Friday, February 23, 2024

$NVDA: When You are The Moat

Posted on February 23, 2024 by admin with No comments

NVIDIA had their earnings call yesterday for the quarter ending Dec'23. Markets were muted in anticipation. As expected, the S&P 500 rose by 2.5% on the back of a strong performance and pipeline.

The day after, NVIDIA stock rallied to all time high of $800. This gave the company a market cap of USD 2 Tn, surpassing Alphabet, Inc., and becoming the fourth largest listed company in the world by market value. 

For perspective consider this - the single day gain of USD 277Bn was bigger than the largest listed company in India - the world's 4th biggest equity market, and by an estimate its market cap was now larger than the entire SENSEX of India.

Who knew? Perhaps not even Berkshire Hathaway. (See share holding pattern in the links below).

One of the simplest reasons for the meteoric rise of NVIDIA is, as Warren Buffet once famously said about resilient businesses, that NVIDIA provides a moat to the the software firms for their business of developing and productising AI and, specifically, GenAI. 

Imagine a very, very large Excel sheet, where every cell is linked with other cells using some simple formula. That is, if you make a change in any one cell, the cascading effect will be seen across the entire grid where every cell would require a re-computation. Such a computation need not be intensive at a cell level, but the sheer quantity (ie the number of cells require re-computation concurrently) can be overwhelming even for the fastest of Intel CPUs. 

AI model training and data retrieval is similar. It requires computation that is very concurrent in nature. A large Language Model (LLM) for a GenAI such as ChatGPT typically has billions of parameters, where change in each parameter can affect all other parameters.  

Unprecedented resources are required for a task such as this. A large portion of those resources are GPUs - specialised computer chips designed to handle 'concurrent' calculation.  NVIDIA is the current market leader in developing and supplying such GPUs to the resource hungry AI companies.

Apart from the availability of very large quality dataset and algorithm development itself, this resource intensive nature of developing and maintaining LLMs raises barriers of entry in the market. A very important force in the industry. 

This is the moat.

Now, in May last year, an internal memo from Google leaked. It got famous by the meme- "We do not have a moat, and neither do OpenAI". The conversation of the memo centred around the resource availability of large dataset and the algorithm development at Google and OpenAI, and how Open Source models are catching up. "While our models still hold a slight edge in terms of quality, the gap is closing surprisingly quickly." lamented the memo.

So, when software doesn't hold as a moat, it has to default to hardware.

Therefore, NVIDIA.

But there is a problem.

This moat has a price-tag. (which moat doesn't? Well, those that do not, and are shrouded in casual ambiguity become your competitive advantage!)

It was perhaps this moat building that took Sam Altman to Saudi Arabia, and the rumours that followed about the trillion dollar investments towards chip development. True or not, the threat perception of proprietary GenAI such as ChatGPT and Gemini from the Open sourced and funded models such as Llama3 by Meta are high.

To cement its entrench position, NVIDIA is said to be in conversation with Alphabet, Amazon, Meta, Microsoft and OpenAI to build custom chips for their respective positions. It is not difficult to predict how this might play out. There can be only one Wintel-like alliance. Meta has announced an intent to purchase upto 350,000 NVIDIA H100 GPUs, taking the total stockpile to 600,000 GPUs. At a discounted rate of USD25,000 a piece, this is more than USD 15 Bn for the boxes alone.

As an analyst observed, "The people who made the most money in the Gold Rush of mid-1800s were the ones providing the tools to get the job done, and not those hunting for the precious metal. NVIDIA is effectively playing the same role today in this tech revolution." 

Therefore, what the moat is guarding is an entirely separate issue. 

In the next post we will look into the hype, the Concentration of power, the de-centralization and true democratisation of AI.

Did you read anything interesting this week on AI? Would love to know. Drop in a comment!

 

Moat and the Gold Rush
A GPU moat guarding the castle of shovel-makers during the Gold Rush of mid-1800s.

