Nymi and Galaxy Gear

September 2, 2013September 3, 2013 Niranjan NandakumarLeave a comment

This week will perhaps see the release of two gadgets that have the potential to change the ways of life. Wearable as they are, both are worn on wrists. While one is released by a major player in the gadget market, the other comes from a new comer. While one of them has an aura of excitement in its launch, the other will be taken with a bit of skepticism. I’m talking about the Samsung Galaxy Gear set to be announced on Wednesday, Sept. 4th in Berlin and Nymi , soon to be out for sale by a company called bionym

Let me start by talking about Samsung Galaxy Gear. Samsung has started to become rather secretive about their product launches, building up the expectations and the curiosity. So there isn’t a definitive Galaxy Gear snapped yet. While the early pictures show something rather bulky, as the choices in the market seem to still be scanty and since Apple has been amazingly slow in bringing its much hyped iWatch to market (gone are the days when Apple launches were considered to revolutionize markets!), there is hope for those with smaller wrists, such as me.

With a Wifi Radio and 4MP camera , that would perhaps require an awkwardly held hand to take a snap, the “gear” seems to run Android in its core, giving it a better potential than the Newton of the PDA world!

Then came Nymi, from the Toronto based startup called Bionym, taking biometrics to the next level. While the rest of the world is still playing with the fingerprint recognition at the same time fantasizing about the biometrics of the retina glorified by the heist movies over the years, Bionym, realized that hidden amongst the Electro Cardio Gram (ECG) pattern is what is known as a HeartID , unique to every individual. And using this, the wristband can now help unlock your phones, laptops and potentially even your car!

SecurID News has a rather extensive review of the technology, going on to explain the out-of-box authentication methods and how secure it can prove to be. Karl Martin, the CEO of this highly optimistic startup, goes on to explain that this is a first generation product. More needs to be seen on how the market responds.

My first take, as I have always been extremely excited about new gadget, will obviously be biased. There is potential, if channeled the right way. At the same time, it takes a lot to make a common man accept such a security tool, given the high caution thrown on identity thefts these days.

Nevertheless, exciting times are ahead!

iCrowd – Unraveling the power of crowd in the web world

August 26, 2013 Niranjan NandakumarLeave a comment

I must begin with a confession. I am a terrible Apple fanatic. So any resemblance in the title here is not a mere coincidence. But I assure you, the resemblance stops here. This is a concept – one that can perhaps be described as a concoction of a multitude of concepts that have already been floating around. Through the posts that follow, you will find me elaborating more on every one of those concepts to unearth a common theme across them – the crowd. Over the past five years, as social media and networking have started to mushroom around the web world, with smartphones and tablets becoming a common man’s gadget, several companies have started to make use of the data that is updated by users around the globe. And indeed many of the entrepreneurs and thinkers of this era have started to find correlations amongst these efforts. And along came several concepts, those which have gradually started to become an everyday term. Among them, Collaborative Consumption coined by Rachel Botsman , Crowd Sourcing coined by Jeff Howe of the Wired Magazine and Cognitive Surplus by Clay Shirky have grown significantly, in parallel.

While each of these talk about the influence of crowd in the functioning of the today’s world, analyzing and categorizing companies and organizations among various buckets, each have their own distinction. They portray a very specific aspect of the crowd and collectively they can encompass the iCrowd, in its entirety. Collaborative consumption talks about the idea of sharing what you have with a stranger, through a common platform for sharing, that is built upon trust. The product that is shared can vary with an organization that lay forth the platform. Airbnb, Taskbunny, A Spare to Share are all examples of this sharing. Rachel Botsman through her ground breaking talk at TED and her book What’s mine is yours , laid the foundation to this categorization of sharing, into buckets based on services .

Crowd Sourcing, coined back in 2005, talks about the idea of converting user input data into useful information, in the form of trend or recommendations or even just a single point of data depicting the state based on the data gathered from the “crowd”. I have spoken extensively about Crowd Sourcing and have tried to classify them into some reasonable buckets. SkyMotion, Waze, Minutely are all applications that have presented information from a large repository of user input data. There are then the amazon recommendations providing you with a list of products that “other customers” looked at, after viewing a particular product, in which case the input is user data collected passively. We will look into both these situations and how they play a part in the information transfer.

