Ramblings on Lisp

In the world of programming languages Lisp can be considered truly ancient along with its companion FORTRAN. However it has survived till this day. Lisp had its origins as early as 1958 when John McCarthy of MIT published the design of the language in an ACM paper titled “Recursive Functions of Symbolic Expressions and Their Computation by Machine". Lisp was invented by McCarthy as a mathematical notation of computer programs and is based on Lambda Calculus described by Alonzo Church in 1930.

Lisp has not had the popularity of other more recent languages like C, C++ and Java partly because it has an unfamiliar syntax and also has a very steep learning curve. The Lisp syntax can be particularly intimidating to beginners with its series of parentheses. However it is one of predominant language that is used in AI domain.

Some of the key characteristics of Lisp are
Lisp derives its name from LISt Processing. Hence while most programming languages try to compute on data, Lisp computes on a data structure namely the list. A list can be visualized as a collection of elements which can be either data or functions or lists themselves. Its power comes from the fact that the language includes in its syntax some of the operations that can be performed on a lists and lists of lists. In fact many key features of the Lisp Language have found their way into more current languages like Python, Ruby and Perl.

Second Lisp is a symbolic processing language. This ability to manipulate symbols gives Lisp a powerful edge over other Programming Languages in AI domains like theorem proving or natural language processing.

Thirdly Lisp uses a recursive style of programming. This makes the code much shorter than other languages. Recursion enables the expression of the problem as a combination of a terminating condition and a self describing sub problem. However the singular advantage that Lisp has over other programming languages is that it uses a technique called “tail recursion” . The beauty of tail recursion is that computing space is of the order of O(1) and not O(n) that is common in languages like C,C++,Java where the size of the stack grows with each subsequent recursive call.

Lisp blurs the distinction between functions and data. Functions use other functions as arguments during computations. Lisp lists are functions that operate on other functions and data in a self repeating fashion.
The closest analogy to this is to think of machine code which is sequence of 32 bit binary words. Both the logic and the data on which they operate are 32 bit binary words and cannot be distinguished unless one knows where the program is supposed to start executing. If one were to take the snapshot of consecutive memory locations we will encounter 32 bit binary words which represent either a logical or arithmetic operation on data which are also 32 bit binary words.

Lisp is a malleable language and allows the programmer to tailor the language for his own convenience. It allows the programmer to manipulate the language so that it suits the programming style of the programmer. Lisp programs evolve from the bottom-up rather from the top-down style adopted in other languages. The design methodology of Lisp programs takes an inside-out approach rather than an outside-in method.

Lisp has many eminent diehard adherents who swear by the elegance and beauty of being able to solve difficult problems concisely. On the other hand there are those to whom Lisp represents an ancient Pharaoh’s curse that is difficult to get rid of.

However with Lisp, “Once smitten, you remain smitten”.

Accelerating growth through M-Banking & M-Health

While only roughly about 5% of the population has access to computers, more than 50% of the world population has mobile phones. Mobile phones have become cheaper and are more ubiquitous these days. Hence given the penetration of mobile phones it makes sense to use them for improving the lives of those in emerging economies. Two such technologies which hold enormous potential are m-banking and m-health described below.

M-banking: Financial services, a key driver for economic growth, is either negligible or completely absent in remote rural areas. Regular banking services are unviable in these areas. The small deposits and loans held by the rural poor make it unprofitable for traditional banks to operate in these areas through traditional delivery methods. In these areas m-banking is truly a god send.

M-Banking refers to financial services offered by Service Providers to the unbanked poor in rural areas. The people in these villages can purchase either pre-paid or post-paid units from the Operator. They can then use these units to pay for goods and services. M-Banking offers a safe and secure method to the unbanked poor for sending and receiving payments through SMS’es. To make m-banking a reality, requires the coming together of the 3 major players namely the Service Provider, the Application developer and the financial institution which can regulate and disburse units of money.

A recent report by McKinsey with GSMA in 147 countries shows that more than 1.7 billion people in emerging economies will have a mobile phone without access to banking services. The McKinsey reports also states that by 2012 the opportunity in m-banking would generate $5 billion annually in direct revenue from financial transactions and $3 billion in indirect revenue through reduced customer churn and higher ARPU for traditional voice and SMS services.

Some examples of success are M-Pesa of Kenya, Wizzit in South Africa and Globe in Philippines. M-banking provides a 24x7 service in the village and does not require any complicated infrastructure. One could imagine services where the unbanked poor could receive instant payment for the farm produce, could save money on a regular basis and pay for electricity bills instantaneously through SMS. This will increase both the sense of security and personal well being.