References and Further reading:

Thursday, December 28, 2023

The Independent Directors at OpenAI

Posted on December 28, 2023 by admin with No comments

Sam Altman was the CEO and Greg Brockman was the chairman of the board at OpenAI.org, the parent company that is listed as a not-for-profit organization in the US u/s 501(C)(3). 

On 17 Nov 2023 both of them were fired by the Independent Directors of the board. This post talks about the 4-day drama that ensued at the back of these events, focusing on the role of Independent Directors. (Try here for a related earlier post.)

One year ago the company launched the ChatGPT, the Large Language Model, that rose to prominence with its Generative AI capabilities (“GPT” or Generative Pre-trained Transformer) and human-like response and interactive interface (“Chat”). At launch ChatGPT was based on based on GPT-3.5 series. The launch took the internet by storm as Microsoft unveiled its commercial partnership with the firm, and its global marketing machine geared into action. 


To accommodate for this new profit-making "partnership" endeavor, the firm came up with another for-profit arm of OpenAI called "OpenAI Global LLC". There was already a "capped" For-profit subsidiary for fund raising et al. However, the supervisory board remained the same as before, and thereby, the corporate governance become hybrid – the same 5-member board now oversaw all the three entities of the company.


Elon Musk claims to have co-founded OpenAI in 2015 “to counter AI dominance that Google had at that time”. He claims that nearly 66% of top AI talent of the planet was cornered by Google at that time, but Google founders did not have AI safety as their priority. The intention was to create an Open-source AI rival to Google’s DeepMind, and hence the name “Open”AI.


Over time, the Corp structure of Open AI has evolved, and it has the following key constituents at present:

  • OpenAI (Not-for-profit): The main governing body that is (still) responsible for the overarching decisions of the entire group.
  • OpenAI (For-profit subsidiary): For fund-raising and other commercial purposes this subsidiary was created. It also helped in talent acquisition in the competitive AI market.
  • OpenAI LP (now OpenAI Global LLC): One of the unique features of OpenAI corporate structure is this Limited Partnership entity. It has a hybrid structure and is a “capped profit” company. It allows for keeping a check on “profit chasing” by investors (and employees) by capping the returns at 100x of their initial investments.

But still, the structure did not have room for Microsoft, Inc., who had substantial investments and pledges, totalling USD 13Bn+, with OpenAI. Microsoft does not have a direct control or a Board presence. (Though this should be more of a worry for the shareholders of Microsoft. With the backdrop of this OpenAI drama, during the Q4 2023 Earnings call, Satya Nadella said "The approach we are always going to take is a broad tent approach"). 


The Independent Directors of OpenAI.org (17 Nov 2023)


On November 17, the Independent Directors of board - Helen Toner, Adam D'Angelo and Tasha McCauley, along with co-founder Ilya Sutskever, removed Altman as the CEO and Brockman as the Chair of OpenAI. The reason cited was a lack of confidence and candidness. No details have been made public. Check their brief bio at the end of this post.


After 4 days of internal churn and external mayhem, Sam Altman returned to OpenAI as the CEO. Brockman also returned as a President. Except for D’Angelo the entire board was replaced.



Let’s delve into the role of Independent Directors and related questions that surrounded the drama:


Who’s interest should the Independent Directors have protected? The Not-for-profit entity or the For-profit one?


Independent directors on the board of OpenAI should primarily protect the interests of not-for-profit OpenAI.org. This aligns with the original mission of OpenAI to ensure AI benefits all of humanity.


The for-profit arm, OpenAI LP (now OpenAI Global LLC), is a mechanism to attract capital and talent, but its activities should align with the overarching goals of OpenAI.org.

The governance structure must ensure that the profit-driven motives of OpenAI Global LLC do not overshadow the ethical and broader human-centric objectives of OpenAI.org.


Was the Hybrid Governance Model a wrong choice to begin with? How the Board could ensure optimal performance given the challenging nature of the model?


The hybrid governance model was innovative but complex. It aimed to balance ethical AI development with competitive market presence. An industry observer commented that the crisis of Altman’s ouster would not have come to pass if someone like Vinod Khosla was on the board. 


Let’s also remind ourselves of Eric Schmidt as Google’s CEO from 2001 to 2011 (and subsequently as the chair of the board until 2017). During his time as the CEO of Google, which was but a search algorithm at the time, came to transform the world of Internet as we know it. Schmidt was 18 years senior to Google founders Brin and Page. And he famously described his role with Brin and Page as that of “adult supervision”.


In addition to missing oversight from a seasoned leadership, the criticism of this model centers on potential conflicts between profit motives and ethical AI development.


After Sam Altman's return as CEO (but without a Board membership, at least for now), and constitution of the new board of directors, better governance can be provided by:

  • Ensuring clear, transparent governance structures that align both entities' goals.
  • Implementing robust checks and balances to manage conflicts of interest.
  • Fostering a culture of ethical AI development, even within the for-profit arm.

Endurance of the ‘Startup’ and Influence of ‘Sharks’?

  • OpenAI, initially a startup, has rapidly evolved, partly due to significant investments from companies like Microsoft.
  • The influence of large tech firms, referred to as ‘sharks’, can be double-edged. While they provide necessary capital and resources, their business interests might conflict with OpenAI's original mission.
  • The longevity of OpenAI's startup ethos depends on its ability to maintain a balance between innovation, ethical AI development, and commercial pressures.
  • The governance structure and board's role are crucial in navigating these challenges and ensuring OpenAI's mission isn't compromised.

In conclusion, the governance of OpenAI, especially in light of recent events in Nov 2023, highlights the complexities of balancing ethical AI development with commercial success. The independent directors and the new board have a critical role in maintaining this balance and ensuring the organization's original mission is upheld.


Sources and further reading:

  • OpenAI announces leadership transition (Removal of Sam and Brockman) (try here.)
  • Elon Musk – comments on Founding OpenAI (try here.)
  • CNBC: Microsoft CEO Nadella says OpenAI governance needs to change no matter where Altman ends up (try here.)
  • Microsoft, Inc earnings call - Nadella hedges against the big bet on OpenAI (try here.)
  • OpenAI Blog: Moving AI Governance Forward (try here.)
  • Eric Schmidt on Twitter, “Day-to-day adult supervision no longer needed!  http://goo.gl/zC89p” (try here.)
Brief bio of the Board of Directors at OpenAI.org on 17 Nov 23:

Ilya Sutskever is the co-founder and chief scientist of OpenAI who leads the research in the artificial intelligence company. He has also been one of the architects behind the ChatGPT models. Sutskever is a Russian-born Israeli-Canadian who specialises in machine learning.

Prior to his involvement in OpenAI, Sutskever was the co-inventor of AlexNet and Sequence to Sequence Learning. He is also amongst the co-authors of the AlphaGo paper.


Helen Toner is the Director of Strategy and Foundational Research Grants at Georgetown’s Center for Security and Emerging Technology (CSET). She has previously worked as the Senior Research Analyst at Open Philanthropy.

She is a member of the board of directors at OpenAI. Tones holds a master’s degree in Security Studies from Georgetown, as well as a bachelor in science degree in Chemical Engineering and a Diploma in Languages from the University of Melbourne.


Tasha McCauley is an independent director at the company and has been recognised for her work as a technology entrepreneur in Los Angeles. McCauley also enjoys a fan following as she is the spouse of American actor Joseph Gordon.

She is the chief executive officer (CEO) at GeoSim Systems, which is a pioneering company involved in developing 3D city modelling systems. Additionally, Tasha McCauley is also the co-founder of Fellow Robots. She holds an MBA degree from USC Marshall School of Business.


Adam D’Angelo is an American internet entrepreneur who is known for co-founding and directing Quora. Earlier, D’Angelo held a pivotal position at Facebook, while serving as its Chief Technology Officer (CTO) wherein he oversaw new product development and managed the engineering team. 

