Public talk about open science in San Francisco

I’m pleased to say that I’ll be giving a public talk about open science in San Francisco, next Wednesday, June 29, at 6pm. The talk is being hosted by the Public Library of Science, and there will be wine, beer and cheese after the event.

The talk is entitled “Why the net doesn’t work for science – and how to fix it” [*]. Here’s my abstract for the talk:

The net is transforming many aspects of our society, from finance to friendship. And yet scientists, who helped create the net, are extremely conservative in how they use it. Although the net has great potential to transform science, most scientists remain stuck in a centuries-old system for the construction of knowledge. I will describe some leading-edge projects that show how online tools can radically change and improve science (using projects in Mathematics and Citizen Science as examples), and will then go on to discuss why these tools haven’t spread to all corners of science, and how we can change that.

The talk will be thematically similar to my recent talk about open science for TEDxWaterloo, but will go much deeper into the challenge and promise of open science.

For more details on the talk, including the address and a map, please see the PLoS blog. Please RSVP to if you plan to attend.

Hope to see you there!

[*] The title is a riff on the wonderful phrase “making the web work for science”, which I believe originated with James Boyle. For a recent talk on the subject by Boyle, see here (see also Creative Commons’ work on science).

Data-driven intelligence

I’ve started a new blog, on data-driven intelligence. In future, this is where technical posts like my Google Technology Stack posts will go. There are two posts up:

  • A post describing Pregel, Google’s system for implementing graph-based algorithms on large clusters of machines. In addition to describing how Pregel works, I give a toy single-machine Python implementation which can be used to play with Pregel. The code is up on GitHub.
  • Sex, Einstein, and Lady Gaga: what’s discussed on the most popular blogs. I crawled 50,000 pages from Technorati’s list of the top 1,000 blogs, and determined the percentage of pages containing words such as “sex”, “Einstein”, “Gaga”, and many others. The results were entertaining.

The blog, of course, has an RSS feed.

Quantum computing for the determined

I’ve posted to YouTube a series of 22 short videos giving an introduction to quantum computing. Here’s the first video:

Below I list the remaining 21 videos, which cover subjects including the basic model of quantum computing, entanglement, superdense coding, and quantum teleportation.

To work through the videos you need to be comfortable with basic linear algebra, and with assimilating new mathematical terminology. If you’re not, working through the videos will be arduous at best! Apart from that background, the main prerequisite is determination, and the willingness to work more than once over material you don’t fully understand.

In particular, you don’t need a background in quantum mechanics to follow the videos.

The videos are short, from 5-15 minutes, and each video focuses on explaining one main concept from quantum mechanics or quantum computing. In taking this approach I was inspired by the excellent Khan Academy.

The course is not complete — I originally planned about 8 more videos. The extra videos would complete my summary of basic quantum mechanics (+2 videos), and cover reversible computing (+2 videos), and Grover’s quantum search algorithm (+4 videos). Unfortunately, work responsibilities that couldn’t be put aside meant I had to put the remaining videos on hold. If lots of people work through the existing videos and are keen for more, then I’ll find time to finish them off. As it is, I hope the incomplete series is still useful.

One minor gotcha: originally, I was hoping to integrate the videos with a set of exercises. Again, time prevented me from doing this: there are no exercises. But as a remnant of this plan, in at least one video (video 7, the video on unitary matrices preserving length, and possibly elsewhere) I leave something “to the exercises”. Hopefully it’s pretty clear what needs to be filled in at this point, and viewers can supply the missing details.

Let me finish with two comments on approach. First, the videos treat quantum bits — qubits — as abstract mathematical entities, in a way similar to how we can think of conventional (classical) bits as 0 or 1, not as voltages in a circuit, or magnetic domains on a hard disk. I don’t get into the details of physical implementation at all. This approach bugs some people a lot, and others not at all. If you think it’ll bug you, these videos aren’t for you.

Second, the videos focus on the nuts-and-bolts of how things work. If you want a high-level overview of quantum computing, why it’s interesting, and what quantum computers may be capable of, there are many available online, a Google search away. Here’s a nice one, from Scott Aaronson. You may also enjoy David Deutsch’s original paper about quantum computing. It’s a bit harder to read than an article in Wired or Scientific American, but it’s worth the effort, for the paper gives a lot of insight into some of the fundamental reasons for thinking about quantum computing in the first place. Such higher-level articles may be helpful to read in conjunction with the videos.

Here’s the full list of videos, including the first one above. Note that because this really does get into the nuts and bolts of how things work, it also builds cumulatively. You can’t just skip straight to the quantum teleportation video and hope to understand it, you’ll need to work through the earlier videos, unless you already understand their content.

The basics

Superdense coding

Quantum teleportation

The postulates of quantum mechanics (TBC)

Thanks to Jen Dodd, Ilya Grigorik and Hassan Masum for feedback on the videos, and for many enjoyable discussions about open education.

If you enjoyed these videos, you may be interested in my forthcoming book, Reinventing Discovery, where I describe how online tools and open science are transforming the way scientific discoveries are made.