Nokia prides itself on making a durable phone that can withstand daily wear and tear. The short video below gives you a look inside the test center where they drop, bend, and tumble the phones to see if they can stand up to whatever our customers can throw at it.
For some more wincing field tests, be sure to check out what these crazy Russians have put their Nokia 5800 through.
UPDATE: There’s more! Someone in Wisconson found a Nokia in their bag of potato chips. No word on weather it was still working though.
Is twitter a directory or a utility? This is the question that Charles Hudson raises in his post The Database of Intentions is More Valuable than the Database of Musings. While investigating prospective business models, he raises good questions about the ability of a collection of “accumulated musings” to determine intent which is what is most valuable to advertisers.
But maybe advertising is not the great revenue driver of the next generation of startups after all, at least not advertising as we know it. Maybe it’s just me but I feel a need to make sense of all the stuff we share with each other. There seems to be value in tapping into the pulse of the “now web” but the methods of pulling meaning out of the noise seem crude. Keyword searches? Is that the best we can do?
Something went wrong with the Intense Debate comments on last night’s post on Keywords and Meaning. It’s unfortunate because there were some really thoughtful responses to the post which I’ll repeat in this post because they are worth reading.
Keyword extraction from Twitter could be cool, but may kill of serendipitous discovery, my favorite aspect of Twitter. If keywords or meta-categories are predetermined truly unique hawtness, unprecedented new things ( a Twitter specialty ) will just get deleted? That would be FAIL.
I wonder if more of a “people with attributes” are really what’s needed. Example, I do want to know what’s going on with the latest developments for Symbian operating system, particularly activity streams and address book stuff. Rather than rely on keyword extraction, I could just assign an attribute to your tweets…
…I can be fairly assured news filtered by real humans, THEN assigned an attribute of my choosing will bring me some good results. A tag cloud of all tweets containing “symbian, activity stream, address book” would be noisy ( pollute with people asking each other for tech support? ), difficult to pull meaning from while drinking beer at my favorite bar.
Jonathan Strauss writes:
The TechCrunch post you cite was inspired by John Borthwick’s very interesting essay on how Google’s approach to content filtering breaks in the realm of what he calls the ‘Now Web.’ Like you say above: “Google’s PageRank, while valueable in sorting out the reputation and tossing the hucksters, is no good when applied to real-time news which is too fresh to build up a linkmap.”
In the (relatively) static web, the network nodes are pages and the endorsement actions are the links between them which are effectively permanent as well as public, and thus crawlable. In the Now Web, the network nodes are people and the endorsements are ephemeral share actions, the majority of which are not public or crawlable (i.e. email, IM, Facebook — what I call the ‘Deep Now Web’). And so, authority also takes on a different form from the aggregate view that PageRank provides to the personal measure of how much influence an individual has with her social network on a particular topic at a given moment.
I agree that we need to have a means of systematically capturing the newly important metadata of share actions and that it needs to be done at the point of sharing (see Jeff Jonas). But, I believe the more easily adopted (and thus ultimately more useful) taxonomy will be one of contextual metadata (i.e. who/what/when/where/why/how) rather than the more personal folksonomy/tagging approach you suggest.
There was also reactions via twitter from Kevin Marks:
@kevinmarks yes, to a certain extent, you are who you read. Is your OPML and Follow list the digital equivalent of DNA?
— ian kennedy (@iankennedy) February 16, 2009
@iankennedy thats not what i meant; i meant we filter through others: we are each others' media
— Kevin Marks (@kevinmarks) February 16, 2009
The act of sharing links, photos, or other metadata on social networks is an action, to a certain extent, that gesture is more interesting than the actual data itself. The fact that my usually dormant cycle racing friends are now extremely active on twitter these past few days as the Tour of California is on is as much an indicator of interest as the actual substance of their conversation.
Keywords are part of the picture – the complete context around who/when/where/why/how are just as important as the tidbit of data itself. The meta-data contains more clues than the data.