Cognitive Surplus is a more recent term, yet to be defined exhaustively. Clay Shirky describes it as a form of constructively making use of an individual’s free time towards a particular goal. Add in the crowd dimension and you now have an “organization without an organization”. Wikipedia is perhaps the best example of this “revolution”. Although Wikipedia has been around for quite sometime, identifying the concept that made it a huge online encyclopedia was as recent as 2009. As more and more efforts start getting categorized under this umbrella, cognitive surplus can be yet another powerful concept making use of the power of crowd.

In the coming weeks, I will hoop through each of them in more detail, pointing out examples that illustrate the common link and the distinctions.

Is the era of grandeur in product launching gone?

July 25, 2013 Niranjan NandakumarLeave a comment

There was a time when product launches were a red carpet event. Be it the special invitees from the developer world and the tech news media, flocking in from all parts of the world to witness the “magical” opening of the iphone

Or the Taylor Swift show at the Sony product launch

Yesterday, at a quiet little press conference known as “Breakfast with Sundar” , Google announced a good chunk of products and among them was something really revolutionary , not because it was the first of its kind to the market, but more so because of its form factor and the pricing. They called it the “ChromeCast” And before you knew, it was sold out in every online store. Deemed as a direct competitor to AppleTV and Roku, and perhaps with a little edge due to its interoperability, looks like the battle of the giants has moved to the TV world now!

PS: you can read the first exhaustive review on it here

So let me leave you with a simple poll…

CrowdSourcing Classified

July 9, 2013July 14, 2013 Niranjan NandakumarLeave a comment

The term crowd sourcing is rather generic in its own ways. Although coined for a specific function, it soon grew into being a broad term interpreted differently by every organization that has crossed its path. Therefore it might be essential to classify the different aspects of crowdsourcing and identify buckets of projects/organizations that can be put under each. Here is a small effort towards one such classification. Wikipedia in its own way has a different interpretation for the same.

Open Democracy: or Crowdvoting as Wikipedia calls it.
Ever since life began, democracy has been prevalent . Taking that to product design can hence be just an afterthought. Several organizations across the iGlobe has successfully used this method to better understand the consumer needs and interests.

Lego CUUSO is one such. Termed as “just a normal way of doing things” in today’s generation, Lego was able to create the famous Lego MineCraft using power of the crowd.

ThreadLess – an online shirt design company – is yet another, taking advantage of the crowd.

In a perfect world, the underlying principles for all such organizations are the same. Users submit a product design, which is then put up for voting. When the voting number reaches a particular threshold, the product is formalized and staged. Of course the user who submitted the design gets a share of the royalty.

Data Sourcing:
Skymotion and Waze are perhaps the best examples for this. Obtaining the wealth of the data provided by users to portray information. I spoke about Waze and Skymotion in my previous post.

In fact, Wikipedia, can also be viewed as one such entity leveraging the power of the crowd.

Now, the means of providing the information can be direct or indirect. In all the cases above, the information was provided by the users, consciously and hence can be termed as direct. Take the example of Google’s Flu Prediction . The trend has been graphically represented using the search terms related to flu that people search across different parts of United States. In this case, information is gathered passively and hence can be classified as indirect.

Open Sourcing:
Although this term has been in existence since the early 1960s, I feel it could now fall under the umbrella of crowd sourcing. Essentially the development of the product or the software was done by the masses. The ever so popular Linux is perhaps the best example for this.

CrowdFunding or Micropatrionage:
This is one of those which has been less prevalent, but you do see pockets of such organizations cropping up all around the iGlobe. The idea again, follows along the same lines – use crowd to fund projects. Although it can be revolutionary, it does come with a pinch of salt. Whenever an individual is expected to “invest” money, however small it is, there is a sense of ownership that gets built around it. It is for this same reason that the Crowd Funding Exemption Movement was set up to successfully lobby the JOBS Act

KickStarter is one such companies, which has been rather successful in funding projects and startups through small deposits collected through their website. Most prevalent in film community for the making of independent films, for channels such as Sundance , KickStarter has been successful in harnessing the power of crowd to fund a large number of undertakings.

