## DIKU APL Group IRC channel

Come join the DIKU APL channel on IRC:

## A new side to Bill Gates

I don’t know why, but I really liked to read this post by Bill Gates. In an odd way it was heart warming 🙂

Three Things I’ve Learned From Warren Buffett

Maybe I should start reading Bill Gates blog as well, just for more of that feel good vibe I got from reading the blog post. I not being sarcastic.

Everything is relative, especially the news value of things, so this is of course only news to me. Having been too busy with life to sit down and quietly read a post that is non-technical.

## NSA back door

This is geek humor at it’s best, and is one of the funniest reactions to PRISM I have seen.

Here is a screenshot from the github project flask-nsa

<3

## Surviving a startup with small children in the house

The question: Is it possible to be an entrepreneur while having small children and a wife? Here is what a bunch of entrepreneurs say about that:

Entrepreneur      Verdict

Jason Roberts
He says yes. Has three kids aged 6, 4 and 2 and several startups behind him or in the works, including AppIgnite.

Jason Calacanis
Los Angeles
He says yes, but not if it is your first startup. Has one kid, perhaps aged 2. Is a well-known entrepreneur with several startups behind him.

Gini Dietrich
She says no, has no children. Has at least two startups behind her.

Jessica Stillman
She says yes, if you are willing to give up a certain bond with your kids (between the lines, is it worth it?). The post is actually more a resume of what other people have said, so open it and follow the links.

## Evolving database algorithms through human experiments

Here is something fun to do on a sunny day. The idea is the following: A group of people collectively designing an algorithm by playing a game.

## Danish social experiment from 1969

In the Danish movie Broen (Om Fordomme) two groups who can not stand each other have to collaborate in order to build a bridge. The movie is visible online.

## Thank you Scott!

I just read this blog post by Scott Hanselman (I’m a phony. Are you?), and it was a bit of a group therapy moment. It’s nice to know that you’re not alone in something!

Adapted from an article I found by Googlin’. There are many ways to define this, but simply put:

• Task parallelism is the simultaneous execution on multiple cores of many different functions across the same or different datasets.
• Data parallelism (aka SIMD) is the simultaneous execution on multiple cores of the same function across the elements of a dataset.

## Background

When I’m at the library, I’d like to be able to go to the toilet, without collecting all my stuff from the table. Part of the solution is to have a camera installed that films all the tables, but assuming we can hire someone to look at the camera-feeds, that person might not notice that my laptop was stolen. Of course they could be notified, and the culprit identified from the tapes, but what if the culprit is “disguised? The only solution is to capture the thief before he/she leaves the building. For that to work, the security personel must be notified of the theft exactly when it happens!

## Formal problem definition

Problem:

• Person A, me, leaves an artifact (computer) at a table in a public space and goes somewhere (restroom).
• Person B drops by table and steals computer
• By the time A is back, B has left the building
• Because B was wearing sunglasses and a blue beard, B can not be identified from the surveillance tape

Solution requirement: Person B should be apprehended before he/she leaves the building, namely before person A is back and notices the theft. This means that an algorithm must detect the theft as it happens!

Solution approach:

• Camera feed is routed to bank of algorithms
• Algorithm X detects people and their location, and assigns unique IDs to different people
• Algorithm Y detects artifacts, and associates each artifact with the ID of its owner
• Algorithm Z detects the situations: 1) An owner has lefts his/her artifact 2) A person which is not the owner is very near an artifact. If both 1 and 2 hold for a given artifact, an event is fired

The events from algorithm Z are handed to the security staff, who can investigate visually whether a theft is taking place.

## How does the number of leafs on a tree grow with the height of the tree?

As a was lying on my back in the University park to day, resting a bit between reading papers (more on that later), I looked up at a pine tree and asked myself a very computer sciencey question. How does the number of needles L on the tree grow, as the tree grows taller? If the height of the tree is h, what is the size of L?

## Exponential?

I initially thought that surely this must be exponential, after all just think of a binary tree: The number of leaf nodes in a balanced binary tree of height h is $2^h$. So maybe:

$L \approx 2^h$