D’Angelo holds a Bachelor’s degree in Computer Science from the California Institute of Technology in 2002. After working for Facebook, D’Angelo embarked to found Quora in 2009. Later in 2018, he joined as a board member of OpenAI.


Monday, December 25, 2023

Tuesday, December 19, 2023

Sunday, December 17, 2023

Thursday, December 14, 2023

Tuesday, December 12, 2023

Monday, December 04, 2023

Friday, December 01, 2023

Wednesday, November 29, 2023

Monday, November 27, 2023

Monday, November 13, 2023

Thursday, November 02, 2023

Electoral Bonds in India: A Corporate Governance Perspective

Posted on November 02, 2023 by admin with No comments
The Election season is upon us again, and it is only fitting that The Supreme Court of India has taken up a clutch of petitions challenging the constitutionality of Electoral Bonds that were introduced in 2017 as a means of donations to political parties. 

The capital involved is expectedly huge. After all, India is the world’s fifth largest economy and the most populous nation that goes through a 5-year election cycle with an overlap between 28 state elections and the national one. Electoral Bonds, as a fund-raising instrument, are primarily targeted towards corporates – including public limited companies except for those run by the government. And while the constitutional bench of Supreme Court headed by the Chief Justice would evaluate it for constitutionality, it is important to conduct an analysis from the perspective of Companies Act 2013 as well as from the purview of good Corporate governance. This article offers an in-depth analysis of these implications. 

Historical Context 
Companies Act, 1956 permitted an entity to make donations to political parties but there were restrictions. Companies were required to pass a resolution and an authorization from the board of directors was necessary. For direct contribution to political parties, it was necessary to have an annual disclosure of the political parties that they have contributed to. And most importantly, the contribution could not exceed 5% of the average profit of preceding three financial years. 

It was also permitted to make indirect contributions to the political parties, such as contributions through an ‘electoral trust’. This route attracted lesser scrutiny and became the most preferred route. Electoral Trust Scheme, 2013 recognized these trusts. Usually, these were non-profit companies that were constituted solely for the purpose of political donations. These trusts merged donations from various entities into one large corpus and then donated to various political parties. Therefore, while it was possible to ascertain which individuals and entities donated to an electoral trust, the donations from the trust to the political parties could not be traced back to them.
The above screenshot is from an interactive infographic at The Hindustan Times. The graphic shows how Satya Electoral Trust and General Electoral Trust garnered huge corpus in the form of electoral donations. This corpus was than used to donate to a variety of political parties. In the case of Bajaj Electoral Trust for example, there is a 1-to-one correlation, but for the majority of the larger trusts it is virtually impossible to ascertain who donated to whom.
  
Regulatory Evolution 
Companies Act, 2013 relaxed the restriction of maximum donation from 5% to 7.5% of the average profit in the preceding three financial years. But the disclosure obligations were not modified or relaxed. The direct route attracted maximum scrutiny and the indirect route through electoral trusts and others remained the preferred mode of donations. Anonymity from public disclosure was allowed to foster, even when majority of the conduits were public listed companies, utilizing money from their reported profits for political donations without disclosing the recipients. 

The Finance Act, 2017, and the Electoral Bond Scheme, 2018, elevated this scheme of things to the next level. Among others, these bills brought in three sweeping changes: 
  • Introduction of Electoral Bonds: A new specialized financial instrument was introduced in the form of Electoral Bonds. This is a promissory note that can be purchased from State Bank of India, and can be donated to a political party within 15 days. The note does not bear the names of either the purchaser or the recipient. While the SBI does comply with the RBI norms of KYC while issuing the Bonds, this information can only be retrieved through a court order. Even then, only the purchaser’s identity is revealed, and not that of the recipient political party. 
  • Anonymity Provision: Electoral Bonds bypassed the disclosure requirements set by the Companies Act, 2013. While the Companies Act, 2013 necessitated that for direct contributions to political parties, identities of both the doner and the recipient must be disclosed, Electoral Bonds allowed for that disclosure to be avoided. In turn, this also made the indirect donation route using electoral trusts somewhat redundant, giving more maneuverability to doners. 
  • Removal of Donation Cap: Most significantly, the Finance Act, 2017 removed the cap on the maximum donation that a company can make. Companies can now donate unlimited amounts, provided they have existed for more than three financial years. 

Legal and Ethical Concerns 
This brings us to the present scenario in the Supreme Court. Since the introduction of the Finance Act 2017 and Electoral Bonds Scheme 2018 various litigants have approached the apex court. The court is reviewing a clutch of these pleas. Reporting on the first day of the hearing, The Economic Times wrote,
Adjudicating on a clutch of petitions challenging the Centre's electoral bond scheme permitting anonymous funding to political parties, a bench headed by Chief Justice of India DY Chandrachud orally remarked that electoral bonds facilitate anonymised "not just in relation to the donee but also in relation to the rest of the society." 
During the resumed hearing, the CJI, speaking for the bench, verbally observed that "in the case of a company, even shareholders won't be told who you are contributing to". 
Earlier this week, attorney general R Venkataramani, in a statement filed in the Supreme Court, had submitted that citizens do not have the right to information under Article 19 (1)(a) of the Constitution regarding the funding of a political party.
But with respect to a listed company the shareholders are not just ordinary citizens. They are invested stakeholders to the company that is utilizing the profits towards the said donations to the political parties. When one considered the fact that all restrictions towards the maximum donation has been removed by the last bill the situation becomes specifically acute. The checks and balances for good corporate governance have been sorely lacking. In an extreme scenario this could potentially mean that a company can disregard its shareholders in entirety while spending all the proceeds and profits towards an anonymous donation to a political outfit. The shareholders will be mere bystanders, lacking any instrument that help them question the decisions of the company management, let alone influence or prevent it. 

Best Practices for Better Corporate Governance 
Therefore, the following Corporate Governance best practices are suggested: 
  1. Avoid Corporate Donations: Companies should refrain from political donations, leaving such contributions to individual promoters and management. Promoters and management may make their choice of donation in their personal capacity, which is different from utilizing company profits, which are shareholder money.
  2. Digital Channels: If unavoidable, use Electoral Bonds for donations as they offer a formal, digital mechanism. To its credit, the Electoral Bonds provide for a more transperant digital mechanism, wherein the recipient political party must use official accounts to collect the donations.
  3. Self-Regulation: Companies should voluntarily cap donations and disclose them to shareholders. Adhering to the previous limit of 7.5% or lower as a benchmark can be a good start. The Finance Act 2017 may not be mandating the maximum cap on donations, but the company must self-regulate and declare to its shareholders the maximum amount up to which it is willing to make donations to political parties.
  4. Board Authorization: Maintain the practice of board approval and full disclosure. The formal procedure of passing the resolution and getting the authorization of the board, as well as robust disclosure obligation of the previous regime encourages good governance, and should be followed even when they are not mandated by the current law.
  5. Transparency in Quid-Pro-Quo: Any potential reciprocal benefits arising from political donations should be reported to the board for review. 

Conclusion 
The ongoing Supreme Court case on Electoral Bonds brings into focus the need for a balanced approach that respects both the political funding requirements and the principles of corporate governance. 
The conflict of interest is apparent in the fact that an elected political government can enact laws that facilitate fund-raising for political parties even at the cost of good corporate governance. The judiciary must do the balancing act for the shareholders and citizens at large. Companies must exercise caution and adhere to best practices to maintain transparency and accountability. 

References and Further reading
Disclaimer: This article is based on legal frameworks and financial data up to the year 2022. GenAI was not used. An intern helped in collating data from the internet and provide references to make this post more accurate. 

Friday, January 24, 2020

Clay Christensen: How Will You Measure Your Life?

Posted on January 24, 2020 by admin with No comments

A tribute to Clayton Christensen, the Harvard professor who introduced "disruption" in his 1997 book The Innovator's Dilemma, which, in turn, led The Economist to term him "the most influential management thinker of his time." 