M-banking provides for tremendous socio-economic growth in the villages. With the increasing penetration and the ubiquity of mobile phones m-banking represents a sure-shot way of ensuring all round economic transformation in the villages. M-banking helps in reducing risk and brings true convenience to financial transactions. However, appropriate authentication and authorization procedures should be used.
Mobile banking does not need expensive infrastructure that is required of banks, the network of ATMs for depositing and withdrawal of money. M-banking is convenient, secure, easy to use and can be quickly deployed. While the Service Providers are the facilitators of m-banking, it is the financial institutions that will regulate and provide banking facility to the unbanked poor.
Hence m-banking is a complete win-win situation for the all the players involved namely the CSPs, the financial institutions and the unbanked poor. Besides providing convenience, m-banking will be a key driver for all round economic growth in the villages.

M-Health: Another companion technology which has enormous potential in emerging markets is m-health. M-health relates to the provision of health services in rural areas where there is an acute shortage of qualified health workers. In these areas the use of mobile communication can help in addressing key health needs of the poor, thanks to the explosive growth of mobile phones in these areas.

Some of the key benefits of m-health is the ability to spread timely health related information and diagnoses to the health workers in the villages enabling the ability to quickly track and contain the spread of diseases and epidemics. Other applications include remote data collection and monitoring of health related issues.
Recent estimates indicate that half of the population in remote areas will have a mobile phone by 2012. This provides inmates in even the remote villages’ instant access to the important health related information’s-health along with m-banking can allow Health organizations to transfer funds which the needy can use for performing health checkups.

Like m-banking SMS is a key enabler of m-health. SMS’es can be sent to educate and spread awareness of diseases, transfer funds and for informing the availability of health services. Health workers can mobile phones or PDAs to collect and send disease related data.

M-health also provides a unique opportunity for Service Providers, Health institutions, insurance companies and the patients themselves.

Conclusion: With the increasing penetration of mobiles both m-banking and m-health are particularly relevant today. Both these technologies are capable of not only transforming the economic landscape but also providing the CSPs, financial and health institutions with a sound business and strategic advantage.

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Singularity

A short science fiction story.

Pete Mettle felt drowsy. He had been working for days on his new inference algorithm. Pete had been in the field of Artificial Intelligence (AI) for close to 3 decades and had established himself as the father of "semantics". He was particularly renowned for his 3 principles of Artificial Intelligence. He had postulated the Principles of Learning as

The Principle of Knowledge Acquisition: This principle laid out the guidelines for knowledge acquisition by an algorithm. It clearly laid out the rules of what was knowledge and what was not. It could clearly delineate between the wheat and chaff from any textbook or research article.

The Principle of Knowledge Assimilation: This law gave the process for organizing the acquired knowledge in facts, rules and underlying principles. Knowledge assimilation involved storing the individual rules, the relation between the rules and provided the basis for drawing conclusions from them

The Principle of Knowledge Application: This principle according to Pete was the most important. It showed how all knowledge acquired and assimilated could be used to draw inferences andconclusions. In fact it also showed how knowledge could be extrapolated to make safe conclusions.

Zengine The above 3 principles of Pete were hailed as a major landmark in AI. Pete started to work on an inference engine known as "Zengine" based on his above 3 principles. Pete was almost finished fine tuning his algorithm. Pete wanted to test his Zengine on the World Wide Web. The World Wide Web had grown into gigantic proportions. A report in May 2025 issue of Wall Street Journal mentioned that the total data that was held in the internet had crossed 400 zettabytes and that the daily data stored on the web was close to 20 terabytes. It was a well known fact that there an enormous amount of information on the web on a wide variety of topics. Wikis, blogs, articles, ideas, social networks and so on there was a lot of information on almost every conceivable topic under the sun.

Pete was given special permission by the governments of the world to run his Zengine on the internet. It was Pete's theory that it would take the Zengine close to at least a year to process the information on the web and make any reasonable inferences from them. Accompanied by world wide publicity Zengine started its work of trying to assimilate the information on the World Wide Web. The Zengine was programmed to periodically give a status update of its progress to Pete.

A few months passed. Zengine kept giving updates on the number of sites, periodicals, blogs it had condensed into its knowledge database. After about 10 months Pete received a mail. It read "Markets will crash on March 2026. Petrol prices will sky rocket - Zengine. Pete was surprised at the forecast. So he invoked the API to check on what basis the claim had been made. To his surprise and amazement he found that a lot events happening in the world had been used to make that claim which clearly seemed to point in that direction. A couple of months down the line there was another terse statement "Rebellion very likely in Mogadishu in Dec 2027". - Zengine.The Zengine also came with corollaries to Fermat's last theorem. It was becoming clear to Pete and everybody that the Zengine was indeed becoming smarter by the day..It became apparent to everybody when Zengine would become more powerful than human beings.

Celestial events: Around this time peculiar events were observed all over the world. There were a lot of celestial events that were happening. Phenomenon like the aurora borealis became common place. On Dec 12, 2026 there was an unusual amount of electrical activity in the sky. Everywhere there were streaks of lightning. By evening time slivers of lightning hit the earth in several parts of the world. In fact if anybody had viewed the earth from outer space then it would have a resembled a "nebula sphere" with lightning streaks racing towards the earth in all directions. This seemed to happen for many days. Simultaneously the Zengine was getting more and more powerful. In fact it had learnt to spawn of multiple processes to get information and return to it.

Time-space discontinuity: People everywhere were petrified of this strange phenomenon. On the one hand there was the fear of the takeover of the web by the Zengine and on the other was this increased celestial activity. Finally on the morning of Jan 2028 there was a powerful crack followed by a sonic boom and everywhere people had a moment of discontinuity. In the briefest of moments there was a natural time-space discontinuity and mankind had progressed to the next stage in evolution.

The unconscious, sub conscious and the conscious all became a single faculty of super consciousness. It has always been known from the time of Plato that man knows everything there is to know. According to Platonic doctrine of Recollection, human beings are born with a soul possessing all knowledge, and learning is just discovering or recollecting what the soul already knows. Similarly according to Hindu philosophy, behind the individual consciousness of the Atman, is the reality known as the Brahman which is universal consciousness attained in a deep state of mysticism through self-inquiry.

However this evolution by some strange quirk of coincidence seemed to coincide with the development of the world's first truly learning machine. In this super conscious state a learning machine was not something to be feared but something which could be used to benefit mankind. Just like cranes can lift and earthmovers perform tasks that are beyond our physical capacity so also a learning machine was a useful invention that could be used to harness the knowledge from mankind's storehouse - the World Wide Web.

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Programming languages in layman's language

There is such a wide variety of programming languages that there is always confusion as to why there is such a profusion of languages. Different programming languages solve different classes of problems. Programming languages can be classified broadly into the following 4 classes.

Procedural Languages: In these languages one thinks in terms of the sequence of steps to solve the problem. It could be thought of solving the problem in 1st person and then substituting the “I” with “the program”. So for example in procedural language we could think

I will wake up.
I will brush my teeth
I will open fridge
I will take milk
I will warm milk

So in procedural languages actions are performed sequentially to achieve the desired end result.
Examples: FORTRAN, BASIC, Pascal, C

Object Oriented (OO) Languages: When a problem is solved using Object Oriented techniques we look at the world objectively. So we need to first identify the participants and functions performed by each of these participants. So the above situation would be viewed as

I, Fridge, Microwave - Participants

then we need look at what functions the above 3 will perform
I – wake up, brush
Fridge – Open door, close door
Microwave – Warm

Hence in OO languages the problem is solved as the interaction of functions between participating objects.
Examples: C++, Java, Smalltalk, C#

Both procedural and OO languages are compiled languages and are also known as “Imperative Languages”. A useful analogy is to view compiled programs as mashed, pre-cooked food that can be easily assimilated by the digestive system or the raw hardware.

Dynamic Languages: Here these languages are either interpreted or converted to byte code. Interpreted languages are similar to raw & uncooked food which must be crunched, munched and digested on the fly. However these languages include in themselves many, many features that are commonly used. While the first two would just specify the method, dynamic languages include several specific features as functionalities. To use an analogy while in the above 2 programming language types one would set the time and the power level for each item to heat in a microwave, dynamic languages come with readymade buttons for those frequently used.
I – wake up, sleep, eat, drink, wash etc
Fridge – Cool, refrigerate, thaw, and freeze
Microwave – Heat popcorn, frozen food, meat etc

Since you get a lot of stuff for free and the program is interpreted on the fly Dynamic Languages take a lot more time
Examples: Perl, Python, Ruby

Functional languages: Here we think in terms of functions that are performed on items. They can be performed on
any object.
For example the above problem would be viewed as the following main functions
E.g. Wake, sleep, warm, thaw, heat, cool, freeze.
We then take and apply the function ‘warm’ on the ‘milk’
Heat on ‘vegetables’ etc
In Functional Programming functions invoke other functions to accomplish a task. The problem is solved from the inside-out. In Functional languages like Lisp one starts with some core functions and build layers over it. For e.g. in a functional language we would express calorific energy as

metabolize (assimilate (digest (chew (food))))

Examples: Lisp, Clojure, Haskell, Erlang

Each language is best suited for only certain applications. So just like it is inappropriate to use pliers where an Allen wrench would suffice we need to know which language is most suitable. If we know what the class the problem is and the performance we want we can choose the appropriate language

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Mobile Smartphones - The New Swiss Knife

Published in Technorati - Mobile Smartphones - The new Swiss Knife

The humble mobile phone from its early avatar of enabling voice calls has now metamorphosed into a device which can perform multiple functions. The mobile smart phone is the new Swiss knife. From making voice calls, to watching video clips, from mobile TV to Location Based Services (LBS) the uses of the mobile phone are many.The mobile phone is both ubiquitous and almost indispensable to daily life. A look at some of key technologies which will still further the utility of the mobile phones are discussed below.

Mobile banking: Bringing the bank to the mobile: Mobile banking is a trend that is just picking up. Mobile banking provides for the banking needs for the poor who have no access to banks and has a lot of potential for growth. Mobile banking refers to a method where the rural poor can make payments and do cash transactions through simple SMS text messages. Mobile banking is crucial in emerging markets where traditional banks are not viable. A recent McKinsey Report 2010 states that the though the number of mobile phones in emerging markets is in excess of 1 billion, only about 45 million use mobile money in the place of traditional banking. The report further states that opportunity in mobile banking is about 3 billion annually.
Mobile banking requires the interworking of telecom operators, application providers and cash agents for making this service a reality. Mobile banking can promote customer growth and reduce churn for service providers. Some success stories are M-Pesa in Keya and SmartMoney in Philippines. There is a tremendous opportunity for this application in countries like India and China and other emerging markets. In this application, the mobile phone helps the user to bank while on the move.

Near Field Communication (NFC): Mobile phones enabled with NFC technology can be used for a variety of purposes. One such purpose is integrating credit card functionality into mobile phones using NFC. Already the major players in mobile are integrating NFC into their newer versions of mobile phones including Apple’s iPhone, Google’s Android, and Nokia. We will never again have to carry in our wallets with a stack of credit cards. Our mobile phone will double up as a Visa, MasterCard, etc. NFC also allows retail stores to send promotional coupons to subscribers who are in the vicinity of the shopping mall.

E-Ticketing: With an application, our flight iternary, tickets or movie tickets will be sent to the mobile phone. E-Ticketing can also be used for train and bus rides and does away with the need to carry small change.

Some of the key applications envisaged for the mobile phone in the future has been discussed and many are already in use. The smartphone will not only be indispensable in future but will be omnipotent and omniscient.

Technology Trends - 2011 and beyond

There are lots of exciting things happening in the technological landscape. Innovation and development in every age is dependent on a set of key driving factors namely – the need for better, faster and cheaper, the need to handle disruptive technologies, the need to keep costs down and the need to absorb path breaking innovations. Given all these factors and the current trends in the industry the following technologies will enter mainstream in the years to come.

Long Term Evolution (LTE): LTE, also known as 4G technologies, has been born out of the disruptive entry of data hungry smart phones and tablet PCs. Besides, the need for better and faster applications has been the key driver of this technology. LTE is a data only technology that allows mobile users to access the internet on the move. LTE uses OFDM technology for sending and receiving data from user devices and also uses MIMO (multiple-in, multiple out). LTE is more economical, and spectrally efficient when compared to earlier 3.5G technologies like HSDPA, HSUPA and HSPA. LTE promises a better Quality of Experience (QoE) for end users.
IP Multimedia Systems IMS): IMS has been around for a while. However with the many advances in IP technology and the transport of media the time is now ripe for this technology to take wings and soar high. IMS uses the ubiquitous internet protocol for its core network both for media transport and for SIP signaling. Many innovative applications are possible with IMS including high definition video conferencing, multi-player interactive games, white boarding etc.
All senior management personnel of organizations are constantly faced with the need to keep costs down. The next two technologies hold a lot of promise in reducing costs for organizations and will surely play a key role in the years to come.

Cloud Computing: Cloud Computing obviates the need for upfront capital and infrastructure costs of organizations. Enterprises can deploy their applications on a public cloud which provides virtually infinite computing capacity in the hands of organizations. Organizations only pay as much as they use akin to utilities like electricity or water
Analytics: These days’ organizations are faced with a virtual deluge of data from their day to day operations. Whether the organizations belong to retail, health, finance, telecom, or transportation there is a lot of data that is generated. Data by itself is useless. This is where data analytics plays an important role. Predictive analytics help in classifying data, determining key trends and identifying correlations between data. This helps organizations in making strategic business decisions.

The following two technologies listed below are really path breaking and their applications are limitless.

