Hi guys, I’ve had this idea recently and I definitely need your help. If you start with a line and at both ends add lines such that they are perpendicular to the first one (like on the second picture) and then repeat this process infintely, you get a geometrical figure that seems rather random (not sure if it can be considered as a fractal though). 

The first 3 images show the 3 first steps ; the fourth one is the result after 8 iterations, and the fifth one after 16 iterations.

Problem is that it takes hours to draw it, and I have little knowledge in programming… Could any of you do that for me, or do you know somebody that would ? I would be infinitely thankful if yes. Have a nice day !


What Happened To Women In Computer Science? 

For decades, the number of women in computer science grew faster than the number of men —until you get to 1984. At that point, the percentage of women began to plunge (even as the share of women in fields like mechanical engineering, math and physics kept rising).

So what happened? What was going on in 1984?

NPR’s Planet Money tried to untangle this question and the answer is complex.

One of the big changes to happen around 1984 was the introduction of small personal computers into the home. Early computers weren’t much more than toys (think pong and space invaders) and they were marketed almost exclusively to boys. 

In the 1990s, UCLA researcher Jane Margolis interviewed hundreds of computer science students at Carnegie Mellon University, which had one of the best programs in the country. She found that families were much more likely to buy computers for boys than for girls — even when the girls were the ones who were interested in computers. 

The pattern was pretty consistent. One student told a story of having to ask her brother for the key to use the computer because it was actually locked away from her in his room. This may be an extreme example, but Margolis never heard the reverse — no stories of boys having to go into their sister’s room to use the computer.

This was a big deal when those kids went to college. As personal computers became more common, computer science professors increasingly assumed that their students had grown up playing with computers.

By the mid 90s, the Carnegie Mellon computer science program was 93% men. Half the women who went to school for computer science ended up quitting the program. As Margolis explains:

“Because if you’re in a culture that is so infused with this belief that men are just better at this and they fit in better — a lot can shake your confidence. You can be sitting next to a male student who could say, ‘You don’t know that? …And you’re a computer science major?’” 

And these types of slights add up.

In her research, Margolis discovered that a lot of the women who were dropping out were great at computer science — more than half were on the dean’s list.

So how do we get women back in to computer science?

Margolis did her research with Allan Fisher, the Dean of the Computer Science program at Carnegie Mellon. The two ended up using what they had learned to make adjustments to the program.

They paid a lot more attention to teaching and added an intro course for students who didn’t have a lot of informal computer science experience.

And it worked. In 5 years, they turned the school around: 42% of computer science students were women (and the drop out rate was the same for men and women).

Top Image: Planet Money

Bottom Image: Two women operating the ENIAC’s main control panel


D-Wave Lab Tour - The Infrastructure of the D-Wave Quantum Computer

Interesting & well shot short documentary about D-Wave’s main experimental facility and their high-tech quantum computer fridge systems and quantum computing infrastructures.

Side note: Geordie Rose, CTO of D-Wave, reveals in his blog that they have built a quantum computer version of Spacewar!:

They look a lot like computers did back in the 60s. There are a lot of parallels to back then — we even built our own version of Spacewar! — except you get to play against a quantum computer. (Aside: this game — which was the world’s first quantum computer game — was called MaxCat. I own the only handwritten copy of the rules…. one of my most treasured artifacts!)

Part two is about the fridge at the cooling system, and the electronics that are used to talk to the quantum chip:

And part three looking at the quantum annealing processor:

[more] [via Geordie Rose]

Date: May 5, 2015 

Source: American Institute of Physics (AIP) 

Summary: Quantum computers are in theory capable of simulating the interactions of molecules at a level of detail far beyond the capabilities of even the largest supercomputers today. Such simulations could revolutionize chemistry, biology and material science, but the development of quantum computers has been limited by the ability to increase the number of quantum bits, or qubits, that encode, store and access large amounts of data.

A GPS That Asks DNA for Directions

A team of engineers in Singapore has been working for years on a computer that uses DNA instead of silicon to process calculations. They recently reported success in advancing the technology, by unveiling a programmable DNA-based optimal route planning processor that behaves like those in traditional GPS navigation systems. 

The system can tackle two different computing tasks at the same time, calculating the shortest route between two different starting points and two destinations on a map consisting of six paths. It does this by using information stored beforehand in the DNA.

Keep reading

Every dystopian society has excessive surveillance, but now we see even western democracies like the US and England moving that way. We have to roll this back. People who are not suspected of committing crimes should not have information collected and stored in a database. We don’t want to become like North Korea.

New Wolfram AI project takes on image recognition

The newly launched Wolfram Language Image Identification Project lets users upload a picture to use the new ‘ImageIdentify’ function. Try it out here.

From the Wolfram blog:

It won’t always get it right, but most of the time I think it does remarkably well. And to me what’s particularly fascinating is that when it does get something wrong, the mistakes it makes mostly seem remarkably human.

It’s a nice practical example of artificial intelligence. But to me what’s more important is that we’ve reached the point where we can integrate this kind of “AI operation” right into the Wolfram Language—to use as a new, powerful building block for knowledge-based programming.

If one had lots of photographs, one could immediately write a Wolfram Language program that, for example, gave statistics on the different kinds of animals, or planes, or devices, or whatever, that appear in the photographs.

It would be inappropriate to say, ‘Digital did this, computers did that, iPhones did this and iPads did that.’ It’s not that ‘cause and effect.’ We are living in a digital media environment now, and the environment that we’re living in is as different from the industrial age as the industrial age was from hand craftsmanship in the late Middle Ages. It’s like having been given electricity. When the whole world is maintained or administrated by computers, and when we’re all walking around with computers to take care of our smallest tasks, we end up being shaped and flavored by the underlying biases of the technology, itself. If you choose your restaurant using Yelp rather than using your own understanding of the neighborhood, or the friends that you spoke to or the smells on the street as you’re walking down the block, you’re living in a different world and you’re going to make choices that are determined very differently for you.