While examples can be drawn from all aspects of the web world, I’m hoping these broad classifications can be a good start to better define crowd sourcing. Let me know your thoughts.

Next up: Why do organizations move towards Crowd Sourcing?

While you wait, let me leave you with this interesting video on crowdsourcing.

The art of crowdsourcing

June 30, 2013 Niranjan NandakumarLeave a comment

With the emergence of social networking as a formidable force in this Internet era, taking advantage of its powers in fields other than just entertainment was only an obvious consequence. The word crowdsourcing first emerged back in 2005, coined by the editors of Wired Magazine. Jeff Howe from wired magazine defines it as the act of a company or institution taking a function once performed by employees and outsourcing it to an undefined (and generally large) network of people in the form of an open call. This can take the form of peer-production (when the job is performed collaboratively), but is also often undertaken by sole individuals. The crucial prerequisite is the use of the open call format and the large network of potential laborers.

It is the ability to harness the data exchanged by the population aka “the crowd”, and use them to produce information useful for the same crowd. Jeff Howe went on to become a proponent in this field, citing examples from all around the Internet Globe (the iGlobe, as I would call it) on how the power of the masses can be strategically taken advantage of. Sometime back, I happened to mention about one of those terms which has been gaining popularity, viz Collaborative Consumption . Crowd sourcing can be viewed as a subset of this idea.

Perhaps one of the biggest in the industry to take advantage of this was Waze . With its data being fed in by the millions of drivers on the road, it started to become a powerful navigation system, often even claimed to have been surpassing the giants such as google maps and apple maps . But as has been the common norm amongst the technology industry, it too got acquired for a huge price by one of those giants.

But that was only the beginning. Along came Sky Motion in a different field – the weather! Forecasting weather has always had its degree of unpredictability. The intensity of the weather conditions have been known to be inaccurate often times. What if you have a real time update from a person who is actually in the middle of it? That is exactly what Sky Motion has tried to do. Although not as widely accepted yet, just as in the case of Waze it does have the potential to turn into something big. Now they are not the only ones that have imbibed this idea in weather. Weddar is another one such company. So now we have a healthy competition!

As weather and traffic seemed to have started to see the useful side of crowdsourcing, Im sure many more would follow. What was ones the supreme power of the ancient civilizations, the society, could soon turn into the superpower in the Internet Civilization!

Genres in streaming music industry

May 19, 2013 Niranjan NandakumarLeave a comment

Just this other day, Google announced its Google Play Music at their Google I/O . And the rumors of Apple iRadio and the challenges involved have been in the news for quite sometime now. Some say google beat Apple in the world of Internet music. But if you look closely, there is a fundamental difference in the approaches that Google and Apple have taken in the field of digital streaming music. To understand this, lets look at two of the main runners in this field today – Pandora and Spotify.

Although both Pandora and Spotify are common in their goals to deliver music to consumers, without actually a need to purchase the albums, their ways of doing it are different. While Spotify follows more of an on-demand, subscription based model, Pandora has resorted to a webcasting service. This difference is not as apparent on the desktops and laptops, where both parties offer free access to users with ads injected rather frequently. But its not at that shocking a revelation to note that the number of users using their desktops for music have diminished dramatically in the last decade or so. In the handhelds segment, Spotify offers a 30-day free trial, followed by a $9.99 per month subscription and Pandora has extended the same model as they have with desktop. The result is the emergence of two schools of thought – The Pandora Model and the Spotify Model.

Google has decided to follow the spotify model , with a $7.99/month fee for those who subscribe before June 30th and $9.99/month for those after. Of course the 30 day free trial is always a requirement. Rumor has it that Apple will follow the Pandora model , going by its challenges to obtain copyrights, just as Pandora has been criticized for their small collection again owing to the copyright issues.

So now we have two genres in the Internet music industry. Pandora and Spotify have been equally successful in their own respects and when two big players such as Google and Apple decide to take separate stance on their approach to digital music, we now have the battle of the strategies. Only time will tell which of those will go ahead. Until then, lets enjoy the competition!