Internet of Things: This technology envisages either passive or intelligent devices connected to the internet with a database at the back end for processing the data collected from these intelligent devices. This is also known as M2M (machine to machine) technology. The applications range from monitoring the structural integrity of bridges to implantable devices monitoring fatal heart diseases of patients.
Semantic Web (Web 3.0): This is the next stage in the evolution of the World Wide Web. The Web is now a vast repository of ideas, thoughts, blogs, observations etc. This technology envisages intelligent agents that can analyze the information in the web. These agents will determine the relations between information and make intelligent inferences. This technology will have to use artificial intelligence techniques, data mining and cloud computing to plumb the depths of the web

Conclusion: Creativity and innovation has been the hallmark of mankind from time immemorial. With the demand for smarter, cheaper and better the above technologies are bound to endure in the years to come.

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The Future of Telecom

Introduction: The close of the 20th century will long be remembered for one thing. The dotcom bust followed by the downward spiral of many major telecom and technology companies. For those who believe in the theory of the 12 year economic cycle this downturn is right about to end and we should see good times soon. Even otherwise there is good news for those in the telecom domain. We could shortly be witness to golden years ahead. There are many signs that seem to indicate that the telecom industry is on the verge of many major breakthroughs. Technologies like LTE, IMS, smartphones, cloud computing point to interesting times ahead. In fact telecom is at a inflexion point when the fortunes seem to be pointed northward. This article looks at some of the promising technologies which are going to bring back the sunshine to telecom.

3G Technologies –Better Quality of Experience (QoE): The auction of the 3G spectrum ended after 131 days of hectic bidding for this cutting edge telecom technology. 3G promises a whole new customer experience backed by extremely high data speeds. 3G promises download speed of up to 2 Mbps for stationary subscribers and 384 Kbps for moving subscribers. It is very clear that such high data speeds will inspire a host of new and exciting applications. Applications that span location based services (LBS), m-Commerce and NFC communications will be simply be irresistible to the users. Moreover the ability to watch video clips or live action on mobile TV or on laptops enabled with 3G dongles will have a lot of takers for 3G technology. App stores for 3G are bound to do a roaring business as 3G takes off in India.

Smartphones – The game changers: In the last decade or so in the telecom industry no other invention has had such a disruptive effect in the telecom domain as smartphones. Smartphones like the IPhone, Droid or Nexus One have changed the rules of the game. The impact of smartphone has been so huge that it actually spawned an entire industry of developers who developed applications for smartphones, content developers and app stores. The irresistible appeal of smartphones is the ease of use and the ability to browse the net as though they were using a normal data connection. Users can watch youtube clips, play games or chat on the Smartphone.

IP Multimedia Systems (IMS) – Digital Convergence: IP Multimedia System (IMS) , based on 3GPP’s Release 5 Specification in 2005, has been in the wings for quite some time. The IMS envisions an access agnostic telecommunication architecture that will use an all-IP Core for the transport of medium be it voice, data or video. IMS uses SIP protocol for signaling between network elements and SDP for exchanging media between applications. The IMS architecture promises a whole slew of exciting application ranging from high quality video conference, high speed data access, white boarding or real time interactive gaining. IMS represents a true convergence of the telecom wireless concepts with the data communication protocols. The types of services that are possible with IMS will be only limited by imagination. With the entry of smartphones and tablet PCs, IMS is a technology that is waiting to happen and will soon become prime time

Long Term Evolution (LTE) - Blazing Speeds: Already there are upward of 5 billion mobile devices and a report from Cisco states that the total data navigating the net will exceed ½ a zettabyte (1021) by the year 2013. The exponential growth of data and the need to provide even higher Quality of Experience (QoE) led to the development of the LTE. LTE is considered 4G technology. LTE promises speeds anywhere between to 56 Mbps to 100 Mbps to users enabling unheard of speeds and applications. What makes LTE so attractive is that it promises better spectral efficiency and lower cost per bit than 3G networks. The competing technology for LTE is WIMAX which is also considered as 4G. But LTE has a better evolution path from 3G networks as opposed to WiMAX, While LTE is a packet only network there are sound strategies for handling voice traffic with LTE. The standards body 3GPP offers two options for handling voice. The first is the Circuit switched (CS) fallback to 2G/3G network. In this scenario data access will be through the packet network of LTE while voice calls will use legacy 2G/3G voice networks. The other alternative is the switch voice traffic to the IMS network with its all-IP Core. This method is supported by the One Voice initiative of many major telecom companies and accepted by GSMA. This strategy for handling voice through an IMS network is known as VoLTE (Voice over LTE)

Internet of Things- Towards a connected World: “The Internet of Things" visualizes a highly interconnected world made of tiny passive or intelligent devices that connect to large databases and to the internet. This technology promises to transform the network from a dumb-bit pipe to a truly "computing" network. The Internet of Things or M2M (machine-to-machine) envisages an anytime, anywhere, anyone, anything network. The devices in this M2M network will be made up of passive elements, sensors and intelligent devices that communicate with the network. The devices will be capable of sensing, identifying and responding to changes in the immediate environment. Radio Frequency Identification (RFIDs) is one of the early and key enabler of this technology. The uses for this technology range from warning when the structural integrity of bridges is compromised to implantable devices in heart patients warning doctors of possible heart attacks. The impact of the Internet of Things will be far-reaching. There are numerous applications for this technology. In fact, ubiquitous computing or the Internet of Things allows us to distribute processing power and intelligence throughout the network into a kind of ambient intelligence spread across the network. This technology promises to blur the lines between science fiction and reality.

