Analytics, Machine Learning, AI and Automation

In the last few years buzzwords such as Machine Learning (ML), Deep Learning (DL), Artificial Intelligence (AI) and Automation have taken over from the excitement of Analytics and Big Data.

Often ML, DL and AI are placed in the same context especially in product and job descriptions. This not only creates confusion as to the end target, it can also lead to loss of credibility and wasted investment (e.g. in product development).

Figure 1: Framework for Automation

Figure 1 shows a simplified version of the framework for automation. It shows all the required ingredients to automate the handling of a ‘System’. The main components of this framework are:

  1. A system to be observed and controlled (e.g. telecoms network, supply chain, trading platform, deep space probe …)
  2. Some way of getting data (e.g. telemetry, inventory data, market data …) out of the system via some interface (e.g. APIs, service endpoints, USB ports, radio links …) [Interface <1> Figure 1]
  3. A ‘brain’ that can effectively convert input data into some sort of actions or output data which has one or more ‘models’ (e.g. trained neural networks, decision trees etc.) that contain its ‘understanding’ of the system being controlled. The ‘training’ interface that creates the model(s) and helps maintain them, is not shown separately
  4. Some way of getting data/commands back into the system to control it (e.g. control commands, trade transactions, purchase orders, recommendations for next action etc.) [Interface <2> Figure 1]
  5. Supervision capability which allows the ‘creators’ and ‘maintainers’ of the ‘brain’ to evaluate its performance and if required manually tune the system using generated data [Interface <3> Figure 1] – this itself is another Brain (see Recursive Layering)

This is a so called automated ‘closed-loop’ system with human supervision. In such a system the control can be fully automated, only manual or any combination of the two for different types of actions. For example, in safety critical systems the automated closed loop can have cut out conditions that disables Interface <2> in Figure 1. This means all control passes to the human user (via Interface <4> in Figure 1).

A Note about the Brain

The big fluffy cloud in the middle called the ‘Brain’ hides a lot of complexity, not in terms of the algorithms and infrastructure but in terms of even talking about differences between things like ML, DL and AI.

There are two useful concepts to use when trying to put all these different buzzwords in context when it comes to the ‘Brain’ of the system. In other words next time some clever person tells you that there is a ‘brain’ in their software/hardware that learns.. ask them two questions:

  1. How old is the brain?
  2. How dense is the brain?

Age of the Brain

Age is a very important criteria in most tasks. Games that preschool children struggle with are ‘child’s play’ for teenagers. Voting and driving are reserved for ‘adults’. In the same way for an automated system the age of the brain talks a lot about how ‘smart’ it is.

At its simplest a ‘brain’ can contain a set of unchanging rules that are applied to the observed data again and again [so called static rule based systems]. This is similar to a new born baby that has fairly well defined behaviours (e.g. hungry -> cry). This sort of a brain is pretty helpless in case the data has large variability. It will not be able to generate insights about the system being observed and the rules can quickly become error prone (thus the age old question – ‘why does my baby cry all the time!’).

Next comes the brain of a toddler which can think and learn but in straight lines and that too after extensive training and explanations (unless you are a very ‘lucky’ parent and your toddler is great at solving ‘problems’!). This is similar to a ‘machine learning system’ that is specialised to handle specific tasks. Give it a task it has not trained for and it falls apart.

Next comes the brain of a pre-teen which is maturing and learning all kinds of things with or without extensive training and explanations. ‘Deep learning systems’ have similar properties. For example a Convolutional Neural Network (CNN) can extract features out of a raw image (such as edges) without requiring any kind of pre-processing and can be used on different types of images (generalisation).

At its most complex, (e.g. a healthy adult) the ‘brain’ is able to not only learn new rules but more importantly evaluates existing rules for their usefulness. Furthermore, it is capable of chaining rules, applying often unrelated rules to different situations. Processing of different types of input data is also relatively easy (e.g. facial expressions, tone, gestures, alongside other data). This is what you should expect from ‘artificial intelligence‘. In fact with a true AI Brain you should not need Interface <4> and perhaps a very limited Interface <3> (almost a psychiatrist/psycho-analyst to a brain).

Brain Density

Brain density increases as our age increases and then stops increasing and starts to decrease. From a processing perspective its like the CPU in your phone or laptop starts adding additional processors and therefore is capable of doing more complex tasks.

Static rule-based systems may not require massive computational power. Here more processing power may be required for <1>/<2>. to prepare the data for input and output.

Machine-learning algorithms definitely benefit from massive computational powers especially when the ‘brain’ is being trained. Once the model is trained however, the application of the model may not require computing power. Again more power may be required to massage the data to fit the model parameters than to actually use the model.

Deep-learning algorithms require computational power throughout the cycle of prep, train and use. The training and use times are massively reduced when using special purpose hardware (e.g. GPUs for Neural Networks). One rule of thumb: ‘if it doesn’t need special purpose hardware then its probably not a real deep-learning brain, it may simply be a machine learning algorithm pretending to be a deep-learning brain’. CPUs are mostly good for the data prep tasks before and after the ‘brain’ has done its work.

Analytics System

If we were to have only interfaces <1> and <3> (see Figure 1) – we can call it an analytics solution. This type of system has no ability to influence the system. It is merely an observer. This is very popular especially on the business support side. Here the interface <4> may not be something tangible (such REST API or a command console) all the time. Interface <4> might represent strategic and tactical decisions. The ‘Analytics’ block in this case consists of data visualisation and user interface components.

True Automation

To enable true automation we must close the loop (i.e. Interface <2> must exist). But there is something that I have not shown in Figure 1 which is important for true automation. This missing item is the ability to process event-based data. This is very important especially for systems that are time dependent – real-time or near-real-time – such as trading systems, network orchestrators etc. This is shown in Figure 2.

Figure 2: Automation and different types of data flows

Note: Events are not only generated by the System being controlled but also by the ‘Brain’. Therefore, the ‘Brain’ must be capable of handling both time dependent as well as time independent data. It should also be able to generate commands that are time dependent as well as time independent.

Recursive Layers

Recursive Layering is a powerful concept where an architecture allows for its implementations to be layered on top of each other. This is possible with ML, DL and AI components. The System in Figures 1 and 2 can be another combination of a Brain and controlled System where the various outputs are being fed in to another Brain (super-brain? supervisor brain?). An example is shown in Figure 3. This is a classic Analytics over ML example where the ‘Analytics’ block from Figure 1 and 2 has a Brain inside it (it is not just restricted to visualisation and UI). It may be a simple new-born brain (e.g. static SQL data processing queries) or a sophisticated deep learning system.

Figure 3: Recursive layering in ML, DL and AI systems.

The Analytics feed is another API point that can be an input data source (Interface <1>) to another ‘Brain’ that is say supervising the one that is generating the analytics data.

Conclusion

So next time you get a project that involves automation (implementing or using) – think about the interfaces and components shown in Figure 1. Think about what type of brain do you need (age and density).

If you are on the product side then make sure bold claims are made, not illogical or blatantly false ones. Just as you would not ask a toddler to do a teenagers job, don’t advertise one as the other.

Finally think hard about how the users will be included in the automation loop. What conditions will disable interface <2> in Figure 1 and cut out to manual control? How can the users monitor the ‘Brain’? Fully automated – closed loop systems are not good for anyone (just ask John Connor from the Terminator series or people from Knight Capital https://en.wikipedia.org/wiki/Knight_Capital_Group). Humans often provide deeper insights based on practical experience and knowledge than ML or DL is capable of.

International Recycle Card

It is encouraging to see availability of recyclable packaging such as plastic wrappers, cans and food containers. But we see the problem of incorrect disposal, littering and lack of waste segregation everywhere (here I believe developed and developing countries are alike).

What incentive can the public be given to not only correctly dispose off their litter but also to pick up after others?

One common method has been the use of bottle/can bank where you return empty bottles and/or cans and you get some money in return.

My idea is to extend this and making it streamlined. 

Concept is simple.

Prerequisites:

  1. All packaging to be uniquely identified using RFID/barcode/QR code etc. – this should identify the source of the packaging and the unique package itself. Something like a bar-code
  2. Everyone buying packaged items has a Recycle Card (app or physical)
  3. (Optional) People buy items using electronic cash (e.g. credit cards) – to attach personal details

Process:

  1. Person scans the item (and the package code is also scanned alongside) – over time these could be the same code.
  2. Alongside the bill, a full list (electronic) is provided on the app for Recycle Card of all the packaging you have purchased (when you purchased the product).
  3. The ‘value’ of that packaging in terms of the local currency will also be shown.
  4. Upon successfully recycling the packaging, a part of that ‘value’ will be credited to the person. This can be a monthly or weekly process.
  5. Any litter found is scanned. The full ‘value’ along with a small fine is debited from the associated Recycle Card. The Recycle Card of the person who found the litter and correctly disposed it gets a small credit applied to it.

This means we recognise the value (in terms of money) of the packaging and not just the contents. This I believe is partially happening where ‘green’ products with innovative packaging attract a premium prices.

Furthermore we should attach a loss (again in terms of money) with improper disposal of the packaging. That is done only through fines but without direct accountability.

Key Factors:

There are two important steps here:

  1. Detecting successful disposal: This should be automated probably at the recycling centre some sort of machine which can scan and tally the packaging and indicate which Recycle Card should be credited. Packaging is unlikely to arrive intact at the Recycling centre. Therefore multiple markers need to be provided. RFIDs are a good solution but may be too expensive for regular use. One option is a dye that exhibits florescence under certain light. This would give a code that can be detected using machine vision. This is similar to the Automatic Number Plate Recognition software that has become very popular at parking lots, toll plazas and petrol pumps. 
  2. Registration of the Recycle Card: This should be a global system. Mainly because the problem of plastics and other packaging materials will impact everyone. Especially if these end up in our Oceans. People should be obligated to correctly dispose packaging where-ever they are in the world. Those who do so should be rewarded and those who don’t penalised. To ensure this – every pieces of packaging must be uniquely identified. This is a big task and I am sure there will be manufacturers (perhaps small/medium sized ones or from the informal sector) who will no follow this system (at least in the beginning due to cost etc.). But the idea is to target the 80% before we target the 20%. In the sense that big companies like Unilever, Nestle, etc. and fast-food joints like McDonalds have the capacity to upgrade their packaging. These are also mass-consumption products. So it would have a noticeable impact.

Do let me know what you think about this idea!

Somewhere in there there are few good machine learning and big-data use-cases. 🙂

Agile and Waterfall for Innovation

Agile methods are iterative and incremental. This, in theory, should prevent implementation death marches which end up with products that do not meet the customer’s needs.

Waterfall on the other hand, is all about having predictable stages with clear milestones at the end of each stage. There is no concept of iteration or increments. All of a stage (like design) are done, validated and only then is the next stage started. The concept here is that validation at the end of each stage keeps implementation aligned.

Unfortunately, both say nothing about the twin human-factor problems of over-excitement and incompetence of the people involved.

Often well understood and repeatable projects (like building a house) follow a waterfall.

Agile suits more ‘non-repeatable’ projects such as building a software product where each product will have its own challenges, risks and ‘hidden dangers’ – while being driven by changes in the ‘business’ environment. Therefore it is very important, when doing Agile for new and innovative products to:

  1. give clear guidance about what is working and what is not working back into the process 
  2. keep overall focus on the problem that the product is attempting to solve (i.e. always keep in sight that gold paved road to sales)

If Agile allows software to ‘flow’ freely, then it needs a proper pipe for it to reach its destination (i.e. the hands of the customer). If the pipe shape keeps changing, or has leaks in it there is no way the software will reach the right destination.

One thing, very easy to do (especially in a startup environment) is to get too excited about the problem domain without staking out what specific parts of that domain the product addresses. What is even worse is not sticking to it once identified! This is because Agile methods can be abused to hide (but not ultimately solve) problems with changing requirements and scope creep – resulting in big failures.

This process is made more difficult by the fact that for a new product idea one needs to find a gap in the market. The irony is: bigger the gap you find (Total Addressable Market – TAM) – more funding are you able to attract on the basis of future demand for your product – bigger the promises made – higher is the chance of getting lost in multiple interesting aspects of the ‘gap’ especially if there are conflicting views in management or if the gap area is not well understood.

Here multiple sources of tension exist: what constitutes a businesses view of the minimum viable product (MVP) and how is it different from the potential customers view (ideally both should be the same)?

The answer to the question ‘which part of the MVP should we do first’ – is the launching point for the Agile process. Ideally – a set of features are decided and then iterative and incremental development starts. As long as there is tough resistance to the business asking for massive changes to the path and clear feedback into the development from the ‘customer’, the end result should be aligned with what initial expectations.

I believe for big gaps where both investors and company owners see big $$$ signs, the so called ‘disruptive innovation’ – it may be a difficult thing to start off with Agile and maintain the discipline of clear feedback and clear definitions of done in terms of the MVP. In such a case it may be good to start of in a waterfall model – with low expectation of success, and then do Agile. Hopefully with one attempt at waterfall, one will end up with a product that can be put against the MVP concept, deltas calculated and then fed into an Agile process to be filled incrementally.

Why start with waterfall? Because waterfall imposes a strict condition of no-iteration. So it is more difficult to abuse it. It forces you to commit to requirements to do some design. To commit to design to write some code and so on. And as I said – in the end it gives you a good target to destroy when you start the Agile method. It can also give strength to push back on requirement changes and scope creep later on.

One may say that it is a waste to do waterfall. But one must remember in an Innovation, new product environment usually the target is not to ‘boil the ocean’. So it may be possible to quickly attempt waterfall to get a starting point for Agile. Also in most innovation environments, the initial team size and skill distribution does not allow for a proper Agile implementation in any case. For example it is not typical to find abundant testing or quality assurance resources.

 

What happens when … a failed healthcare system is opened to FDI

So there are many takers for Indian hospitals.This is very interesting given the fact that India’s healthcare spending as a percentage of GDP (~ 3.9% including private sector, ~1.8% excluding) is one of the smallest in the world whereas it has the second largest population in the world.

In this ‘what happens when’ we explore this scenario a bit. In India the demand is definitely there for healthcare. The supply is skewed towards urban areas and the variance in availability and quality of service is massive, especially when comparing Government run hospitals and private hospitals.

What cannot be argued against is that there is a massive gap between demand and supply with demand far outstripping supply. This gap is likely to further widen as the population ages. This gap, for sure, increases as we move down the wealth ladder.

In theory – investment is supposed to increase the supply (if used to build capacity). But that model works for products more than services. Especially where services are specialised in nature (e.g. MRI scanning, Gamma knife) or require extensive training (e.g. general practitioner, dentist etc.)  or both (e.g. neuro-surgeon, heart specialists, cancer specialists, neo-natal specialists etc.).

Therefore more money in today does not mean more doctors tomorrow. It means higher packages being offered to currently qualified doctors and specialists irrespective of whether they are in the private or public sectors. This would mean an increased demand for a resource in limited supply. In turn, to recoup the higher input costs the hospitals will have to find ways of either increasing their charges, reducing other costs or somehow battle to increase occupancy rates (perhaps by connecting with Health Insurance schemes?). This becomes even more important when we take into account the fact that any investment will require a return. Whether it is over a longer term or short term, fixed or variable.

So it leads to some disturbing conclusions:

  1. Brain drain away from the public sector into the private
  2. Providers sticking to safe markets (e.g. urban areas)
  3. Increased gap between quality and availability of healthcare as the costs rise
  4. Rising inequality in terms of access to healthcare
  5. Increased reliance on insurance to come in and plug the gap between treatment costs and income (insurance – healthcare provider nexus)

To think positively one can look at the silver lining:

  1. It would encourage setting up of integrated medi-cities (treatment, training and research) and expansion of medical education (suddenly all those medical colleges churning out MBBS will have more incentive to expand and improve quality of education – especially if the foreign owned healthcare facilities are more discerning than their local counterparts)
  2. There may be some risk takers driven by new investments, who may want to explore newer markets (e.g. smaller cities, villages) and come up with innovative business models for healthcare delivery
  3. Increased accountability and a driver to improve medical insurance (the US model)
  4. Turning to medical tourism to ‘subsidise’ treatments for locals (in the same way UK universities use foreign students to subsidise home students)
  5. Faster and (hopefully) cheaper access to advanced treatments

In all of this the Citizens of India and the Government will have to make sure that they act as watchdogs to make sure FDI does not result in exploitative practices or long term mis-alignment of the healthcare system in India.

 

Pokemon Go! Evolve vs Transfer

Each type of Pokemon needs certain number of candies (of a compatible type) to evolve to the next level. Usually you need  either 12, 25, 50, 100 or 400 (Magikarp) to evolve to the next level.

The exact number depends on the Type of the Pokemon as well as its current evolution level. For example Pidgey to Pidgeotto requires 12 Pidgey candies where as Pidgeotto to Pidgeot requies 50.

When looking to evolve Pokemon we often need to ‘transfer’ a few back to the Professor to earn candies before we have enough for the evolution. This is especially true in two cases:

a) Uncommon types (dependent on location etc.): where you will end up having far larger number of that type than you will be able to utilize for evolving. For example in our area there are very few Machop, and for the first level you need 25 Machop candies. Thus I will need to catch 9 Machop before I can evolve Machop! But if I was to transfer I could evolve after catching 7 (giving me 7*3 = 21 Machop candies) and then transferring 4 (giving me 4 Machop candies).

b) Very common types (to maximise evolutions especially if you have a lucky egg activated): where if you have a few hundred Pidgeys (again far few that you can evolve).

In both cases you need a way to calculate, given the current number of a particular type (e.g. for a Pidgey and Pidgeotto are different types even though they are part of the same evolution chain), the number of candies available and the number of candies per evolve – how many extra evolutions you can have by transferring some Pokemon.

The formula is:

ToInteger[(Nt + C) / (1 + Co)] – Nc = Ne

Nt = Number of currently present Type

C = Number of currently available Candies

Co = Number of Candies required for next Evolve

Nc = Number of possible Evolves without Transferring

Ne = Number of extra evolutions possible by transferring Pokemon

For example:

Let us assume you have 103 (C) Eevee candies. Now each evolution of Eevee (which has only a single level) requires 25 (Co) Eevee candies. Let us assume we have 30 (Nt) Eevee with us.

This gives:

Nc = ToInteger(103/25) = 4

ToInteger[(Nt + C) / (1 + Co)] = ToInteger[5.11] = 5, thus Ne = 5 – 4 then Ne = 1

Which means we can return Eevees to get one additional evolve!

 

Now we need to find out exactly how many Eevees we need to return to achieve that one additional evolve – while making optimal use of existing Eevee candies. The so called Equilibrium condition is that we have no un-evolved Eevees or unused Eevee candies after the evolutions.

The formula for Number of Returns (Nr):

Nr = [(Ne + Nc)*Co] – C

From the example above we have: Ne = 1, Nc = 4, Co = 25 and C = 103, which gives:

Nr = [(1+4)*25] – 103 = 125 – 103 = 22

Thus to make optimal use of existing Eevee and Eevee candies we should transfer 22 out of 30 Eevees and utilize the candies gained from transfer to evolve the remaining Eevees.

The result is not at Equilibrium because we will be left with 3 Eevees after we return 22 and evolve 5 [30 – (22+5) = 3].

Enjoy!

Please Gamble [Live] Responsibly

In UK there is a habit of trying to plan and manage everything. While this habit is one of the main reasons for the advanced state of development enjoyed by the countrys’ residents, sometimes it can be pushed to insane limits.

For example, out here  all gambling websites, shops and even advertisements need to have information pointing to ‘GambleAware’ along with the advice: “Please gamble responsibly”. The main purpose for this is to remind people to ‘gamble responsibly’ and to show people with gambling related problems a way out.

All that is well and good but my question is how can one gamble ‘responsibly’?

Gambling itself is an act of taking a risk. So they are asking us to ‘take a risk’ with responsibilty? If you were responsible for something would you take a risk? The obvious answer to that is ‘depends’ on what you were responsible for and what was the associated risk, but that brings us to the question of what exactly is involved in gambling. What is it that we are risking?

