Wolfram Computation Meets Knowledge

Date Archive: 2010 September


Let’s Do It Again

Iteration usually increases complexity. For example, ponder the following "Fractal Maze”. The green lines mark the boundaries of a frame that shows the black paths of a maze. Copies of that frame and the paths are copied inside. With 4 levels of nested frames, it is possible to get from 1 to 8 on the outer frame. When pictures are repeated inside themselves, it's usually called the Droste effect.
Best of Blog

Do Computers Dumb Down Math Education?

Since I just heard that the video for Conrad Wolfram's recent TED talk "Stop teaching calculating, start teaching math" will be coming out soon, I thought I would address the single biggest fear that I hear when I talk about using computers in math education. The objection that using computers will "dumb down" education comes with the related ideas "students have to learn to do it by hand or how will they know they have got the right answer", "they won't understand what is happening unless they do it themselves", and so on. Well, let's examine this by looking at a typical math question that I know I had to solve at some point in my education.
Announcements & Events

Stephen Wolfram Discusses Making the World’s Data Computable

Wolfram Research and Wolfram|Alpha hosted the first Wolfram Data Summit in Washington, DC this September. Leaders of the world's primary data repositories attended the summit, exchanging experiences and brainstorming ideas for the future of data collection, management, and dispersion. In his keynote speech, Stephen Wolfram discussed the complex nature of gathering systematic knowledge and data together. He also talked about the creation of Wolfram|Alpha, how Mathematica helps with the challenges of making all data computable, and what we can expect moving forward. The transcript is available below.
Announcements & Events

A New Kind of Science is on the iPad!

I spent a decade of my life writing A New Kind of Science. Most of that time was devoted to discovering the science in the book. But another part was spent figuring out how to present the science in the best possible way—using words and pictures. It took a lot of technology to do that […]

Computation & Analysis

Tapping Into the Power of GPU in Mathematica

Last week we posted an item about Wolfram Research's partnership with NVIDIA to integrate GPU programming into Mathematica. With NVIDIA's GPU Technology Conference 2010 starting today, we thought we would share a little more for those who won't be at the show to see us (booth #31, for those who are attending). Mathematica's GPU programming integration is not just about performance. Yes, of course, with GPU power you get some of your answers several times faster than before---but that is only half the story. The heart of the integration is the full automation of the GPU function developing process. With proper hardware, you can write, compile, test, and run your code in a single transparent step. There is no need to worry about details, such as memory allocation or library binding. Mathematica handles it elegantly and gracefully for you. As a developer, you will be able to focus on developing and optimizing your algorithms, and nothing else. Here are a couple of examples to give you a taste of the upcoming feature.
Computation & Analysis

Mathematica and NVIDIA in Action: See Your GPU in a Whole Different Light

Wolfram Research is partnering with NVIDIA to integrate GPU programming into Mathematica. CUDA is NVIDIA's performance computing architecture that harnesses modern GPU's potential. The new partnership means that if you have GPU-equipped hardware, you can transform Mathematica's computing, modeling, simulation, or visualization performance, boosting speed by factors easily exceeding 100. Now that's fast! Afraid of the programming involved? Don't be. Mathematica's new CUDA programming capabilities dramatically reduce the complexity of coding required to take advantage of GPU's parallel power. So you can focus on innovating your algorithms rather than spending time on repetitive tasks, such as GUI design.
Education & Academic

Finding Interesting Dynamics in the Asteroid Belt with Mathematica’s AstronomicalData

Almost everyone has heard of the asteroid belt. This is the place between the orbit of Mars and Jupiter that is home to a very large percentage of the known minor planets in the solar system. Movies love to have space battles in asteroid belts to add to dramatic dogfight scenes. Even the Star Wars universe pays homage to asteroids: in The Empire Strikes Back, C3PO makes a popular statement about the possibility of successfully navigating an asteroid field. Popular fiction, especially in Hollywood, loves to twist reality for cinematic effect. Often it shows an asteroid belt as an intricate maze of chaotically tumbling boulders that are moving at high speeds relative to each other, requiring advanced evasion techniques to avoid hitting one of them. They are also often shown to collide with each other at high speed, resulting in large explosions. In reality, at least for our asteroid belt, things are not quite so dramatic. If you were actually in our asteroid belt, the chances that you would see an asteroid are fairly small. Most of them are quite small relative to the Earth and the space between them is relatively large. NASA has sent numerous probes through the belt, and not one has had an accidental encounter with an asteroid, although there have been a couple of intentional encounters. We know very little about the physical characteristics of asteroids compared to planets. Very few have been visited. However, their orbital dynamics are well studied and show some pretty amazing features. Let's take a look at a view of all of the asteroids used in Mathematica's AstronomicalData out to the orbit of Jupiter.
Design & Visualization

Twisted Pictures

I have a lot to study at the moment, as I learn how to use the technology that's in our development pipeline. One of the first features I played with was so much fun I thought I would share it with you. You will be able to efficiently and easily texture map over any 3D image. Texture mapping has all kinds of practical uses for improving visualization, but the first thing that I thought of was setting fire to a plot...