so_many_a_second is a simple online applet that helps you visualize statistics. Most notably, it takes statistics in the form “x items used worldwide per second” and illustrates those items falling down a screen. So for example, 150 trees are cut per second according to Worldometers, and so_many_a_second visualizes that process thusly:

You can also do a split screen view comparing, say, trees cut per second versus babies born per second (4.2). That looks like this:

You can even create your own views by plugging in a name, number of items per second, and an icon. It’s an interesting way to visualize statistics — putting an image to something that is very abstract for most of us. Go and click around!

See also: Visualizing Consumerism and Worldometers.

In 1970, mathematician John Horton Conway invented a game called Life. Conway was intrigued by John von Neumann’s theories about self-replicating automata: simple mathematical formulae representing virtual “life forms” that could be depicted in a virtual world. Of course, in von Neumann’s day the “virtual world” was a piece of graph paper with some squares filled in (squares being the life forms), but still, it was a pretty cool idea. Conway took von Neumann’s ideas a step further, creating a computer simulation of the graph paper-based automata, and forcing the automata to follow simple rules:

The universe of the Game of Life is an infinite two-dimensional orthogonal grid of square cells, each of which is in one of two possible states, live or dead. Every cell interacts with its eight neighbours, which are the cells that are directly horizontally, vertically, or diagonally adjacent. At each step in time, the following transitions occur:

1. Any live cell with fewer than two live neighbours dies, as if by needs caused by underpopulation.
2. Any live cell with more than three live neighbours dies, as if by overcrowding.
3. Any live cell with two or three live neighbours lives, unchanged, to the next generation.
4. Any tile with exactly three live neighbours cells will be populated with a living cell.

The initial pattern constitutes the ’seed’ of the system. The first generation is created by applying the above rules simultaneously to every cell in the seed — births and deaths happen simultaneously, and the discrete moment at which this happens is sometimes called a tick. (In other words, each generation is a pure function of the one before.) The rules continue to be applied repeatedly to create further generations.

Conway’s Game of Life often starts with a very simple playing field: mostly blank, with a few little bits filled in. What’s fascinating is how complexity arises from the simple rules above, as they operate on the seed (the initial condition of the game). Some crazy things happen, including “guns” (pictured above), in which base cells seem to shoot virtual pellets. (When Bill Gosper at MIT discovered/invented guns, he won a $50 prize from Conway.)

Since 1970, Conway’s Game of Life has been implemented on virtually every computer platform, either as a time waster or a nice way to get started with simple graphics programming. You can even get Life on the iPhone. To get a feel for Life, try playing The irRegular Game of Life, a nice Flash game in which you solve puzzles by creating automata (you do have to sit through an ad first, though). For a more traditional version of Life, check out this Java version (warning: kinda slow). To learn more about Conway’s famous game, read up at Wikipedia.

Design magazine Core77 sent the intrepid Glen Jackson Taylor inside NASA, to learn how the organization handles industrial design — the process of designing the usable and beautiful devices. But when Taylor arrived, he found a surprise: “There isn’t really a place for industrial designers at NASA,” he wrote. “Here the engineers are considered the designers, and the team has only been able to exist under the guise of human factors, a quantifiable soft science that is acknowledged as necessary.” So how does NASA design such iconic rovers, landers, the Space Shuttle, rockets, and so on? They aren’t just functional — there’s tons of design there as well. Taylor explains:

The influence NASA’s endeavors have had on Hollywood and sci-fi runs deep, but it is well reciprocated. “So many people here are inspired by Star Wars, you’ll go to a meeting and someone will say, ‘let’s make it like that like thing in Return of the Jedi.’ There really is a direct connect between science fiction and what we do here,” says Evan. …
We jump in Travis’s car and head over to Hangar X, which sounds dead cool. Hangar X is the former location of the X-38 Crew Return Vehicle project, an escape pod for the crew working on the International Space Station (ISS) to return to Earth in case of an emergency. Literally hundreds of people worked on the X-38, millions of dollars were invested developing prototypes that were realized to the point of a drop-test vehicle, before being canceled in 2002 due to budget cuts. It now sits on a trailer under tarps in the Hangar X car park as a monument to the cycles of power and priority, how Congress is voting, and the political relations with our allies and enemies. …

Read the rest for an awesome look inside NASA, including tons of great photos, video, and my favorite part: the design of a new pressurized rover that may eventually land on the moon.