Ngrams and Google

May 17, 2013May 17, 2013 Niranjan NandakumarLeave a comment

When talking about Big Data, one initiative is worth a mention – The Google Ngrams . Google, in its on magnanimous way, started an program to digitize every single printed document, within the copyright limits back, in 2004. Started as a partnership with some of the well-known libraries around the globe such as the New York Public Library, the Harvard University Library and
Bodleian Library at University of Oxford , the plan was to make high resolution digital images of all printed documents – books magazines et al – and save them in a huge repository that is searchable through books.google. com.

As the collection grew, Google realized the potential to actually digitize them one word at a time. Through a tool known as reCAPTCHA they then started to extract every word from every single image that was scanned. What was born out of it was an amazingly large data set from words dating back to 1500. By 2012, they had almost 15% of all the printed books digitized and that amounted to almost 700 billion words! What came out of this was Google Ngrams !

An “ngram” is a sequence of letters of any length, which could be a word, a misspelling, a phrase or gibberish

Google Ngrams is a searchable word repository, which graphs the occurrence of a word or a phrase in a “corpus of books” (as Google themselves puts it). It then plots those occurrences across time and the result is a visualization of how frequent the words were used over time.

As curious as I was, I decided to try out a few of the “jargons” of today to see how far back it was used. The results were alarming!

The word “technology” (keep in mind the search is case sensitive) was used as long back as early 1500s, which is ok considering it is quite a defined term in the English dictionary. But what was even more puzzling is that the word “Internet” was used in the 1590s! Now what can that be referred to! Also, although the whole slew of ARPANET and packet switching started to evolve in the 1960s it wasn’t until 1990s when the word “Internet” started to be used widely in printed form!

Not only SQL but also ….

May 15, 2013 Niranjan NandakumarLeave a comment

Keeping with the theme of Big Data, as we spoke a couple of days back , the concept of N=all suddenly started to give rise to a whole slew of new challenges – that which is an obvious consequence of dealing with such large chunks of data. Storage and retrieval! The ability to quickly retrieve, analyze and correlate data to derive information becomes essential when it comes to dealing with big data. And for such massive amounts of data, relational databases do not seem to jive all that well. One of the major reasons for this is the fact that relational (although I may now safely call it, the traditional) databases require a structure to the data that it can store. Now when you are trying to correlate between the users’ location data Vs the local deals (as an example) and add on the users’ personal credit card usage, the data does not always fall into a structured pattern for it to be stored in a relational database. Along came NoSQL . The name was borrowed from the 1998 open source RDMS developed by Carlo Strozzi, and was later popularized by Eric Evans of Rackspace.

Unlike SQL or any of the other traditional databases, noSQL can be viewed more as a collective term for a variety of new data storage backends, with the concept of transactions taken out of it. With its eternally loose definitions, a noSQL can possibly aggregate data from rows that span across multiple tables in a traditional relational database. Now this obviously results in enormous chunks of data posing storage challenges. However with the costs associated with storage decreasing rapidly, this can be ignored when compared to the potential that you now have. Couchbase , one of those companies that have caught on quickly to this new revolution in data storage and retrieval with its document-oriented database technology, outlines an interesting article on why noSQL .

They are not the only ones that have grown into this new idea. Hadoop , is yet another one of those, that has quickly become a new household name. Developed and sustained by a group of unpaid volunteers, Hadoop is a framework to process large data sets, perhaps know as big data. Rumored to have been spun off as a free implementation of Google MapReduce , several big names have built services and solutions around this framework, some of the notable ones being Amazon Web Services (AWS), VMWare Hadoop Virtual Extensions (HVE), IBM BigInsights.

Yet another database that has been gaining popularity off late is MongoDB – a project spun off by 10Gen . Like Couchbase, this is also a document-oriented database and has started to pick up several implementations including SAP, MTV and Sourceforge.

With an “unstructured” database comes the challenges of querying it. Mongo uses a skewed version of JSON (known as BSON or Binary JSON) for representing queries whereas Couchbase has adopted a SQL-like query language that is slowly becoming a standard world wide, known as unQL (Unstructured Query Language).

While all these are still in the nascent stages of development, as the big data wave is rapidly approaching it peak, let me leave you with a slide deck from the QCon London 2013 presented by Matt Asay, VP of Corporate Strategy at 10gen on the “Past, Present and Future of noSQL.

