offers an interesting format for interviews where you see the interviewer and interviewee side-by-side, which they call a diavlog (a term I can’t quite imagine using in conversation). The interviews appear to be recorded with webcams and a phone call.

They offer some neat playback features: the ability to link into a video (but I don’t see that I can make my own link) and the ability to playback the auido/video at a faster speed, which is surprisingly usable (although I wish I had a scrubber interface for the speed of the video, rather than simply the “1.4” button which appears to switch playback to an alternate video file).

I enjoyed listening to bits of a few interviews. The one below was fun, although it starts slow, you can start in the middle what’s the point of sex? which discusses some scientific perspectives on the topic. The parts about free will and the placebo effect were pretty interesting too.

Jon Udell writes about where the US gets its oil (the majority comes from Canada, not the middle east). He follows the data with the story of how he discovered the answer and presented the data using DabbleDB.

I agree with Jon when he says “we’re really close to the point where non-specialists will be able to find data online, ask questions of it, produce answers that bear on public policy issues, and share those answers online for review and discussion.” It’ll likely need another generation of tools before we work out the glitches and hiccups in the data flow and it’ll require the generation who grew up with the web to expect such tools at their fingertips and put them to use. I look forward to seeing what comes next.

David Martin, an assistant professor at Boston College, has published a fabulous sorting visualization (via HMK).

These should be a must-see for every computer science student. He includes some good notes about what we should be looking for and why we might care (excerpted below). Often people publish marvelous visualizations, but people who are new to the subject matter can miss key aspects of what they might learn from the detailed visual cues. It is great to see the combination here.

These visualizations are intended to:

* Show how each algorithm operates.
* Show that there is no best sorting algorithm.
* Show the advantages and disadvantages of each algorithm.
* Show that worse-case asymptotic behavior is not the deciding factor in choosing an algorithm.
* Show that the initial condition (input order and key distribution) affects performance as much as the algorithm choice.

The ideal sorting algorithm would have the following properties:

* Stable: Equal keys aren’t reordered.
* Operates in place, requiring O(1) extra space.
* Worst-case O(n·lg(n)) key comparisons.
* Worst-case O(n) swaps.
* Adaptive: Speeds up to O(n) when data is nearly sorted or when there are few unique keys.

There is no algorithm that has all of these properties, and so the choice of sorting algorithm depends on the application.