Sharing pictures and making scriptures
·
This post on TC was pretty descriptive about the murky waters of photo sharing startups. Instagram and its monster exit has led to a plethora of startups doing Instagram + some additional features. There is a lot of movement in and around this space. Conceptually, photos carry so much traction because
1. Density of information - A photo is not just a way to capture a moment, it is also an instrument to preserve your memories, to think back and reflect about what you were doing when that memory was formed. It is also an effective way to signal. How will the world know that you are having fun if you dont post pictures on FB. A rough survey about the golden rule of the internet on reddit revealed that the 1st rule of the internet is indeed "Pics or it did not happen".
2. Simplicity of capturing this information - Even with your phone unlocked, you could snap a picture. Use a filter and you are your own agency. It is simple and very easy to use. Pretty much anyone can pick it up.
3. Means of expression - Photos lie at the intersection of expression and inspection. You want to have moments that are intensely private - like your family's pictures as well as photos that are for the eyes of the world (Think of the firehose on your newsfeed that Coachella accompanies)
4. Potential of this expression - Filters can do in an instant what the promised land of Photoshop used to be. You can do with your unused pictures what Sci-Fi movie makers in the 90s could only dream of.
Regarding the density of information,
There are the sticklers for the quality of photographs who wont touch FB photos. This is a niche group that does not want to see their precious quality get diminished by some hosting service, never mind if this service was 1 Billion strong. As Amazon EC2 grows and the costs diminish more, I would expect convergence on FB. The portfolio sites should not have a strong enough value proposition to continue. Or portfolio sites need to go the way of Medium and attract class content on the sites.
About the simplicity of capturing this information,
Can clicking a photo get any easier? I would wager not.
The means of expression is where this gets interesting,
Imagine the world having to know that you are having fun - classic Facebook. Imagine pics of your family and the closest friends that you have ever had, the ones who know everything about you from your internships to the interest you earn on your savings account. Think theres a potential problem to be solved? Path beat you to it. Is there potential to improve? I personally have a path account and like everybody, I love their design. I do not use Path much but that is probably because I do not have many friends I want to open my heart to.
Now over to the potential of this expression,
Thinking beyond filters, this is where the real potential seems to lie. Consider a few use cases
1. Family Vacation - I have an iPhone that auto uploads photos to Dropbox so I never have to manually take a backup again. There are 4 iPhones shared within the family. A grand total of about 250 photos and you have no idea which ones are worth keeping, discarding or sharing. You take all the photos and ask that they be added to a common sandbox. Here, an app iterates through the photos, face-matches your pics and sends the ones that you are in for you to categorize. This happens for all the photos and each member of the family is uniquely well positioned to identify good pics with them in it. Where this breaks down is when there are group pics or nature shots. A general voting on those photos and they are packaged for you to share in any way that you like.
2. Time travel - Those kids sure do grow up fast dont they? With this time travel app, you could keep time shifted records of things that grow rapidly. Pet owners form a lovely target user group. So do parents.
3. Group Pics - "We can just photoshop her in". Imagine an app that has a singular point of focus, to make a meaningful group pic.
And of course, then we move on to the holiest grail of them all.
The merging of the conceptual world and the real world. Imagine this great park that you have visited. You want to know if the hike up to the reservoir is worth it, or if the taco stand is just expensive or really good, or if the make out point a half mile away is worth a quick sprint after sunset. How about what did Jack do if he had 6 hours to kill in SF? Yelp and Foursquare are doing this with restaurants and cafes. The potential to enhance this body of knowledge to be malleable to the conceptual framework of reality is almost limitless. If anyones asking, Foursquare has a better shot at doing this than Yelp.
And thats where the next round will begin. Fight!
2. Time travel - Those kids sure do grow up fast dont they? With this time travel app, you could keep time shifted records of things that grow rapidly. Pet owners form a lovely target user group. So do parents.
3. Group Pics - "We can just photoshop her in". Imagine an app that has a singular point of focus, to make a meaningful group pic.
And of course, then we move on to the holiest grail of them all.
The merging of the conceptual world and the real world. Imagine this great park that you have visited. You want to know if the hike up to the reservoir is worth it, or if the taco stand is just expensive or really good, or if the make out point a half mile away is worth a quick sprint after sunset. How about what did Jack do if he had 6 hours to kill in SF? Yelp and Foursquare are doing this with restaurants and cafes. The potential to enhance this body of knowledge to be malleable to the conceptual framework of reality is almost limitless. If anyones asking, Foursquare has a better shot at doing this than Yelp.
And thats where the next round will begin. Fight!
Big Bag of Data
·
So data < information < insights
Having known this, why would we think that more data would help bridge the gap between data and information?
That is in essence the fallacy of big data. Big data will expand the range of hypotheses, it will also extend the range of the search space. Nothing gets easier with the addition of more data, especially when you are in the business of data exploration. The main job of a data scientist is to find possible hypotheses that describes what is happening with the data. The data does not lie, or at least lies less than the human :)
Should we collect more data? Should we care?
Just because data has grown exponentially, does not mean we keep collecting it. We care if the data is interesting. If the data fits snugly into an equation, we have figured out the data. There is no mystery left with the data anymore then we should not care about it. It is with figuring out the various "Whys" of the data that we can find true insights. We should only care when the data puzzles us.
Where do insights come from?
Not from no data. That double negative is just meant to express the fact that there is no accepted answer. Data helps and some data is better than no data. But where we should draw the line is highly debatable. The storage costs per gigabyte reducing by a factor of 6 has meant that we can safely store information without having to worry about cost overhead but it is in the utility of this data that we are confused. Big, huge quantities of data are not necessarily high yield in terms of insight. And it is here that having a lean approach towards storage can certainly help.
In conclusion
Store the data to figure it out. Once it fits, its time to move on to another data set. It is in these attitudes of exploration that we can truly drive insights or at least a mindset that helps achieve insights.
Riffed off of and thought credits to
http://techcrunch.com/2012/11/25/the-big-data-fallacy-data-%E2%89%A0-information-%E2%89%A0-insights/
Having known this, why would we think that more data would help bridge the gap between data and information?
That is in essence the fallacy of big data. Big data will expand the range of hypotheses, it will also extend the range of the search space. Nothing gets easier with the addition of more data, especially when you are in the business of data exploration. The main job of a data scientist is to find possible hypotheses that describes what is happening with the data. The data does not lie, or at least lies less than the human :)
Should we collect more data? Should we care?
Just because data has grown exponentially, does not mean we keep collecting it. We care if the data is interesting. If the data fits snugly into an equation, we have figured out the data. There is no mystery left with the data anymore then we should not care about it. It is with figuring out the various "Whys" of the data that we can find true insights. We should only care when the data puzzles us.
Where do insights come from?
Not from no data. That double negative is just meant to express the fact that there is no accepted answer. Data helps and some data is better than no data. But where we should draw the line is highly debatable. The storage costs per gigabyte reducing by a factor of 6 has meant that we can safely store information without having to worry about cost overhead but it is in the utility of this data that we are confused. Big, huge quantities of data are not necessarily high yield in terms of insight. And it is here that having a lean approach towards storage can certainly help.
In conclusion
Store the data to figure it out. Once it fits, its time to move on to another data set. It is in these attitudes of exploration that we can truly drive insights or at least a mindset that helps achieve insights.
Riffed off of and thought credits to
http://techcrunch.com/2012/11/25/the-big-data-fallacy-data-%E2%89%A0-information-%E2%89%A0-insights/
Subscribe to:
Posts (Atom)