The Past, Present, and Future of NoSQL from InfoQ

Digitizing the cash counters

May 14, 2013May 14, 2013 Niranjan NandakumarLeave a comment

I’m sure the image that you see above has become quite a familiar sight across America. Apple stores have been flaunting a similar version for quite a while now, which almost resembles the Mophie . I first noticed this at Conshohocken Cafe , a quaint little breakfast place at Conshohocken, PA. Square , as they call it, they started to make money through the 2.75% transaction fee charged per swipe. Now my post was not particularly to about the Square, but instead, the Square Stand , that was announced today. At $299 a piece and a $499 iPad, this can replace the traditional cash registers in a blink of an eye. Sounds quite simple, as we start to see more and more dependency on the mobile device .

But wait, there is more. The exact same day, Paypal decides to announce its revolutionary product know as the Cash for Register . With a free credit/debit/paypal processing for the rest of the year for any qualifying US Business, we now have a competition!

The era of cash registers which opens up a “slot machine” of quarters and pennies is slowly disappearing. Whether its paypal or square, the digital revolution has spared none. Soon the traditional cash registers will just be a piece of antique in the museum!

The new library of Alexandria – the power of Big Data

May 13, 2013 Niranjan NandakumarLeave a comment

A term that has been gaining substantial amount of curiosity in the recent past and perhaps one that would keep growing in importance as the era of Internet and the information flow starts to become more widely available, is Big Data. Although the word has been ringing all around me and my place of work for quite sometime, what really triggered my interest are two books that I am currently alternating between – “ The long Tail by Chris Anderson , a book that describes how endless choice is creating unlimited demand, and Big Data by Viktor Mayer Schonberger and Kenneth Cukier, a book that sets forth to describe the concept that would revolutionize the way we live and think.

Wikipedia defines big data as

a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications

But perhaps a more fitting definition is one that is described in the book “Big Data” – a large set of data derived from a sample size N where

N=all

. The reason I find the latter more befitting is because, data sets do not always have to be big as long as it encompasses the entire world. For e.g. the book describes a study done on the corruption in Sumo Wrestling in Japan . The study collected data from almost 65,000 matches across 7 years in Japan to find a correlation. The data in this case was not as big as one would imagine it to be. But the fact that it “surveyed” the entire set of matches across those 7 years, rather than limiting itself to certain samples from those, made me lean towards calling it a “big data”.

Big data changes the fundamental aspect of life by giving it a quantitative dimension

says Viktor and Kenneth in their book. Humans have long tried to quantify several aspects of human behavior in order to gain insights to perform predictive analysis. Now one of the terms that I used in my previous paragraph is of interesting relevance – “survey”. Surveys perhaps were one such primitive form of gathering relevant data. One of the major challenges of a survey was the fact that your sample size is now N < all, which means that you now have the data associated with the population that actually took your survey. The results then become biased to the characteristics of that limited population, which does not neccessarily portray the entirety. As this problem started to evolve, statisticians found that the results were perhaps more accurate if the sample set of the population was chose at random, rather than just increasing the sample size. Studies have shown that extrapolating the survey done on a random sample set yield a more accurate results as compared to a large sample size across a specific set of the population. Now this still does not solve one of the challenges that I'd like to call as active polling vs passive polling. In almost all cases, a survey deals with the study of a specific set of questions answered by a specific group of people or simply put, a survey is an active polling. To truly understand a human behavior, this would prove to be inaccurate especially because when answering a question, humans tend to stop and think. THis can be quite analogous to studying the human nature when interacting with a group of people, by having a tutor or a professor in the group. The mere awareness of a study being conducted could potentially skew the behavior. Whereas, if the same group of people can be "passively" observed, the information gathered can be closer to being accurate. The same can be told about any methods of predictive analysis. Big Data analysis methodologies in my view prove to be far more passive in its ways of polling data and hence tend to lean more towards being accurate.

In the coming weeks, as I wander through the world of Big Data, I plan to post more examples and insights into this amazing field that has been gaining significant relevance in today's world. I plan to talk about one aspect in each of my posts so as to limit yet another challenge of big data, known as information overload! But that does not entirely solve the problem. My plan is also to engage more interaction among my reader to gain more information, as I meander through. Feel free to enthral me with your comments.