping into miscellaneous objects and learning their locations so that on the next pass, it would not hit them. I hope to learn more about that kind of logic by reading this article, as I think it is important to have a better understanding of exactly how artificial intelligence learns.

"Engineers build "smart" pills for drug delivery"

This page gives a great comparison between mass customization and restaurants. The author explains how restaurants who have used this kind of method when selling food and how it could extend all over the market. The page was written based off of a college for business and economics.