App Stores – The final verdict: The success of App Stores in the last couple of years has been nothing short of phenomenal. It is a complete ecosystem with App Store Developers, App Stores, and the Content Developers and Service Providers. Apps and App stores have changed the rules of the game so completely. No longer is a mobile phone’s snazzy looks enough for it to be a best seller. The mobile should be supported by cool downloadable apps for the user to use. App Stores and apps will play an increasingly important role with apps being developed for smartphones and tablet PCs. There are bound to be several interesting apps spanning technologies like Location Based Service (LBS), mobile Commerce, eTicketing, Near Field Communication

Cloud Computing – Utility computing: Cloud Computing has been around some but is slowly gaining more and more prominence. Cloud computing follows a utility model for computing where the cloud user only pays for the computing power and storage capacity used. Cloud computing not involve any upfront Capacity expenditure (Capex). Users of public clouds like EC2, App Engine or Azure can pay according to the usage of the resources provided by the cloud. Cloud technologies allow the CSPs to purchase processing power, platforms, and databases almost like a utility like electricity or water. The cloud exhibits an elastic behavior and expands to accommodate increasing demands and contracts when the demand drops. Cloud computing will be slowly be adopted by more and more organizations and enterprises in the years to come.

Analytics – Mining intelligence from data: Nowadays organizations all over are faced with a deluge of data. For raw data to be useful it has been analyzed, classified and important patterns determined from the data. This is where data mining and analytics come into play. Analytics uses statistical methods to classify data, determine correlations, identify patterns, and highlight and detect key trends among large data sets. Analytics enables industries to plumb the data sets through the process of selecting, exploring and modeling large amount of data to uncover previously unknown data patterns. The insights which analytics provides can be channelized to business advantage. Data mining and predictive analytics unlock the hidden secrets of data and help businesses make strategic decisions. Analytics is bound to become more common and will play a predominant role in all organizations in the years to come.

Internet TV – Hot off the net: If IMS represents the convergence of Telecom and the internet, Internet TV represents the marriage of TV and the internet. Internet TV is a technology whose time has come. Internet TV will bring a whole new user experience by allowing the viewer to be view rich content on his TV in an interactive manner. The technology titans like Apple, Microsoft and Google have their own version of this technology. Internet TV combines TV, the internet and apps for this new technology. Internet TV is bound to become popular with complementary technologies like IMS, LTE allowing for high speed data exchange and the popularity of websites like Youtube etc. Internet TV will receive a further boost from apps of smartphones and tablet PCs

IPv4 exhaustion – Damocles’ sword: While the future holds the promise of many new technologies it is also going throw a lot of attendant challenges. One serious problem that will need serious attention in the not too distant future is the IPv4 address space exhaustion. This problem may be even more serious than the Y2K problem. The issue is that IPv4 can address only 2 32 or 4.3 billion devices. Already the pool has been exhausted because of new technologies like IMS which uses an all IP Core and the Internet of things with more devices, sensors connected to the internet - each identified by an IP address. The solution to this problem has been addressed long back and requires that the Internet adopt IPv6 addressing scheme. IPv6 uses 128-bit long address and allows 3.4 x 1038 or 340 trillion, trillion, trillion unique addresses. However the conversion to IPv6 is not happening at the required pace and pretty soon will have to be adopted on war footing. It is clear that while the transition takes place, both IPv4 and IPv6 will co-exist so there will be an additional requirement of devices on the internet to be able to convert from one to another

Conclusion:
Technologies like IMS, LTE, and Internet TV have a lot of potential and hold a lot of promise. We as human beings have a constant need for better, faster and cheaper technologies. We can expect a lot of changes to happen in the next couple of years. We may once see rosy times ahead for telecom as a whole

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Singularity

Published in Associated Content

Pete Mettle felt drowsy. He had been working for days on his new inference algorithm. Pete had been in the field of AI for close to 3 decades and had established himself as the father of "semantics". He was particularly renowned for his 3 principles of Artificial Intelligence. He had postulated the principles of learning as
The Principle of Knowledge Acquisition: This principle laid out the guidelines for knowledge acquisition by an algorithm. It clearly laid out the rules of what was knowledge and what was not. It could clearly delineate between the wheat and chaff from any textbook or research article.