The cellphone is a rich source of meta-data which can be captured at the source, the moment of sharing. Feeding contexts captured from the cell phone would be a great way to add context to any act of sharing. There are privacy concerns and ownership questions. There needs to be a real value demonstrated to the potential user before they give up some of this privacy. But that’s a topic for another post.
TechCrunch asks if twitter search gets us closer to being able to mine the world’s collective thoughts. We may be getting there as millions text their latest thoughts into their cellphones. With a simple text message, the hive mind has the potential for 4 billion nodes out in the real world (for comparison, the human brain has 100 billion neurons)
News junkies of the world turn to twitter as the latest source of raw, unfiltered information. Peering over the shoulder of various members of the House and Senate who twitter is a unique view into our government. What you see is a more intimate, human view of the people that make the news. Yet, how do you harness that noise and turn it’s output into information?
Twitter follows a long line of services which break through editorial filters, get at the source of a story so you can make your own judgements. Blogs occupied this space just a few years ago and real-time indexes such as Technorati rose to prominence as a way to get a jump on the news.
Sidenote: Alacra, admitting important news about companies breaks on the web, is launching Pulse which applies their analytics engine to extract company names from their hand-picked collection of 2,000 RSS feeds.
The need for speed is nothing new. Former Wall Street Journal newsman Craig Forman draws an arc that extends through the real-time newswires used in the financial world back to the pidgeons of Baron Reuter that delivered news of Napoleon’s defeat at Waterloo. If there’s a way for someone to profit from the knowing something before anyone else, there’s always going to be people looking for a way to get at a scoop and others looking for a way to deliver.
We want to look to twitter for the scoops but we are doomed to learn the same lessons as we have in the past about authenticity. What we gain in speed and convenience, we lose in validation and measured fact-checking. Google’s PageRank, while valueable in sorting out the reputation and tossing the hucksters, is no good when applied to real-time news which is too fresh to build up a linkmap.
Working for Dow Jones in Tokyo, I would work with bankers and reporters who would use digital newswires to deliver them the latest news from around the world. As a systems engineer setting up their workstations, I would often be asked to set up their news filters to narrow the feeds down to something reasonable (the typical newswire delivers hundreds of stories an hour, most subsribe to several newswires). In the late-90’s the tools were crude and after getting frustrated by throwing in a few keywords, I would get called in to refine things using additional tools such as company ticker symbols, or a few undocumented codes from a taxonomy of subjects that varied from newswire to newswire.
Today the problem of information overload has spread to the greater population trying to derive value from the rushing torrent of updates coming out of twitter and facebook. How do I manage all this stuff and figure out what’s important? We use the tools we have but if you think about it, Google Trends and twitter search are just keyword searches with very crude resolution. We have a long way to go before such tools will let us tap into the collective mind.
Perhaps it’s time for a crude taxonomy for social networks to help sort out the types of messages flowing back and forth? Imagine if all your tweets, facebook messages, and friendfeed streams came pre-tagged with the following tags or categories?
- look at me, I’m doing something cool
- check this out, it’s funny
- books, movies, music, food, or sports
- this is touching and will change your life
- gadgets and meta, technology post about using technology
- weather and the natural world
- babies and kittens
- my obscure hobby
- breaking news, OMG!
- make money now!
What other categories would you add? Librarians of the world, what keywords would you put into your search filters to help grep out what goes where? Categorization is the first step towards ranking and with ranking you get useful filters.
For various reasons I was unable to attend the Open ID Design Summit. Thankfully, the talks were very well covered so it’s possible for anyone see what happened and the current state of discussions around what’s being called the “open stack”
Live-blogging the openid design summit – John McCrea from Plaxo did a great job of live-blogging the event. This is the best place to start because his post also embeds all the presentations. Thanks John!
Chris Messina just posted a bunch of video clips:
More below the fold: