I'd never heard of tilt-shift videos before today. It's a rather dramatic effect--using a special lens and adjusting the frames-per-second, you can make real-world large object look miniature. Here are several eye-popping examples. I kept thinking that I was looking at miniatures until I saw such realistic people enter the frame.
“Whoever knows he is deep, strives for clarity; whoever would like to appear deep to the crowd, strives for obscurity. For the crowd considers anything deep if only it cannot see to the bottom: the crowd is so timid and afraid of going into the water.”
Friedrich Wilhelm Nietzsche, The Gay Science (1882).
“. . . using financial complexity allegedly to deceive and then using so-called independent experts to validate the deception (lawyers, accountants, credit rating agencies, "portfolio selection agents," etc etc ) . . .”"Now we know the truth. The financial meltdown wasn't a mistake – it was a con"
Why are many human systems complex? If we’ve learned anything over the past few years, it’s that there are two reasons—there are two kinds of complexity. Sometimes, complexity is required to get the job done. I think of this as “parsimonious complexity.” For instance, the Mars Rovers are extremely complex robots, but every part of these magnificent robots has a specific function that furthers a clearly and publicly defined mission. There are also instances where complexity is purposely injected into a system. I think of these as instances of “gratuitous complexity.” It’s important to keep in mind that all forms of complexity serve as entry barriers to activities, due to the limited attentional capabilities of humans. Very few of us have the stamina or intellect to thoroughly understand all of the artificial systems people create; many of us don't have the stamina to thoroughly understand even simple systems. When an activity is more complex, it is more difficult to understand and more daunting to those wishing to participate. Activities that are more complex are thus accessible to fewer people. For instance, chess is more complex than checkers, in that the state space of possible moves is larger in chess than in checkers. Checkers is easy to learn and play. But many checkers players don’t graduate to chess due to the increased complexity. Some systems are so incredibly complex that only the chosen few are able to participate.I recently posted on Sir David Attenborough, touting ability to educate us regarding nature. You might have thought, "Well, anyone could give a lively talk on the blue whale, the largest creature to ever live on Earth." Maybe so. But how many people have ever produced a spellbinding video on fungi? Attenborough and his team are often at their best when presenting species that seem mundane.
Graham Sale's imagination is active at Salon.com, where he explores the long game of proselytizing.
In a recent article in Discover Magazine called "Machine Dreams," (May, 2010, not yet available online) a panel of robotics experts discussed the relationships among people and the machines we call robots. What is a "robot"? Rodney Brooks of MIT offered this definition:
[A] robot is something that senses the world, doesn't some sort of competition, and decides to take an action outside of its physical extremity. That action might be moving around, or it might be grabbing something and moving it. I say "outside it's extremity" because I don't like to let dishwashers be defined as robots.
The panel offered a lively discussion, focusing on many real-world applications. Robots are doing many things these days, including surveillance and reconnaissance during flood disasters. Robots are already quite good at some things, but Rodney Brooks offers some sobering thoughts for those who think of robots as replacements for human beings. We have quite a ways to go. Where are we headed? Here are the goals for which robotics researchers are currently striving to reach (according to Brooks):First the object recognition capabilities of a two-year-old child. You can show a two-year-old a chair that he's never seen before, and he'll be able to say, "that's a chair." Our computer vision systems are not that good. But if our robots did have that capability, would be able to do a lot more.
Second, the language capabilities of a four-year-old child. When you talk to a four-year-old, you hardly have to dumb down your grammar at all. That is much better than our current speech systems can do.
Third, the manual dexterity of a six-year-old child. A six-year-old can tie his shoelaces. A six-year-old can do every operation that a Chinese worker does in the factory. That level of dexterity, which would require a combination of new sorts of sensors, new sorts of actuators, and new algorithms, will let our robots do a lot more in the world.
Fourth, the social understanding of an eight or nine-year-old child. Eight or nine-year-olds understand the difference between their knowledge of the world and the knowledge of someone they are interacting with. When showing a robot how to do a task, they know to look at where the eyes of the robot were looking. They also know how to take social cues from the robot.