Midway through the talk, Shum mentioned that Google’s stated philosophy is to minimize the time that users interact with search results pages. A search engine should do little more than give you easy access to maximally-relevant external content and then get out of your way. I couldn’t agree with this more, but Bing’s strategy is very different. Shum said that their goal is to get people to interact completely with Bing, instead of solely acting as a helpful navigator. Bing is littered with features intended to keep you on Bing, including quick-info boxes at the top of search results, fancy inline slideshows, and built-in Wolfram|Alpha support.

Bing is designed around “complex task and decision sessions,” instead of simple query-response chatter. I don’t entirely agree with this use case. I understand that some people may like the type of interactivity that Bing provides, but that’s not how people I know search for things on the internet. People don’t go to Google with the goal of getting their information from Google. They search with the intent of gaining access to some relevant piece of information on some other site. It’s like Bing is trying to be the illegitimate child of Google and Wikipedia, but ends up with AOL.

As a side note, Shum’s talk gave me an interesting view into the workflow of a Microsoft head-honcho. During the live demo portion of his talk, I was startled by his Internet Explorer setup. His four toolbars (including separate ones for Live Search and Bing), in addition to the IE browser chrome, left about 65% of the browser window actually occupied by webpages. I wish I had a screenshot. Take into account the giant blocks of ads centerstage and to the right of results in Bing, and you’re left with precious little room for useful content.

The talk as a whole was somewhat frustrating because I want Bing to succeed. I like Google as a whole (so much so that I’m interning there this summer), but their dominance of the search market is pretty ridiculous. As consumers, we all benefit from competition between services in the same space. As such, it’d be nice to see Google get some solid competition to keep everyone on their toes. I hope that the Bing team continues to iterate on their aspirations for usability and develops a kickass service to shake things up.

I’m currently reading Logicomix, a graphic novel with a twofold role as a biography of Bertrand Russell and a concise history of the quest for mathematical certainty that took place in the early 20th century. Reading it alongside a courseload of discrete math and theory of computation classes has me knee-deep in the mathematical foundations of computer science. While these foundations are valid and necessary for a historical appreciation of the field, they don’t always lend themselves well to contemporary issues faced in industry and academia.

Spector’s talk reinforced the image of Google as grand archiver and distributor of the consolidated sum of human knowledge, a role not always well-served by a traditional approach. In recent years, we’ve seen a rise in parallel and probabilistic approaches to emerging problems: MapReduce/Hadoop, machine learning, Bayesian this, Markov that. With the astronomical amounts of data that companies like Google have to deal with, the door is opened for statistical methods.

Computer science deals with more measurable quantities than it used to. For example, as networks and systems grow larger, small margins of error or delay become more readily measurable. When the entire world is your testbed, you have to measure and test every aspect of the systems you build. In this sense, CS is increasingly becoming a more empirical science.

My only hope is that this was more often emphasized in classes, instead of by visiting guest lecturers.

The first step was to set up an XML-RPC server to serve remote calls to the pygeoip API. This was fairly easy to do using Python’s SimpleXMLRPCServer class:

from SimpleXMLRPCServer import SimpleXMLRPCServer
import pygeoip
...
# Create server
server = SimpleXMLRPCServer((ip, port), allow_none=True)

The location-lookup methods within the pygeoip library must be registered for use via the XML-RPC server. We first initialize a GeoIP object, passing it the filename of a valid binary GeoIP database. Then the GeoIP object is passed to the XML-RPC server’s register_instance method to expose its methods for remote execution:

# Initialize and register GeoIP object
gi = pygeoip.GeoIP(geoipdb_filename)
server.register_instance(gi)

# Run the server's main loop
server.serve_forever()

The lookup methods of pygeoip can now be called remotely. To demonstrate my project, I wrote a script that fetches the IPs of all nodes in the distributed computing network that you’ve allocated, looks up their lat/lang coordinates, and plots them on a Google map. For funsies I used the geolocation API built into Firefox 3.5+to include a pointer to the user’s current location.

Screenshot of project demo

Hopefully my little library will get some use. Moving into the new year, I’m hoping to increase my involvement in the Seattle project and become more familiar with networking and API design.

My initial implementation created a Javascript date object and compared the results of its getUTCDay, getUTCHours, and getUTCMinutes() functions to the developer-specified warning times. If the current time was greater than the set warning time, the banner was displayed. There’s some cookie-handling in there so that the user can close the warning banner and not have it show up until the next warning time, but no bother.

A potential problem arose in that Javascript uses the client’s local time to create date objects. Thus if the user’s computer had incorrect time, the warning banner wouldn’t display when it was supposed to. A better way to go about it would be to use the server’s time instead of the client’s.

Luckily I could make use of Mason’s preprocessor to insert the results of the Perl time() function into clientside Javascript to get the server time. I first calculate the client/server time difference and then use it to create an accurate date object inside the poll function.

// Determine delta between client and server times
var time_delta = (<% time %> * 1000) - Date.now();

function launchWarningPoll() {
    var d = new Date(Date.now() + time_delta);
    ...
}

As launchWarningPoll() gets called every 60 seconds, it will accurately portray the server time regardless of how much the user’s local time is off.

