Tagged: techcrunch

Is website design becoming irrelevant?

Where & how do you consume content on the web these days? I find that increasingly, I get to the content without ever going to the website of origin.

For instance, on my iPhone I read pretty  much everything via Flipboard. On Android, I’m still struggling to find a good Flipboard replacement and shuttle between Pulse, Google Currents and recently, Feedly. In either case, I rarely ever go to the actual website.

I still get some of my content fix from Google Reader (xkcd, Abstruse Goose etc).

Most of the “news” — that is, when I’m in “skim mode” — comes from social media, mostly G+ and a tiny bit from Twitter.

I remember the days (several years ago) when Techcrunch changing it’s site layout used to be a news in itself. Now I can’t remember the last time I visited Techcrunch (well, that could be partially attributed to the content quality…)

My point is, in all of the above cases, the app or service presents the content in an origin-agnostic manner. When you read something on Flipboard, it’s presented to be consumable via the Flipboard interface (in most cases), and not meant to preserve the look and feel of the origin website.

And such apps and services are just becoming more and more prevalent: Evernote Clearly; Readability; content-provider specific apps such as those from Time, CNN, NYT etc.

So, is website design becoming irrelevant? Especially for content-heavy sites?

(The Oatmeal is an exception — Matthew forces you to visit the website, and it’s always worth it)

Lousy reporting at TechCrunch


Consider this gem from [[http://www.techcrunch.com/2008/02/20/yahoo-search-wants-to-be-more-like-google-embraces-hadoop/|a recent post on TechCrunch]]:


//Hadoop is an open-source implementation of Google’s MapReduce software and file system. It takes all the links on the Web found by a search engine’s crawlers and “reduces” them to a map of the Web so that ranking algorithms can be run against them.//

As one of the commenter’s rightly said, that is probably the most inaccurate description of Hadoop (or the Map-Reduce paradigm in general). The author, Erick Schonfeld, updated the post with another explanation based on feedback in the comments:


//What MapReduce and Hadoop do is break up a computation problem into mangeable chunks and distribute them to different processors—that is the “map” part, it is mapping the data. Once all of the individual results are in, they are combined into one big result—that is the reduce part. Search engines, in turn, use this technique to literally map the Web.//

While this is better, it is still far from an accurate and concise description. For instance, I’m not sure I understand (for that matter, even Erick understands) the relevance/meaning of the phrase “it is mapping the data” in this context. Or that results are “combined into one big result” in the reduce phase.

Given the visibility and readership of a prominent blog like TC, I find such reporting to be below par. If the author had taken 5 minutes to just try to understand the basic map-reduce paradigm, all this confusion could have been easily avoided.