April 08, 2024
March 25, 2024
Neosapience - The unstoppable ascent
Neosapience -- which is my word for artificial intelligence (AI) -- is obviously all over the news. From self driving cars to ChatGPT ( technically, large language models) this new 'technology' has not only taken the world by storm but threatens certain core financial and social constructs that define human society. There is however a counter-view that claims that neo sapiens (AI programs or silicon intelligence) can never supersede the original homo sapiens (carbon based humans and animals) because they are being 'programmed' or built by humans. Continuing on this theme, it is argued because neo sapiens are being built by homo sapiens, they are at best an imitation of the original creators and so cannot be anything new, different or superior to what the originals are. Hence, humanity is safe from a takeover by neosapience. In this article, we argue why this is not true.
But to begin with what is intelligence? A simple, straightforward definition is unlikely to satisfy everyone so first let us define a model and then explore various models of intelligence.
What is a Model?
A model is a representation of something that 'exists' out there in the 'real' world. A model car, made of wood and plastic, mimics the behaviour of real car to a certain extent, but it can be made more realistic if we spend more money and time to include engines, tires etc. A mathematical model, like equations of motion or gravitation, developed by Isaac Newton, helps us mimic the behaviour of physical objects -- from balls to spaceships. A computer system -- like SAP -- helps us model an enterprise like Tata Steel or Hindustan Lever and tells us the money in their accounts or the inventory position in their warehouse. Building models, whether physical or digital helps us understand and mimic the world around us.
When we try to understand, mimic or model intelligent behaviour we have the choice of two broad categories of models.
Algorithmic models - that define intelligent behaviour as a set of tasks or steps that are required to, say, calculate the product of two numbers or the interest accrued in a bank account based on deposits and withdrawals, or define the steps required to solve a sudoku or Rubik's cube or even calculate the exact thrust or direction of a rocket engine that is travelling through space.
In each case, the complexity of each task is different but the model consists of breaking down the problem into smaller, easier problem and then assembling the answers in a clever manner to achieve the goals.
Non-Algorithmic models - where it is impossible to identify either a set of tasks or a 'clever' sequence of tasks that can achieve the goal. Typical examples of non-algorithmic intelligence include, for example, writing original computer programs ( to solve new problems), generating original poetry or prose or artwork that appeals to other humans and even coming up with original scientific equations ( say those that help us calculate gravitational forces). Mundane task like crossing a busy street are also examples of extreme non-algorithmic intelligence but we do not think much about them because even dogs and cats can do so!
To understand the difference between these two kinds of models let us look at two simple examples.
The gravitational model 'discovered' by Isaac Newton tells us how to calculate the gravitational forces between to massive objects ( of mass m1, m2) separated by a distance r. Since the gravitational constant G is known to, and is the same for, everyone -- even non-humans on a distant planet, anyone can arrive at the right answer.
Similarly a regression model that, say, connects the money spent on advertising to the actual sales of a product, is known, as a concept, to almost any marketing person who has learnt statistics in an MBA program. However the exact value of the two constants in the model (the slope, m and the intercept, c) changes from case to case. In the case of lipsticks, Hindustan Lever that has data on ad-spends and sales of lipsticks for the last five years, can determine the value of m and c and use that to predict lipstick sales. Similarly, in the case of cheese, Amul has the data on ad-spends and sales for the last five years and they can determine the value of m and c and predict cheese sales. So even though both Hindustan Lever and Amul knows how to use regression, HLL cannot build a model for cheese and Amul cannot build a model for lipsticks. ( And a B-school teacher like me, cannot build for anything, since I do not have any data, even though I know how to build it if I had the data)
In the case of gravitation, the model is completely defined by the equation F = G*m1*m2/r2 where {G = 6.674×10-11m3kg-1s-2 } is known to everyone. In the case of regression, the model is defined not ONLY by the equation Sales = m*AdSpend + c but ALSO by the exact values for say, lipstick : { m = 2, c =3} that is available with HLL and for cheese : {m = 20, c=3.5} that is available with Amul. The power of the model lies not in the algorithmic application of an equation but in the values of the constants, that are determined on the basis of historical data.