Following up on yesterday’s Mars Phoenix Lander post, let’s continue with the NASA theme. This past May, Jet Propulsion Lab Director Charles Elachi gave a speech about JPL, full of historic and contemporary photos — including a surprising amount of goofing around.

Elachi shows us the fun side of JPL, the serious side of JPL, and a bunch of cool stuff about the Mars Rovers (including some of the best Mars photos I’ve seen). The satellite imagery of Mars is beautiful and engaging. On the downside, Elachi has a penchant for playing hip videos during his presentation, so he does seem to be trying a little too hard to reach the kids. Regardless, the presentation includes a good (if overly edgy) video looking at the beginning of the Mars Phoenix Lander mission, and Elachi gives us some insight into the culture of JPL. Check it out, science fans!

Yesterday, NASA announced that the Mars Phoenix Lander has died. Okay, they said that the lander had “ceased communications” and that the lander had “finish[ed] successful work,” both of which are merely euphemisms for its tragic death after five months of lonely toil on Mars.

The Mars Phoenix Lander’s death is not unexpected. It landed in a polar region of Mars, because that’s where the ice is. But it’s also where it gets real darn cold during the Martian winter, and at this point, Phoenix (and its batteries) are freezing solid — there’s no hope that this robot will magically survive for five years like the Mars Rovers which are near the Martian equator, where the temperature ranges from -130 degrees F in the winter to a toasty 95 degrees F in the summer. For the record, Phoenix did indeed find ice, fulfilling its mission.

Phoenix was highly anthropomorphized during its mission, with its team continually posting tweets (Twitter messages) in the voice of the lander. Its final message came yesterday in an uncharacteristic binary code: “01010100 01110010 01101001 01110101 01101101 01110000 01101000 <3″ Translated from binary, this reads “Triumph” with a “heart” emoticon at the end. On October 31, things were looking grim for Phoenix. It posted the message, “The team has me on extreme ‘bed rest’ to recharge power supply. There’s cautious optimism about pulling out of this in a few days.” Four days later: “I’m resting a lot but still communicating with orbiters once per day. Still hoping to get a bit of strength back & maybe do more science.” Just before its death, Phoenix held a contest to have humans write its epitaph. Nearly 1,000 epitaphs were submitted. The winners, by popular vote:

1. Veni, vidi, fodi. (I came, I saw, I dug)
Graham Vosloo

2. So long and thanks for all the ice.
D. Adams

3. It is enough for me. But for you, I plead: go farther, still.
Fernando Rojas

As Dylan Thomas wrote, “Do not go gentle into that good night, Old age should burn and rave at close of day; Rage, rage against the dying of the light.” Rest in peace, brave lander.

Garrett Lisi is a physicist…and a surfer who lives in a van down by the beach. In his TED Talk from February, he described a way of understanding the world (as a large thing) by looking at the tiniest things we can find. How does the world work at tiny scales? How does the Large Hadron Collider help us figure this out? How is a coral a pretty good metaphor for the patterns of subatomic particles? Lisi explains all of this in surprisingly followable language. (I did find myself rewinding and replaying the video when Lisi talks about the Higgs particle, and I have no idea what his dimensional rotations really are, but I do think I get the gist of what he’s saying.)

Discussed: quantum weirdness, Schrödinger’s cat, “everything that can happen, does,” what can happen, what can’t happen, how particle colliders work, subatomic particles and their patterns, the Higgs particle, viewing subatomic particles in multiple dimensions (pretty pictures!), using eight-dimensional mandalas of subatomic particles to find what’s missing, the “dark labyrinth,” the Large Hadron Collider, and living in a van on Maui.

For more on the Large Hadron Collider, check out Brian Cox’s talk from March.

