Optimists called the first world war “the war to end all wars”. Philosopher George Santayana demurred. In its aftermath he declared: “Only the dead have seen the end of war”. History has proved him right, of course. What’s more, today virtually nobody believes that humankind will ever transcend the violence and bloodshed of warfare. I know this because for years I have conducted numerous surveys asking people if they think war is inevitable. Whether male or female, liberal or conservative, old or young, most people believe it is. For example, when I asked students at my university “Will humans ever stop fighting wars?” more than 90 per cent answered “No”. Many justified their assertion by adding that war is “part of human nature” or “in our genes”. But is it really?
Continuing on the topic from the last post… Surgeon and inventor Catherine Mohr tours the history of surgery (and its pre-painkiller, pre-antiseptic past), then demos some of the newest tools for surgery through tiny incisions, performed using nimble robot hands. Fascinating — but not for the squeamish.
I’m a da Vinci surgeon because it is obvious to me that this is an improvement, a paradigm shift if you will, a leap forward in our ability to take care of our patients… and it really comes down to the bottom line. If I was going to have someone in my own family operated on would I want that surgeon to be trained in robotics? Yeah, I would.
Singularity University, based on the NASA Ames campus in Silicon Valley, is an interdisciplinary university whose mission is to assemble, educate and inspire a cadre of leaders who strive to understand and facilitate the development of exponentially advancing technologies (bio, nano, info, AI, etc.), and apply, focus and guide these tools to address humanity’s grand challenges.
Research group switches on world’s first “artificial intelligence” tasked-array system. For several years now a small research group has been working on some challenging problems in the areas of neural networking, natural language and autonomous problem-solving. Last fall this group achieved a significant breakthrough: a powerful new technique for solving reinforcement learning problems, resulting in the first functional global-scale neuro-evolutionary learning cluster.
The world is changing in an exponential rate. The world 20 years ago was vastly different from today. In 1987 could anyone have predicted the communication structures that we now take for granted? What will the world be like in 20 more years? It will be even more different than the last 20. (2008 update)
In the early 1980s, around the time Ronald Reagan became President and Wall Street’s great modern bull market began, we started gambling (and winning!) and thinking magically. From 1980 to 2007, the median price of a new American home quadrupled. The Dow Jones industrial average climbed from 803 in the summer of 1982 to 14,165 in the fall of 2007. From the beginning of the ’80s through 2007, the share of disposable income that each household spent servicing its mortgage and consumer debt increased 35%. Back in 1982, the average household saved 11% of its disposable income. By 2007 that number was less than 1%.
The most energetic laser system in the world, designed to produce nuclear fusion–the same reaction that powers the sun–is up and running. Within two to three years, scientists expect to be creating fusion reactions that release more energy than it takes to produce them. If they’re successful, it will be the first time this has been done in a controlled way–in a lab rather than a nuclear bomb, that is–and could eventually lead to fusion power plants.
Robotic systems continue to evolve, slowly penetrating many areas of our lives, from manufacturing, medicine and remote exploration to entertainment, security and personal assistance. Developers in Japan are currently building robots to assist the elderly, while NASA develops the next generation of space explorers, and artists are exploring new avenues of entertainment. Collected here are a handful of images of our recent robotic past, and perhaps a glimpse into the near future. (32 photos total)
The United States is scheduled to launch on Friday an orbiting telescope designed to help answer one of the oldest and deepest questions of astronomy: Are we – or at least our planet’s microbes – alone in the galaxy? The Kepler spacecraft will stare at a patch of sky – the same 100,000 stars near the northern constellation Cygnus, all at once – for at least 3-1/2 years. The goal is to detect Earth-like planets orbiting their host stars at distances thought to be sweet spots for life. Dubbed habitable zones, these are orbits where a planet is bathed in light that is strong enough to permit liquid water to collect and remain a persistent feature of the planet’s surface. If all goes well, Kepler’s journey will start with the launch from Cape Canaveral in Florida at around 10:49 p.m. Eastern time.
What Will Replace The Internet? First it will become wireless and ubiquitous, crawling into the woodwork and perhaps even under our skin. Eventually, it will disappear. The Internet seems to have just arrived, so how can we possibly imagine what will replace it? In truth, early versions of the Net have been around since the 1960s and ’70s, but only after the mid-1990s did it begin to have a serious public impact. Since 1994, the population of users has grown from about 13 million to more than 300 million around the world. About half are in North America, and most–despite significant progress in rolling out high-speed access–still reach the Internet by way of the public telephone network. What will the Internet be like 20 years from now?
These are indeed nice days for artificial intelligence researchers. While Stair’s performance might not seem much better than that of a dog fetching the newspaper, it’s a technological tour de force unimaginable just a few years ago. “Stair, please fetch the stapler from the lab,” says the man seated at a conference room table. The Stanford Artificial Intelligence Robot, standing nearby, replies in a nasal monotone, “I will get the stapler for you.” Stair pivots and wheels into the adjacent lab, avoiding a number of obstacles on the way. Its stereoscopic camera eyes swivel back and forth, taking in the contents of the room. It seems to think for a moment, then approaches a table for a closer look at an oblong metallic object. Its articulated arm reaches out, swivels here and there, and then gently picks up the stapler with long, rubber-clad fingers. It heads back to the conference room. “Here is your stapler,” says Stair, handing it to the man. “Have a nice day.” Indeed, Stair represents a new wave of AI, one that integrates learning, vision, navigation, manipulation, planning, reasoning, speech and natural-language processing. It also marks a transition of AI from narrow, carefully defined domains to real-world situations in which systems learn to deal with complex data and adapt to uncertainty. AI has more or less followed the “hype cycle” popularized by Gartner Inc.: Technologies perk along in the shadows for a few years, then burst on the scene in a blaze of hype. Then they fall into disrepute when they fail to deliver on extravagant promises, until they eventually rise to a level of solid accomplishment and acceptance.
Posted by eneve 
Posted by eneve 
Posted by eneve 