The Principle of Knowledge Assimilation: This law gave the process for organizing the acquired knowledge in facts, rules and underlying principles. Knowledge assimilation involved storing the individual rules, the relation between the rules and provided the basis for drawing conclusions from them

The Principle of Knowledge Application: This principle according to Pete was the most important. It showed how all knowledge acquired and assimilated could be used to draw inferences andconclusions. In fact it also showed how knowledge could be extrapolated to make safe conclusions.

Zengine The above 3 principles of Pete were hailed as a major landmark in AI. Pete started to work on an inference engine known as "Zengine" based on his above 3 principles. Pete was almost finished fine tuning his algorithm. Pete wanted to test his Zengine on the World Wide Web. The World Wide Web had grown into gigantic proportions. A report in May 2025 issue of Wall Street Journal mentioned that the total data that was held in the internet had crossed 400 zettabytes and that the daily data stored on the web was close to 20 terabytes. It was a well known fact that there an enormous amount of information on the web on a wide variety of topics. Wikis, blogs, articles, ideas, social networks and so on there was a lot of information on almost every conceivable topic under the sun.

Pete was given special permission by the governments of the world to run his Zengine on the internet. It was Pete's theory that it would take the Zengine close to at least a year to process the information on the web and make any reasonable inferences from them. Accompanied by world wide publicity Zengine started its work of trying to assimilate the information on the World Wide Web. The Zengine was programmed to periodically give a status update of its progress to Pete.

A few months passed. Zengine kept giving updates on the number of sites, periodicals, blogs it had condensed into its knowledge database. After about 10 months Pete received a mail. It read "Markets will crash on March 2026. Petrol prices will sky rocket - Zengine. Pete was surprised at the forecast. So he invoked the API to check on what basis the claim had been made. To his surprise and amazement he found that a lot events happening in the world had been used to make that claim which clearly seemed to point in that direction. A couple of months down the line there was another terse statement "Rebellion very likely in Mogadishu in Dec 2027". - Zengine.The Zengine also came with corollaries to Fermat's last theorem. It was becoming clear to Pete and everybody that the Zengine was indeed becoming smarter by the day..It became apparent to everybody when Zengine would become more powerful than human beings.

Celestial events: Around this time peculiar events were observed all over the world. There were a lot of celestial events that were happening. Phenomenon like the aurora borealis became common place. On Dec 12, 2026 there was an unusual amount of electrical activity in the sky. Everywhere there were streaks of lightning. By evening time slivers of lightning hit the earth in several parts of the world. In fact if anybody had viewed the earth from outer space then it would have a resembled a "nebula sphere" with lightning streaks racing towards the earth in all directions. This seemed to happen for many days. Simultaneously the Zengine was getting more and more powerful. In fact it had learnt to spawn of multiple processes to get information and return to it.

Time-space discontinuity: People everywhere were petrified of this strange phenomenon. On the one hand there was the fear of the takeover of the web by the Zengine and on the other was this increased celestial activity. Finally on the morning of Jan 2028 there was a powerful crack followed by a sonic boom and everywhere people had a moment of discontinuity. In the briefest of moments there was a natural time-space discontinuity and mankind had progressed to the next stage in evolution.

The unconscious, sub conscious and the conscious all became a single faculty of super consciousness. The knowledge of nature now became clear. It has always been known from the time of Plato that man knows everything there is to know. According to Plato the soul already has all knowledge and learning is just discovering what the soul already knows. It is all buried in the unconscious mind. In the Hindu philosophy it is also known as the Brahman which is universal consciousness and can only be attained in a deep state of mysticism through self-inquiry.

However this evolution by some strange quirk of coincidence seemed to coincide with the development of the world's first truly learning machine. In this super conscious state a learning machine was not something to be feared but something which could be used to benefit mankind. Just like cranes can lift and earthmovers perform tasks that are beyond our physical capacity so also a learning machine was a useful invention that could be used to harness the knowledge from mankind's storehouse - the World Wide Web.