So I went to the GambleAware website to try and figure out what they highlight as ‘risks’ of gambling without responsibility… in other words what is their definition of ‘gambling responsibly’. This is what I found (from their website http://www.gambleaware.co.uk/responsible-gambling):

 
 
 

A person who gambles responsibly:

  1. gambles for fun, not to make money or to escape problems.
  2. knows that they are very unlikely to win in the long run.
  3. does not try to ‘chase’ or win back losses.
  4. gambles with money set aside for entertainment and never uses money intended for rent, bills and food.
  5. does not borrow money to gamble.
  6. does not let gambling affect their relationships with family and friends.
Weird!
1) Gambles for fun … : Well I don’t know about making money but as far as escaping problems is concerned then they should put the ‘Please escape from reality responsibly’ advice up on each and every source of entertainment. From movies to sports! Isn’t that what we use these things for? To escape from reality which is usually full of problems?
 
2) … very unlikely to win … : They should put ‘Please create babies responsibly’ advice in each and every hospital’s maternity ward. To warn the newborns that life is a game that is impossible to win. Everyone dies in the end!
3) … win back losses. : I thought it was a good thing to overcome odds and to ‘win back’ what one lost. Some of the greatest people did this to ‘achieve’ greatness. I also thought this was part of human nature to try and overcome loss. This is what allows us to go on in face of great odds and rebuild our life. This calls for the following general advice: ‘Please loose responsibly’.

4) … money set aside for entertainment … : This calls for the following advice in all shops: ‘Please spend money responsibly’ because we know that whenever we go into a shop or supermarket or a mall, hundreds of offers/sales/deals are thrust into our face! That is why expensive brands (which we really can do without) are reduced marginally in price so that the average person, thinking of it as a deal, tends to buy them leading to overspending.

5) … does not borrow money to gamble. : This is a good one. All the banks out there distributing credit cards like they were going out of fashion listen up! Put the following advice in bold letters on your credit card: ‘Please borrow money responsibly’. So that people don’t run up huge credit card bills buying things they don’t need and cannot afford just because they are able to ‘borrow’ money easily.

6) … affect their relationships …  : Another good one. All offices should have the following advice in all public areas: ‘Please work responsibly’. Also all managers and senior managers should be sent on special ‘working responsibly’ courses! We know work is one thing that affects our relationships the most. It keeps us away from our loved ones even after work hours. Gives us stress which we often take out on people we love.

Maybe we just need one advice tattood on the arm of all newborns: ‘PLEASE LIVE RESPONSIBLY’.

😉

So what do you think guys? Do you think we will see these bits of good advice popping up anywhere soon?

UK Elections: A Ringside View

UK Government elections are coming up in a few weeks time (May first week).  This election is a face-off between the Labour Party, who have been in power for the last 12 years, and the Conservative Party, who are sensing a real chance to form the government this time. There is a third party – the Liberal Democrats, dream of becoming king-makers and in reality can seriously affect the base of the two established parties.

One issue which, according to those who claim to be the ‘experts’, is going to dominate the voter’s minds is the economic crisis that gripped UK last year.

I believe that in politics your point of view is decided not by logic or analysis but by the political party that you belong to. Keeping this in mind, the fact that the UK economy has just about limped clear of the recession can be seen from three different prespectives.  

The Labour view is that they have taken some ‘very difficult’ decisions through some of the ‘toughest times’ seen by ‘world’ economy and have guided the UK economy out of the battlefield. According to the Labour government the economic crisis was not of their creation but something external in which the UK economy got dragged into.

The Conservatives have the view that Labour was responsible for the country facing such difficult times. That if they had been in power they could have helped UK sustain the storm better.

The Lib-Dems do not have a clear view of things. They keep changing their views depending on what the two major parties are saying.

There is one thing though, that all three of them agree on:  they have to take some ‘very difficult’ decisions and  some of the ‘toughest times’ are still ahead for the country.  

All three are saying there have to be big cuts in Government spending to reduce the deficit. But what exactly should be cut and how the resulting gaps will be filled, changes with the party. Great fear is also being generated regarding cuts in frontline services (e.g. Police and NHS).

What no one is willing to admit is the fact that the road ahead is not full of options. The steps that can be taken are limited. Yet the voters are being fooled into believing that there are multiple roads out of the mess and that each party holds the map to a different route.

Looking at these things from a temporary resident’s point of view I can say if frontline services like NHS and Police are cut then it will surely make the country less attractive for skilled workers. Free healthcare and a safety are two major requirements especially when it comes to people with families.