Even more influential for some would be his 2012 co-authored book How Will You Measure Your Life?. [try here].


Christensen passed away in Boston on Jan 23, 2020.

Saturday, October 13, 2018

The most famous Machine Learning MOOC of our time

Posted on October 13, 2018 by admin with No comments

If you haven't taken the Stanford's Machine Learning MOOC by Prof Andrew Ng on Coursera, you are less likely to be taken seriously in the AI community. Or so they say.

Somewhere in 2008 Andrew Ng started the Stanford Engineering Everywhere (SEE) program that placed a number of Stanford courses online, for free. Andrew himself was responsible for teaching one of these courses, Machine Learning, which consisted of video lectures by him, along with the student materials used in the Stanford CS229 class.

The "applied" version of the Stanford class (CS229a) was hosted on ml-class.org and started in October 2011, with over 100,000 students registered for its first iteration; and became one of the first successful MOOCs made by Stanford professors.

Andrew Ng and Daphne Koller left Stanford to co-found Coursera in 2012. The Machine Learning course was one of the key offerings on the platform. And it continues to be #1 (check here, here, or comprehensively here). 

Wednesday, October 22, 2014

Bezos' Five "Amazing" Points

Posted on October 22, 2014 by admin with No comments
JEFF BEZOS SPENT AN EVENTFUL TIME with his larger Amazon.com engineering team in India recently. The "events", so to speak, involved no less than a typical decorated delivery truck on one hand (The event where, apparently, his amazon.in CEO called out Jeff as his 'Baap' [try here]). And, on the other hand, there was him meeting with the Indian Prime Minister in Delhi and talking about things (in e-retail in the most promising e-global economy with the world's 3rd largest open internet userbase, of course).

In between these two was a private dinner organised with a dozen or so CEO's in Bangalore. This paraphrased post is thanks to one of them [try here] "minuting" the following five points that Jeff talked about among other things.
#1: What was the hardest moment of your life?
Jeff: My experience of raising the first million dollars to start Amazon.
Nothing over the following two decades of founding Amazon compared to that. I reached out to 80 odd investors and how they thought my idea of selling books over the internet was crazy.
#2: How do you hire people?
Jeff: I look at two things: one, does the person consider himself to be fortunate? And two, how good are they at making decisions without data... I'm biased and I prefer people who consider themselves as very fortunate [...] they will make or do things better because they are thankful to the way their lives are shaping up. The others will waste their lives looking over their shoulder and complain about how life is not satisfactory. “Those kind of people I don’t want on my team”. [...] While data is an extremely important element of decision making, you have to first listen to your gut, what feels right. Usually, the gut is right and you have to substantiate it with data. But you should not start the other way round, where you look at data first and then suppress your instinct and do what the data says. That will not necessarily make you do great things. 
#3: Would you hire a philosopher and/or an entrepreneur?
[Jeff pauses for a bit], I would hire a philosopher and not an entrepreneur. [...] a philosopher will take my mind where nobody else has taken it. And then, he will find the entrepreneur to make that into a reality. 
#4: What are the fundamental tenets of your business? 
Jeff: There are three things -
1. Customers rule: That is an obsession at Amazon. At any meeting that we have, we have a chair for the customer. I say, ‘there’s a customer sitting here, and are we doing things right for the customer?’.
2. An incessant appetite for innovation: This has to be there in every walk of life, and it’s not an annual activity, but an everyday thing: we have to do things better.
3. Operational excellence: When you are running a successful corporation, the fundamental building block is phenomenal operational excellence. Everything will happen the way it is planned to happen and that we actually execute and deliver on the promise. 
#5: What next?
Jeff: I’ve only just begun.
(For a perspective, today Amazon ranks #35 in Fortune500 list - compared to Google's #46, and Microsoft's #34). 

Thursday, May 08, 2014

Saturday, August 03, 2013

The Pygmalion vs. The Golem Effect

Posted on August 03, 2013 by admin with 3 comments
There are two kinds of self-fulfilling prophecies. They are broadly defined by wiki as follows:

The Pygmalion effect, or Rosenthal effect, is the phenomenon in which the greater the expectation placed upon people, the better they perform.