Netelligence

Published in Associated Content
The Internet - Web of information: No invention has had such a enormous impact in our lives as the internet". Now the world's information and knowledge are stored and accessed on this wonderful invention. Getting information on any topic is like participating in a lucky dip. Enter your search items in a search engine and presto - the screen comes up all relevant and related content. In fact the internet has steadily grown over the years and holds encyclopedias, ideas, thoughts and endless insights and observations of mankind.
Netelligence: In fact , we have almost reached a point , where it is almost impossible to fathom the amount of information and knowledge that is available on the web. If only, we the human race, can harness this information and knowledge on the web we can make great progress. There is a need to tap the "netelligence" of the world wide web. For this we need to have specifically designed programs that can scour the web for the knowledge, ideas and insights.The programs would have to be based on complex algorithms, artificial intelligence techniques, data mining and analytics. The programs would have to assimilate information, identify patterns, ask itself relevant questions search for answers and draw appropriate conclusions from it.. Such algorithms that can mine the netelligence from the web will have to identify , correlate, associate and validate its owns findings. These "migratory netelligent" programs will have at their disposal a real wealth of information on the web. From social networking sites to blogs, from encyclopedias' to research articles, from history to philosophy mankind has recorded all his experiences, desires and dreams. There is more wisdom in the web than we can comprehend.

Harnessing wisdom: While such a "migratory netelligent" program almost seem the stuff of science fiction, it definitely is not impossible based on the advances in computer science. The time is now ripe for such a advancement as the content of the web has almost reached a critical mass and algorithms are getting more sophisticated. Mankind does not have to wait for divine inspiration to come to make the next big breakthrough. The web has more intelligence than we are aware of. In fact the web is a man-made artificial resource. If only we could tap this "artificial resource" mankind may witness the next great advancement in science. In the 21st century and beyond the collective wisdom of the human race, in the billions of servers comprising the web, will be the most crucial resource for mankind.

Net gold: In fact the insights that netelligent programs discover from the web can be referred to as "net gold"

The rise of analytics

Published in The Hindu, Nov 10,2010 - http://bit.ly/d2GBXp

We are slowly, but surely, heading towards the age of “information overload”. The Sloan Digital Sky Survey started in the year 2000 returned around 620 terabytes of data in 11 months — more data than had ever been amassed in the entire history of astronomy.

The Large Hadron Collider (LHC) at CERN, Europe's particle physics laboratory, in Geneva will during its search for the origins of the universe and the elusive Higgs particle, early next year, spew out terabytes of data in its wake. Now there are upward of five billion devices connected to the Internet and the numbers are showing no signs of slowing down.

A recent report from Cisco, the data networking giant, states that the total data navigating the Net will cross 1/2 a zettabyte (10 {+2} {+1}) by the year 2013.

Such astronomical volumes of data are also handled daily by retail giants including Walmart and Target and telcos such as AT&T and Airtel. Also, advances in the Human Genome Project and technologies like the “Internet of Things” are bound to throw up large quantities of data.

The issue of storing data is now slowly becoming non-existent with the plummeting prices of semi-conductor memory and processors coupled with a doubling of their capacity every 18 months with the inevitability predicted by Moore's law.

Plumbing the depths

Raw data is by itself quite useless. Data has to be classified, winnowed and analysed into useful information before if it can be utilised. This is where analytics and data mining come into play. Analytics, once the exclusive preserve of research labs and academia, has now entered the mainstream. Data mining and analytics are now used across a broad swath of industries — retail, insurance, manufacturing, healthcare and telecommunication. Analytics enables the extraction of intelligence, identification of trends and the ability to highlight the non-obvious from raw, amorphous data. Using the intelligence that is gleaned from predictive analytics, businesses can make strategic game-changing decisions.

Analytics uses statistical methods to classify data, determine correlations, identify patterns, and highlight and detect deviations among large data sets. Analytics includes in its realms complex software algorithms such as decision trees and neural nets to make predictions from existing data sets. For e.g. a retail store would be interested in knowing the buying patterns of its consumers. If the store could determine that product Y is almost always purchased when product X is purchased then the store could come up with clever schemes like an additional discount on product Z when both products X & Y are purchased. Similarly, telcos could use analytics to identify predominant trends that promote customer loyalty.

Studying behaviour

Telcos could come with voice and data plans that attract customers based on consumer behaviour, after analysing data from its point of sale and retail stores. They could use analytics to determine causes for customer churn and come with strategies to prevent it.

Analytics has also been used in the health industry in predicting and preventing fatal infections in infants based on patterns in real-time data like blood pressure, heart rate and respiration.

Analytics requires at its disposal large processing power. Advances in this field have been largely fuelled by similar advances in a companion technology, namely cloud computing. The latter allows computing power to be purchased on demand almost like a utility and has been a key enabler for analytics.

Data mining and analytics allows industries to plumb the data sets that are held in the organisations through the process of selecting, exploring and modelling large amount of data to uncover previously unknown data patterns which can be channelised to business advantage.

Analytics help in unlocking the secrets hidden in data and provide real insights to businesses; and enable businesses and industries to make intelligent and informed choices.

In this age of information deluge, data mining and analytics are bound to play an increasingly important role and will become indispensable to the future of businesses.