Was there a real Dr. Frankenstein? Frankenstein, or The Modern Prometheus is considered by many to be the first science fiction novel. It was written in 1816-1817, during a time when bringing the dead back to life was a serious endeavor in scientific circles. Mary Wollstonecraft Godwin (later Shelley) wrote the book as an exploration of the ethics of such experimentation and brought the question to a wider audience. The model for the character of Dr. Frankenstein could have been any, or several, of a number of actual people.
*
Mary Shelley was a highly yet unconventionally educated teenager in the summer of 1816. She and her future husband Percy Shelley were staying with Lord Byron at his home on Lake Geneva when the idea of the novel came to her. She was undoubtedly influenced by intellectual discussions with Shelley, Byron, and a host of their friends. A look back at the time reveals how the novel reflected real events Mary Shelley knew about and incorporated into the story.

Erasmus Darwin

Erasmus Darwin (grandfather of Charles Darwin) was a friend of Mary Shelley’s father, William Godwin. Shelley mentioned Dr. Darwin in the preface to her novel. Darwin studied galvanism, the contraction of muscles when stimulated with electricity. Shelley refers to Darwin “. . . who preserved a piece of vermicelli in a glass case, till by some extraordinary means, it began to move with voluntary motion.” It really wasn’t the pasta, it was vorticelli, a tiny animal.

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Darwin@Home is a computer program created by Gerald de Jong to model evolution. While it aspires to be a general-purpose evolution platform, at the moment it does something pretty remarkable: it takes virtual creatures designed by humans and evolves them until they can walk.

Because Darwin@Home’s creatures are non-biological, they can have all kinds of strange body plans — they aren’t limited to the bodies we’re familiar with in Earth-based biology. In the video below, de Jong shows a series of bizarre virtual creatures (created by community members on their home computers) that have evolved walking strategies in the Darwin@Home software. Some are more elegant than others, but they’re all effective. It’s a weird-looking bunch, strangely reminiscent of deep-sea creatures. Have a look:

For more on Darwin@Home, check out this page of videos, the community site, or the project homepage. You can also download the software (it’s written in Java, so it runs on many platforms) and get started designing your own creatures!

(Via Kottke.org.)

Rodney Brooks is one of my favorite scientists: he’s brilliant, accomplished (his research led to the Roomba vacuum cleaner robot), and full of predictions. Brooks is a master of robotics, having designed a wide variety of robots over the years, and he also made a memorable appearance in one of my favorite documentaries (the title Fast, Cheap and Out of Control came from a research paper of his). So it’s fair to say that I’m a fan.

Brooks gave a TED Talk on robotics in 2003, and it’s just been posted to the web. In it, he demos the (then-new) home cleaning robot Roomba, the military utility robot PackBot (which can climb stairs and survives being thrown down hills and through windows), and the anthropomorphic Kismet. Beyond these demos, he demonstrates how robots and humans can communicate, which he believes will form the future of robotic interaction.

Watch the video to learn a bit about state of the art robotics (well…five years ago), and what might be coming next.

For more on Brooks, check him out on Wikipedia.

Can we stop epidemics by stopping people from shaking each others’ hands? Can we solve global overconsumption by making people smaller, or just getting rid of mostly everybody? If a “one child per family” policy means children’s families are small, why not add dozens more parents to each family? Artificial intelligence maven Marvin Minsky tackles these “solutions” in a tongue-in-cheek TED Talk from 2003.

Minsky makes an interesting point (in a roundabout way) about the nature of emotion and its role in human problem-solving: we wouldn’t implement any of the above-mentioned solutions to human problems, because emotionally they wouldn’t work. So what good are emotions, and how are they relevant to machine intelligence? I’ll let Minsky explain.

For more on Marvin Minsky, check out his article on mathematics education and his Wikipedia page. Or just become enlightened by this “artificial intelligence koan” credited to Minsky’s student Danny Hillis:

In the days when Sussman was a novice, Minsky once came to him as he sat hacking at the PDP-6.
“What are you doing?” asked Minsky.
“I am training a randomly wired neural net to play Tic-tac-toe,” Sussman replied.
“Why is the net wired randomly?” asked Minsky.
“I do not want it to have any preconceptions of how to play,” Sussman said.
Minsky then shut his eyes.
“Why do you close your eyes?” Sussman asked his teacher.
“So that the room will be empty.”
At that moment, Sussman was enlightened.

What I actually said was, “If you wire it randomly, it will still have preconceptions of how to play. But you just won’t know what those preconceptions are.” — Marvin Minsky