Second, you can now save and revisit inventions. As suggested by commentors,  generated-invention pages now have save buttons that give you permalinks.

So go create random inventions and share them with your friends!

The app is built around a Markov processor assignment I had last quarter in a programming languages course. Essentially the program uses Markov chains and a binary tree of n-grams to generate random text based on word frequencies of whatever source text you feed it. In effect, the generated text is babble in the language of whatever source document you input.

I had a lot of fun playing with the program last quarter. I’d give it the history of America as a text file and get to read about English settlers crossing the Delaware under siege by the Confederate army. Or noticing how randomly-generated text in the language of the Bible wasn’t really any easier to read than the real thing.

After hearing about the Apps for America 2 challenge, I spent a few weeks scoping out datasets on Data.gov and thinking about ways to use them. I zeroed in on the XML files of US patent application bibliographic data and eventually connected the dots back to the Markov processor assignment.

The contest entry page for Eureka can be viewed here. All source code is available on GitHub. This includes some shell and Python scripts to validate and parse the XML, a Ruby port of my Markov processor (originally in ML), and the website frontend of the app.

With regard to typography, Josef Albers writes:

“The concept that ‘the simpler the form of a letter the simpler its reading’ was an obsession of beginning constructivism. It became something like a dogma, and is still followed by ‘modernistic’ typographers…. Ophthalmology has disclosed that the more the letters are differentiated from each other, the easier is the reading. Without going into comparisons and details, it should be realized that words consisting of only capital letters present the most difficult reading — because of their equal height, equal volume, and, with most, their equal width. When comparing serif letters with sans-serif, the latter provide an uneasy reading. The fashionable preference for sans-serif in text shows neither historical nor practical competence.”

Josef Albers, Interaction of Color (New Haven, 1963, revised edition 1975), p. 4.

The message should speak for itself, but I found it striking in particular given the now-cliché trend of lowercase sans-serif company and website names. This was printed over 25 years before the era of flickr, digg, facebook, and mint.

Mind you, this trend in part tends to only apply to logos and images, leaving websites’ copy properly capitalized. However, it takes actual effort to find a modern web service brandishing serifs in body content. If your product’s brand is trying to convey a sense of easy-going, friendly, hipness, then you’re more likely to eschew statistical readability for the cool finnesse of helvetica, lucida grande, and tahoma.

• Make chai from scratch
• Spend more time reading (books)
• Work out at least three times per week, consistently
• Learn more about stocks, trading, economics
• Redesign this website
• Write more consistently for this website
• Start doing research within the CSE department at UW
• Get really good at cooking
• Get a spice rack
• Be mindful
• Finish learning CakePHP
• Be able to taste the difference between english and irish breakfast
• Get a drum set
• Play a show
• Keep being independent
• Don’t stir the jam
• Break 15,000 songs
• Be able to lift a respectable amount of weight
• Code more fluidly
• Live more fluidly
• Live by the words you say
• Get out of bed in the morning quicker
• Learn

When I complained about being paid fifty dollars for an article that had taken me a week to write, he [Kurt] said I should take into account what it would have cost me to take out a two-page ad announcing that I could write.

The message here is simple: if you are in a profession where your work is viewed publicly, then you should worry less about how much you’re being paid, and more about doing good work.

Why? Because if your work is publicly displayed (be it in print, the web, or whatever), then it serves as an advertisement for you skills. If you’re a designer, the best marketing you can do is to create attractive products that accomplish what clients want. A happy client will be more likely to share his happiness with others, thus shooting business your way. Word of mouth has exploded.

If you’re a developer working for a company of any size, write the best code you can and make sure others know about it. If you’re a writer, write your ass off. Your name is wherever your words are, so every article you get published is active marketing.

If you’ve got the chops, flaunt them and reap the rewards.

In his most recent email, Jason Calacanis offers insight into how to achieve the first part of this question:

It was our collective sloth, consumption and sense of entitlement that got us into this mess, and the only thing that will get us out will be lots of hard work.

This bodes well with Gary V’s concept of “hustle” and aligns itself with the positive side of my feelings toward capitalism. Insidious advertising, closed-mindedness, and corruption aside, a capitalist system appeals to me in that (virtually) anyone can “make it” by simply buckling down and doing work. Got an innovative idea? Build on it and capitalize.

One of the exhilarating parts of today’s software/web industry is its tendency to be a catalyst to the American dream. The cost (both monetary and temporal) of innovation in the software space is so incredibly low that the hardest part of the process becomes the search for an idea to act on. A result of this is my train of thought trying to come up with a revolutionary web service when it should be refreshing itself on linear transformation.

In times like this I try to remind myself of another Calacanis bit from TWIT a couple months ago. In essence, recessions are the best time for entrepreneurs because it gives them a quiet period of time to stay in the shadows and build value. While all this economic turmoil and fail is unfolding, you’re given the opportunity to take a step back and improve yourself so that you can rush out swinging confidently when the economy turns around.

In my case, this means buckling down and learning as much as I possibly can in school and at work. As a college student, the best thing you can do for yourself and your future is to suck it up and learn. Knowledge will always be the most valuable resource in the world and if you can increase your share of it, you’ll end up fine. Even in the face of economic meltdown.