Immigration is the second point where these parties will clash. Again there are not that many options out. Already immigrations laws are very strict. Apart from closing the Tier 2 (Work Permit) and Tier 1 (Migrant Worker) schemes to South Asians (which will damage the UK economy and push work out of the country) they really can’t do anything.

To clamp down on illegal immigration will require increased government spending (for better border security and tougher enforcement) but the question remains: where will the money come from? Also the government will never admit this but illegal immigrants contribute a lot to the UK economy. They do the kinds of job which the locals will not do. Illegal immigrants, in fact, help the UK economy by providing cheap labour. They don’t pay any tax but even if they were legal the amount they earn would keep them well below the tax bracket.

In my view this election is going to be about whichever party screams the loudest and is able to convince the UK voter that yes indeed they can pull rabbits out of hats and pennies out of thin air!

Life is a box…

Someone recently asked me how would I like my life to be.
I thought about it and replied that life was not a retaurant where you go and give your oder “I would like my life to be a bit spicy but go easy on the problems”.
If we could “order” our life then there would be no growth as who would wish for tough times and problems from which we can learn?

The next question was what do I want from life.

This led to a second insight about the nature of life. I realised that life was like an empty box. Whatever you put in is what you will come out. Also while there are things in the box they change (like all things in nature). Another important point is that while it is up to us what to put in the box and when to put it, we have no control over takin things out. The only guarantee is that things we put in will come out.

So choose wisely what you put into life!

🙂

The multi-Billion Dollar Scam: Selling unsustainable dreams…

The real estate sector is booming in India. Areas just outside the four metro cities have seen land rates shoot up like a NASA rocket.

A textbook case is the suburb of Gurgaon touching the southern border of New Delhi. Till 10 years ago it was a dusty under-developed area with bad infrastructure. It was not a hot favourite for house-hunters and real-estate developers. How can I say all this? I had relatives living in that area and have been visiting them since I was 11-12 years old. I have seen that area develop as I was growing.

Then came the multi-national corporations, the call centers and the big brandnames. These were followed closely by the shopping-mall culture and a major empowerment of the young working Indian. All this meant that within a short span of time on a 4 km stretch of the Meherauli-Gurgaon road there were 6 shopping malls standing shoulder to shoulder.

While individually these were no where close to their western counterparts, taken together they formed a solid block of shops surrounding on of the busiest roads connecting Gurgaon with South Delhi. Within months the Meherauli-Gurgaon road became a nightmare for regular commuters. Being stuck in traffic for hours became normal.

Yet the property prices in Gurgaon kept increasing. New real-estate projects started springing up all over the place. There were buildings but no roads. Homes but no water or electricity. The boom was fueled by the ITeS boom in India and rise of home loans where young professionals starting their first job were able to buy flats and land. People made a lot of money selling dreams.

But what is the reality? Infrastructure is still trying to catch up with Gurgaon. Non-existant transport facilities are being supported with a new metro system. But what about water?

What about sustainability?

A crore’s worth of property is not of any use if you do not get water when you want to have a bath or electricity when you want to sleep. While power shortage can be removed (if your children are lucky then maybe in their lifetime) what will we do about water?
Study sees dramatic drop in Indian groundwater – longterm prospects are anything but bright for a good supply of water.

With a declining water table, unpredictable rains the long term forcast for Haryana points towards it becoming an extension of the Thar desert.

What will happen to the billion dollars worth of real estate? The investment in our future will be equal to a pile of sand?

Lack of sustainable development and blind destruction of the natural shield that is Haryana does not give a solid foundation to any kind of long term investment (for e.g. property investment).

The above factors make the real estate boom in India a bubble waiting to burst. When this bubble bursts a lot of people will be left with shattered dreams.

Few people though, will be left with a load of money they made selling unsustainable dreams.

The World and I

Does the world exist around us or do we exist in it?
I think the answer to this question reveals a lot about a persons thought process.

Most people will obviously ask what is the difference between the two views. What is the choice that we are being given in the question?

The fundamental difference in the choices is the net flow of influence. Do you end up influencing the world around you or are you influenced by it?
For most people there is no net flow because situations where the world dictates you are balanced by situations where you dictate the world.

In fact if there is no net flow then you are doing well in life according to me.