This set or collection of values, from the two simple pieces in linear regression {m,c} to the trillions of pieces in ChatGPT, is what defines these models.
Models of Intelligence
Initial attempts to model human intelligence, as in playing chess or translating from English to Bengali, were based on algorithmic models and had very limited success. However quite a few smart people caught on to the fact that the human brain is not algorithmic and intelligence lies, not in any of the neurons in the brain but in the way each simple neuron in the brain is connected to, or influences, the other neurons. But since there are nearly 100 billion neurons in each human brain, determining the influence of each on all the others was an insurmountable computational problem. The two key algorithms -- the backpropagation algorithm and the stochastic gradient descent algorithm - that help us to calculate the influence (collectively referred to as weights w, and biases, b ) have been known since the 1980s, but no one had the data or the computational power to build a non-trivial model by determining the exact values of the numerous {w,b} parameters.
The situation changed dramatically with the arrival of BigTech companies ( Google, Amazon, Meta etc.) with their voracious appetite for consumer data and new hardware (for example, GPUs from NVidia and cloud based systems from Amazon AWS). Now, for the first time, it was possible to analyse trillions of data points and calculate the billions of values that define the new "models".
As an aside, widely used machine learning techniques like regression, classification, clustering are not based on the architecture of the human brain but on principles of statistics. However the models that are created using these techniques consist of a collection of parameters whose values are determined from the set of historical on which these statistical techniques are applied. Once again, the strength, or quality, of the model lies not in the algorithm or the technique but the data on which the algorithm or technique is applied. However, all such statistics based models have been surpassed by a new class of algorithms that mimic the behaviour of the human brain.
The technology architecture of artificial neural networks ( ANNs) can now simulate, with software, the structure of the human brain with increasing levels of sophistication. The "architecture" in this case refers to how the simulated neurons are deemed to be connected to, and influence, each other because this, in some mysterious and ill understood way, reflects on the nature of problems that can be solved.
The initial feed-forward architecture was good for a large variety of problems but there are others, like convolutional networks and reinforcement networks that were found to be better for image recognition and text analysis. The current superstar in this area is one that is referred to as 'transformers' (nothing to do with alternating currents) that are based on 'attention' and the next one on the horizon is based on 'graphs'.
The techniques used to build, or simulate, these networks and the algorithms needed to calculate the parameters are all in the public domain. So in principle anyone can build these models if -- and only if -- they have the behavioural data from thousands of millions of individuals and the computation power to process them and calculate the values of the trillions of parameters that are needed by the model. At present, only big conglomerates have the ability to do so. The rest of us can only watch from the sidelines and only hope to use these models if we can afford to access them, as it happens in the case of ChatGPT.
Surpassing Humans
Now that we have some idea of what these models are, let us circle back to the question of whether these models can demonstrate behaviour that is better, superior, or more intelligent, than that of its creators. One of the biggest mysteries surrounding these models, is that even though the algorithm used to generate these trillions of numbers is known, the exact reason why a particular parameter has a specific value is indeterminable. There is no way to connect a cause -- say the image of fat man in a crowd -- to any effect, that is the value of a specific parameter. Since everything is probabilistic, it is impossible to identify a chain of causality. This leads to two kinds of behaviour. First, we have systems that hallucinate or generate illogical responses and second, we have systems that generate output that are logical and correct but have never been seen in humans before. This second behaviour has been detected in chess playing systems that have come up with novel strategies that are completely unknown to even the best of human chess players. [As an aside, no human, not even the best of the lot can win against any chess playing program today]
The key takeaway from this situation is that the strength or quality of any model does not lie in the algorithm or programming skill of the person who built it but on the quality and quantity of the data that is used, or ingested, while training the model. That is why it is incorrect to assume that neo sapient systems can never supersede the ability of homo sapiens, who build them.
The process of learning and its outcome does not depend on the competence of the teacher, but on the way the student can apply it to the environment in which they find themselves. Had it not been the case, Einstein and Newton would not have been able to generate knowledge or insights that were not available with their teachers.
