Welcome to The Weekender, April 28 2012 edition. This week, it’s all about testing, experiments, and the battle between humans and computers. Are you in, or are you Skynet?
Is Siri Smarter than Google?, by samzenpus, SlashDot :
Google could go the way of the dodo if ultra intelligent electronic agents (UIEA) make their way into the mainstream, according to technology prognosticator Daniel Burrus. Siri is just the first example of how a UIEA could end search as we know it. By leveraging the cloud and supercomputing capabilities, Siri uses natural language search to circumvent the entire Google process. If Burrus is right, we’ll no longer have to wade through ’30,000,000 returns in .0013 milliseconds’ of irrelevant search results.
Which is the seeds sown for a fascinating argument– what is the direction of voice-controlled artificial intelligence (and does Siri qualify)? As one commenter put it, “What will be truly revolutionary is when we can have conversation with Siri.” And no, it wasn’t Alan Turing.
The A/B Test: Inside the Technology That’s Changing the Rules of Business, by Brian Christian, Wired, and Is Our Adults Learning?, by David Brooks, New York Times:
Wired reports that A/B testing, after years of being an insider secret, is quietly beginning to dictate everything from political messages to news headlines. It works: by setting out two versions of the same thing (the A & the B) to a small and random audience without letting them know, you can understand their preferences through hard data and make incremental tweaks for a better business:
Where editors at a news site, for example, might have sat around a table for 15 minutes trying to decide on the best phrasing for an important headline, they can simply run all the proposed headlines and let the testing decide. Consensus, even democracy, has been replaced by pluralism—resolved by data. Wired
While accessible data and analytics is great, it also has the potential to stifle innovation in favor of incremental change. For example: Steve Jobs did zero product testing. Or to paraphrase Henry Ford, “They would have told me they wanted a better horse.” Moreover, the question arises, should everything be tested? Can everything be tested? David Brooks argues:
Businesses conduct hundreds of thousands of randomized trials each year. Pharmaceutical companies conduct thousands more. But government? Hardly any. Government agencies conduct only a smattering of controlled experiments to test policies in the justice system, education, welfare and so on.
Why doesn’t government want to learn? First, there’s no infrastructure. There are few agencies designed to supervise such experiments. Second, there is no way to conduct a randomized experiment to test big economy wide policies like the stimulus package.
Finally, the general lesson of randomized experiments is that the vast majority of new proposals do not work, and those that do work only do so to a limited extent and only under certain circumstances. This is true in business and government. Politicians are not inclined to set up rigorous testing methods showing that their favorite ideas don’t work.
The Descriptive Camera, Matt Richardson:
The Descriptive Camera works a lot like a regular camera—point it at subject and press the shutter button to capture the scene. However, instead of producing an image, this prototype outputs a text description of the scene. Modern digital cameras capture gobs of parsable metadata about photos such as the camera’s settings, the location of the photo, the date, and time, but they don’t output any information about the content of the photo. The Descriptive Cameraonly outputs the metadata about the content.
As we amass an incredible amount of photos, it becomes increasingly difficult to manage our collections. Imagine if descriptive metadata about each photo could be appended to the image on the fly—information about who is in each photo, what they’re doing, and their environment could become incredibly useful in being able to search, filter, and cross-reference our photo collections. Of course, we don’t yet have the technology that makes this a practical proposition, but the Descriptive Camera explores these possibilities.
One Man’s Newsletter Leads the Fight Against Twitter Overload, by Hamish McKenzie, Pando Daily:
…and no, that’s not me. It’s Dave Pell, who writes the NextDraft email newsletter of stuff interesting on the web. It’s a great interview, but one of his most important points is of the role of human curation of information on the internet. Algorithms are great: they can pinpoint your interests and deliver you a stream of content, but they are bad at sifting out relevancy from news. Moreover, an algorithm doesn’t have a great and original voice while doing it.
Or, at least, not yet, argues Evgeny Morozov in Slate’s A Robot Stole My Pulitzer. But it’s close. Robots writing journalism is here.
What the Hell Did We Just Read?, by the Editors, LongReads:
LongReads, the site that curates long-form journalism, looks back on what people like to read, as their data shows after two years. Turns out, it’s all about people’s failures, technology’s success, and crime, which with no pun intended, stole all the LongReads views. But the data also shows that people like reading long, old stuff. Also interesting: SEO headlines do well in getting views, but none of the most popular articles were SEO optimized, probably because 5 Things You Need to Known About _____, in 5000 Words” doesn’t really age as well as “Frank Sinatra Has A Cold.”
Inside the MIT Media Lab, by Charles Stross, Antipope:
Inside probably one of the coolest places in the world?
In one corner, a bunch of students are trying to reinvent the wheel — specifically, the car steering wheel, which they’re trying to add intelligence to. You look around the back of the room. There’s a sign identifying an experiment in Borgables. Under it you see the waistcoat that ate Silicon Valley, an unlikely offspring of a mating between a sewing machine and a laptop computer, bristling with memory, sensors, and i/o devices.
Take the elevator down a floor. Walk through another glass door beneath a sign proclaiming the Opera of the Future, and you find yourself in a room full of brightly coloured balloon-shaped musical instruments plugged into a rackful of experimental electronics. The instruments are actually the user interface to a whole bunch of computers that comprise the Children’s Symphony. The object of the project isn’t to reinvent the Stradivarius but to change the way toddlers learn to make music — by giving them brightly coloured toys that provide immediate feedback, letting them explore the shape of sounds for themselves rather than struggling for years to master the piano keyboard or the guitar fretboard.
Take the down elevator again and you’re in the quantum computing lab, next to a two-metre high dewar flask full of liquid nitrogen. This is where they’re trying to build a quantum computer — exploiting the eldritch physical phenomenon of quantum decoherence to solve complex iterative problems in linear time. (It’s a bit of a culture shock after the children’s symphony and the sympathetic steering wheel, but you’re beginning to get a feel for how off-balance a tour of this building can make you — if you expect a random surprise around every corner you won’t go wrong.)
* * * * *
This Weekender has been compiled and excerpted by Roman Kudryashov, Max Gi, and Rostislav Roznoshchik. Thank you for reading!Read More