Today, large language models like ChatGPT and others, can write computer programs, poems, stories, screenplays and generate images and videos and the quality is improving by leaps and bounds with every passing day. In the case of business communication and computer programs, areas where LLMs have had access to maximum data, they are already better than 99% of humans. [ For example, the graphic used in this post was created by me with Bing in about 15 mins and I am sure that a vast majority of my readers would not be able to create anything similar on their own, without using a generative AI tool ] Salman Rushdie has claimed that in the case of originality of thought and humour AI or neo-sapient artifacts are still deficient but this claim is essentially baseless because with the passage of time and the availability of more and better data the capability can only increase.
Physics puts an upper limit on the speed that a material body can travel at and this is the speed of light. To go faster than this limit, one has to conjure up strange artifacts like tachyons that lie beyond the realm of normal physics. Similarly, is there some divine or extra-human power that allows some of us to demonstrate creativity that no one else can replicate? If -- and only if -- there is, then our current crop of neo sapients would never have the ability to access that kind of power and and hence would never equal or surpass these highly gifted humans. But if there is nothing divine in human ability, then there is nothing that can stop neo sapients from surpassing homo sapiens in any realms of intelligent behaviour.
Post Script : Genetic Information Models
If we consider genetics, then there is another -- possibly controversial and certainly non-mainstream -- analogy that can be brought to bear in this debate. While the debate between nature and nurture -- whether we are born with certain abilities or whether we acquire them in our life -- is still open and contested, we do know for sure that humans are more intelligent than, say dogs or cats, and this because of our genome. The genome of a living organism is actually a sequence of proteins grouped into genes and arranged on our chromosomes. This is basically information. So our intelligence is based on information stored in our genes and this can be viewed as the model. The process -- or algorithm -- that converts this information into proteins that make up our body is almost the same for all living things, so the magic lies in the information stored in the model and not in the process of converting it into our material body. But unlike human and current machine learning models where this information pattern is created rapidly, the genetic information gets created or updated very slowly over many generations and millions of years. Nevertheless, it is still information ( or data) that plays the key role in the ascent of species. Except that biological sapients have been evolving far more slowly than our machine counterparts. But that is a different story altogether.
December 31, 2023
PostgreSQL 42
Why is 42 a special number?
The number 42 is, in The Hitchhiker's Guide to the Galaxy by Douglas Adams, the "Answer to the Ultimate Question of Life, the Universe, and Everything", calculated by an enormous supercomputer named Deep Thought over a period of 7.5 million years.
This slide deck (with 42 slides) demonstrates a wide variety of SQL statements that should meet almost every common requirement faced by data scientists. The accompanying Google Colab Notebook will allow the user to install Postgres in a free VM and explore variations of these commands. Here is the full course outline for my brand new RDBMS course, complete with all slide decks and notebooks.
September 10, 2023
Restructuring the Indian Space Program for Financial Efficiency
While India celebrates the success of Chandrayaan-3 in safely delivering the Vikram lander and the Pragyan rover to the surface of the Moon, it should not view this exercise as an end by itself but merely a means to an end. But what is that end goal that India should be looking for? A lunar base of course, but first, why?
History tells us that the famous Chinese mariner Zheng He carried out seven maritime missions (1405 - 1433) on behalf of the Ming emperor to different parts of East and South-East Asia right up to the Horn of Africa. The goal was to increase trade by 'showing the flag' and impressing the natives of distant lands with the maritime prowess of the Chinese navy and the wealth of products that were available in China. But the fatal flaw in this strategy was that he never established a Chinese colony anywhere. On the other hand, the European mariners who came a century later not only visited the same ports but immediately set up 'factories' or trading posts. These eventually became colonies from which they transferred vast amounts of wealth to Europe and laid the foundations of the opulence that we see there now. Today, China is trying to make up lost ground by trying to establish bases and colonies in the Indian Ocean and Africa, but that is a different story.
The Chandrayaan saga should be seen from this perspective. Landing on the Moon is a demonstration of India’s incredible technical skill. Setting up a permanent base there should be the business and commercial vision. But before one can set up a base on the Moon, there are three key prerequisites that need to be in place : technology, money and political will. We explore how these can be made to converge in a practical manner.
Technology is of course a necessary condition. Travelling to distant planets calls for technologies that are currently available with only a handful of countries while setting up permanent bases is something that no one has yet done. But however difficult that it may be, the problem is obviously solvable. As long as something is not barred by the laws of physics it is a matter of time and money before human ingenuity will come out with an engineering solution for any problem. Which brings us to the next challenge - money and the political will to spend it. This is where the real problem lies because the quantum of money involved is stupendous and the risk of failure is high.
While the Indian government can certainly fund a couple of Chandrayaan style missions, scaling up to the next level of setting up permanent bases on the Moon would impose an extraordinary level of financial stress on the Indian tax payer. To invest that kind of money would mean imposing a drastic cut on what the nation can spend on national development -- roads, schools, hospitals and other public facilities. Not only would this be politically unpalatable but morally irresponsible. After all this is public, tax-payer money and it should be spent for the greatest good for the greatest number. A base on the Moon may be a worthwhile goal for many but mortgaging the future of a nation on a risk prone endeavour is never a good idea. As long as the investments are small, at the level of Chandrayaan, India can still go ahead but if the cost becomes a thousand times larger, as could be the case for a lunar base, then it needs to look at alternate funding models. For this, let us again look back at history.
The British came to India, not with money provided by the government of England, but as the East India Company -- one of the first joint-stock companies in the world. This private company was owned and funded by private investors. This small group of people had the required risk appetite that allowed them to invest private funds in this risky enterprise and the results are known to everyone by now. What stops India from adopting the same for space travel and lunar habitats?
Private investment in space is not a new idea, as Elon Musk and Jeff Bezos have already shown. But even these super-wealthy people have barely been able to scratch the surface of the technical and funding challenge. Given the total size of the Indian stock market and the wealth, and risk profile, of the Indian investing community, it is unlikely that an equivalent of the East India Company will emerge from investors in India. This is true even though the success of Chandrayaan-3 has led to a stupendous Rs 31,000 crore ( USD 3.75 billion ) rally in the shares of companies that have supplied components to this project. Clearly, some creative corporate and financial structures are necessary if we need to fund such large projects from private investors.
Space operations in India are currently managed by ISRO and Antrix. ISRO, as a part of the Department of Space, is a government department while Antrix Corporation is a registered company and acts as ISRO's commercial arm. Antrix gets paid by customers who want to launch satellites but the cost of doing so is borne by ISRO. This does not matter, because Antrix is wholly owned by the government and it is simply a matter of transferring money from one pocket to another. This model needs to be expanded further and should be opened up, in a phased manner to private investors, both domestic and foreign.
The first task is unbundling the various services that ISRO offers and the obvious model for this is the way most State Electricity Boards (SEB) in India were unbundled into three different organisations, for generation, transmission and distribution of electricity. While still largely owned by the government, each entity is now a registered company with its own balance sheet, P&L and governance structures. These companies act as customers, suppliers or both of each other or of other similar companies formed from other SEBs. Instead of inter-departmental exchange of services within the same government department, that is the erstwhile SEB, these companies now have independent arm's-length relationships with other similar companies. This eliminates cross-subsidisation and delineates the financial status of each company with greater transparency.
If we apply the same logic and process to ISRO, the task of setting up and operating a lunar base can be unbundled into several major activities and managed by different companies. These companies may be directly promoted by the government as PSUs or could have as promoters, other corporate entities -- public or private -- that have the requisite technical and managerial expertise in the specific business domain. These could be :
- RocketCo - The Rocket Company that will provide the primary interplanetary transport services for both equipment and personnel to the other companies. RocketCo would be promoted by or be a successor to the existing Antrix Corporation.
- PowerCo - The Power Generation Company. Energy is the primary requisite for all other activities and since, as explained in another article, (https://bit.ly/3QUAZXZ) nuclear power is the long term solution for an industrial economy on the Moon, this could be promoted, for example, by the Nuclear Power Corporation of India.
- MineCo - The Mining Company. Mining for valuable minerals will be the one of the primary activities on the base. This company should be promoted by companies already engaged in mining, for example, Coal India, National Mineral Development Corporation and Vedanta.
- InfraCo - The Infrastructure Company. This will build not just the habitats where eventually people will stay but also the basic civil infrastructure needed by PowerCo and MineCo. This company could be promoted by or have significant equity participation from major infrastructure majors like Adani, Shapoorji Pallonji and GMR.
- RoboCo - The Autonomous Machine Company. This will build autonomous machine tools and vehicles that will be used by PowerCo, MineCo and InfraCo to meet their business goals. This company could be promoted by heavy engineering companies like Larsen & Toubro.
- LifeCo - The Life Sciences Company. This company will not only focus on space medicine but will leverage genetics, bio-engineering and similar techniques to identify and promote plants, microbes and other life forms that will survive on the Moon and other planetary destinations like Mars and Titan. This company could be promoted by Serum Institute, Biocon and other leading biotech companies in India.
- AdminCo - A management company that will regulate the technical, commercial and legal relationship between the other six companies and provide the mechanism for dispute resolution and maintaining law and order. This company will be the administrative backbone of the lunar base and of course would be entirely owned by the government as an extension of the Home Ministry.
In each case, the existing terrestrial expertise in each domain would need to be upgraded to support the expectations and requirements of space and the Moon. Obviously creating this capability is a huge expense but dividing the work amongst different companies will make it easier. Each company would have a narrow focus and they will become operational in a phased manner
More importantly, the vast investment required for such an enterprise can be raised in a phased manner by private placement of the shares of these companies to venture capitalists, both in India and overseas. Eventually, when a certain level of maturity has been achieved, each company can go for an IPO in local and global markets. The quantum of dilution in each case would be determined by the government based on strategic imperatives. For example RocketCo may have only a small fraction of non-government shareholding whereas InfraCo could be diluted almost entirely leaving only a small part of the ownership with the government.
Setting up a lunar base is the first step in our evolution towards becoming an interplanetary civilisation. To go to the Moon and beyond is not just a commercial or business compulsion. It is an expression of the atavistic urge to break the bonds that tie us down to our zone of comfort and explore the vast unknown that lies beyond the horizon.
Engineers at ISRO have demonstrated extraordinary skills in taking India to the Moon. Now it is for the corporate sector to follow it up with the right financial engineering so that India can continue with the next step and build a base on the Moon.
In the words of Rabindranath Tagore, "এবার তোর মরা গাঙে বান এসেছে জয় মা বলে ভাসা তরী" - Now that the tide is surging through the dry river bed, Hail the Mother and launch your boats.
August 24, 2023
After Vikram, Bhabha next : Nuclear Power on the Moon
The stunning success of the Chandrayaan / Vikram / Pragyan mission opens up a world of possibilities for India on the Moon. The next logical step would be to set up a permanent base station - similar to Dakshin Gangotri in Antartica -- that would serve as a locus for the mining, manufacturing and other operations. The Indian engineering industry has extensive experience in these areas, but their expertise would have to be fine-tuned and optimised for the lunar environment. The single most significant difference from Earth bound operations would be the use of autonomous machines, or robots, to do most, if not all of the work. This is because supporting a human workforce in such a harsh environment would increase the cost of doing business to the point of becoming economically non-sustainable.
Fossil fuels are again out of the question because even in the extremely unlikely event of locating deposits, there is no oxygen on the Moon to burn them and generate heat. So, the only realistic option for generating electricity on an industrial scale is nuclear energy. In fact, this is true even for Earth but because we have easier options here, we do not explore it so urgently. But on the Moon, nuclear energy is the only option and fortunately, setting up small, nuclear plants on the Moon is -- relatively speaking -- not at all that difficult.
Small modular reactors (SMR) [see 1, 2] are the first choice in this regard because of two important reasons. First, they need a smaller amount of radioactive fuel and second, and more importantly, they can be built at a remote factory and then carried to and installed at the intended site. This is the perfect approach for a lunar power plant because we could build these reactors on Earth and carry them, in multiple, and bigger, Chandrayaan type missions to the surface of the Moon and have them installed by autonomous robotic workers.
Nuclear power on Earth faces political and environmental challenges because it is perceived to be dangerous for humans, even though a rational debate would debunk this claim. On the Moon however, this would not be an issue at all because there is, literally, enough space out there to make sure that reactors and the spent fuel are located far away from the base station. In fact, new nuclear technology can in fact be first tried out, first on the safety of the Moon before they are deployed back here on Earth. Isaac Asimov had indeed anticipated this in his sci-fi micro-story "Silly Asses".
Ferrying a small modular reactor from Earth to the Moon in a knocked-down state is again not a difficult proposition. A 300 MW nuclear reactor of the kind used in nuclear submarines would weight around 700 tons. Assuming that an enhanced Chandrayaan can carry a 10 ton payload on an energy-frugal journey to the moon, we would need 70 launches. A Chandrayaan mission costs around Rs 650 crores and of course this cost will go down significantly with each subsequent and successful mission. A typical wide-bodied aircraft from Airbus or Boeing costs around Rs 400 crores and both Air India and Indigo have placed orders for hundreds, yes hundreds, of these machines. So the Indian economy could easily sustain two Chandrayaan launches every month and create resilient supply chain that will deliver a small modular reactor to the Moon in a reasonable, 5 - 7 year, time frame.
Finally, where we do get these small modular reactors from? The Indian atomic energy program is currently focussed on building and commissioning large nuclear power plants in different parts of the country and even this has run into political and environmental challenges. However, SMR technology is under active development in many countries and some plants have already been commissioned in Russia and China. What we would need to do is to leverage our extensive experience in traditional nuclear power and quickly set up industrial alliances with suppliers of SMR technology to create new models and designs for SMRs that can be deployed on the Moon.
This approach would call for both the Indian Space Research Organisation and the Indian Atomic Energy Commission -- two very powerful and autonomous bodies -- to work together towards the common goal of creating a sustainable energy supply for a vibrant industrial economy on the Moon. This can only happen if the political leadership takes the initiative to initiate such a mega project and drive it to its successful conclusion.
After Vikram (Sarabhai) it is time for (Homi) Bhabha to go to the Moon.
Post Script : Two of my engineer friends, Amitava Das and Rob Roy have indicated that heat removal may be a big challenge on the Moon. I am sure that this is not the only challenge but I am also sure that all such challenges can surely be overcome.
The reader may also look at three earlier posts on the contours of the space economy
July 12, 2023
Bhagavad Gita and the Illusion of Duality
Unlike Abrahamic religions, Sanatan Dharma is mature enough to handle both heresy and blasphemy, and this gives us the right and liberty to question certain perspectives that lie at the core of what is referred to as Hinduism. Of late, a certain minor operative of ISKCON has been very critical of Vivekananda and Ramakrishna but on enquiring further I realised the ISKCON boss himself, Prabhupada, had referred to both Vivekananda and Aurobindo as rascals. To understand this behaviour, I delved further and realised that what I was reading today was in fact bending back to what a school friend of mine had once told me: that the Bhagavad Gita reads like a marketing pitch -- believe in me or you are doomed.
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| An image of a woman seen in the reflection on the pupil of one eye of another woman. digital art. |
Many well-known and supposedly erudite people have sung paeans to the glory of the Gita that was delivered 'directly by God' on the battlefield of the Mahabharat. But it has some obvious problems. First there is the immense chasm of duality that separates ME from the GOD, and the god is obviously far, far superior to what I, me, am and it is only he who can save me. This is no different from the Abrahamic texts like the Bible and the Quran. No wonder, people who have been brought up in the Judeo-Christian tradition love this perspective. For them it is a simple switch from the Almighty GOD to Almighty Vishnu and everything else falls in place with the chanting, the dancing and the fellowship. Only the Hallelujah is replaced with Hare Krishna. Which is why Prabhupada, the shrewd marketer that he was, used this tool to sell Hinduism in the West. That is the language they understood very easily. On the other hand, Vivekananda, with his vast intellectual bandwidth, was far ahead of Prabhupada in terms of both his intuitive and cognitive abilities. But he also had the intellectual honesty to portray Sanatan Dharma as it truly is and not the ersatz, Abrahamic, version that Prabhupada peddled to the non-Indians.
Sanatan Dharma -- the perennial philosophy of the Indic realm -- is based on the Vedas and the Upanishads and not just the Itihas of the Mahabharat of which the Bhagavad Gita is but an appendix. Sanatan Dharma looks at the universe with a far more open and questioning mind. This begins with, among other things, the Nasadiya Sukta of the Rig Veda that asks "But, after all, who knows, and who can say Whence it all came, and how creation happened? the gods themselves are later than creation, so who knows truly whence it has arisen?" Then it looks deeper, and we realise that this duality of me and the god that we worship is an error forced upon us by the illusory Maya. Both Sankara and his modern avatar Vivekananda tells us there is no duality -- of me and my god, but only the singularity (or non-duality, Adwaita) of man and the Universal Consciousness of Brahman (different from Brahma, the Vedic deity).
The phenomenal world that we perceive around us, that is me, myself and all that I can see and touch around me, are but an illusory image -- an incomplete reflection, a pale shadow-- created in, by and through the Maya or illusion caused by the Prakriti that emanates out of the primordial Consciousness, the Brahman, when he desires to engage in his lilā. But what is it a reflection or image of? It is a reflection of the Purusha, a derivative of the Brahman that is seen through the fog of the Prakriti that was derived simultaneously. Eventually -- once the lilā is over -- the reflection, the image (the phenomenal world) in Prakriti dissolves back, or converges, into the Purusha through the process of a Yogic union and recovers its state primordial singularity of the Brahman, which is pure consciousness, without form, shape or qualities. That is why Yoga is so central to Sanatan Dharma. It is not merely a set of physical exercises that keep the body healthy; the exercises are a good by-product. Yoga is the convergence of the subject, the object and the action itself -- for example, the food, the eater and the act of eating. Or as in this case, the merger of an object, its reflected image and the medium where the reflection happens.
Vivekananda simplified this concept of non-dual Advaita in the image of Shiva as a calm ocean of pure knowledge on the surface of which individual identities are whipped up by the power of Shakti -- Shiva's passion or desire -- as ripples or waves that rise out of deep and then after a while merge back into the depths of great ocean, once again. The ocean when it is calm is Shiva. The same ocean when it is turbulent with waves, is Shakti. Eventually Shakti will and does merge back into the calmness of Shiva in the process of Yog.
This perspective is so vast, so profound, so eclectic and so alive with potential that anything else pales into insignificance before its grand effulgence. Viewed against the backdrop of this magnificent vision, the imagery that is rendered through the Gita -- where the man, Arjun, is simply subservient to the god, Krishna and must obey his commands -- sounds downright juvenile and fit only for simple, immature minds. What is hilarious is that even with these commands, God fails to convince Man of his greatness and when his logic fails, he has to use the magic of Chapter 11, to stun him into an acceptance of his greatness. This is the really, really disappointing part of this very popular text.
But for the advaitins this is a very minor issue. Sanatan Dharma is so very generous and inclusive that it does not deny or denigrate the duality, or Dwaita, based bhakti of the Bhagavad Gita. To remove the illusory Maya and experience the union, or Yog, of the individual and the Brahman, it says, that one can follow any one, or even more than one, of the four paths, namely, of knowledge, of duty, of bhakti (as advocated in the Bhagavad Gita) and the esoteric path -- RajYog -- known only to its adepts. That is why, Sankara, the greatest advaitin of them all, had no hesitation in adoring both Govinda as well as the Divine Mother whom he regarded as the Purusha and the Prakriti, and celebrating their union in the imagery of the SriYantra.
Unfortunately, the ISKCON-wallahs would not see things this way, and like their Abrahamic cousins, will not allow even others to see things this way. For them, it is my way or the highway, except that the ISKCON-vaishnavs have not yet descended to the level of murder and mayhem so beloved of their Abrahamic cousins.