On the other hand is the Golem effect, in which low expectations lead to a decrease in performance.
In ancient Greek mythology, Pygmalion fell in love with one of his sculptures, which then came to life. The theme was in the main stray of many English literary works during the victorian era. One of which is George Bernard Shaw's play titled "Pygmalion" from which Rosenthal effect gets its name. In Shaw's play, the protagonist, a professor of phonetics Henry Higgins makes a bet that he can train a bedraggled Cockney flower girl, Eliza Doolittle, to pass for a duchess at an ambassador's garden party by teaching her to assume a veneer of gentility, the most important element of which, he believes, is impeccable speech. (The play is a sharp lampoon of the rigid British class system of the time and a commentary on women's independence.)

When read along with Hawthorne effect, the two behavioral effects above become even more interesting. The Hawthorne effect (commonly referred to as the observer effect) is a form of reactivity whereby subjects improve or modify an aspect of their behavior, which is being experimentally measured, in response to the fact that they know that they are being studied, not in response to any particular experimental manipulation. (Of course, without much doubts the key-words and the theme thus far may have already reminded you of the Quantum double-slit experiment, which in itself is a topic for a new Bubble-game. Meanwhile, try here if you must.)

These effects, among others, constitute the broader macro psychology theory of human motivation and personality called "Self-Determination Theory" which concerns with people's inherent growth tendencies and their innate psychological needs, and attempts to study the motivation behind the choices that people make with/out any external influence and interference.

When applied to modern-day study of the economy, it brings us to the ongoing work by MIT professor Dan Ariely in the field of "behavioral economics". The following TED talk captures his ideas rather nicely around prevalent biases in human decision-making process and the term that he coined to describe the behavior: "Predictably Irrational". (My short book-review of the namesake shall follow as a future post.)


[Dan Ariely: Are we in control of our own decisions?]
NB: This blog entry is an example of "Bubble-game Theory"

Saturday, July 20, 2013

Bubble-Game Theory

Posted on July 20, 2013 by admin with 1 comment
YOU CAN CONSIDER GOOGLE your friend only if the two of you play games with each other -- especially with Google the search box. I call our little game Bubble-game. The rule is simple. You need to come up with a vaguely familiar term that you know from somewhere -- desirably from within the Google Apps ecosystem that you personally use on various gadgets. Again, the only rule is that the term should be only vaguely familiar, if at all. It is not necessary to know the precise spelling.

So then, you turn to Google.com and ask. From within the context of your 'relationship' with Google, the algorithm would suggest to you the possible answers in the form of search results. And depending on how extensively you use Google --or, to put it more socially-- depending on how well Google 'knows' you, you should find traces in the search results that may indicate where you might have encountered the term for the first time and the subsequent info-branches it created thereafter: cached data, search queries, location information and frequently visited places, bookmarks and favourites, frequently visited sites, email and social circles, interactions and conversations you have had -- to mention a few. (For the complete list, you may want to review details in the public domain for project PRISM.)

If you have noticed, Google Now does something very similar albeit behind the scenes. Which in turn defines the bubble that you live and operate within inside a given app ecosystem. These informed results are algorithmically cultivated to "inform" you better. However, in the process, the algorithm assigns weights to certain information snippets to bump them up over others, and in doing so, it alters the reality for you.

It is my theory that over a period of time, pretty much like a chewing bubble gum one can effectively change the shape and size of this bubble. Since it was defined by your own habitual patterns in the first place, it can be redefined also. It would primarily involve controlling and altering one's digital information usage patterns around the given bubble. Typically, a bubble shrinks over time, making your behavior patterns more predictable. As you add milestones to your life such as acquiring a new degree, getting married, adding a newborn to the family, relocating to a new place, changing jobs, etc. would add additional dimensions and info-branching to the existing bubble. A significant effort may allow you to restrict the bubble from affecting your information consumption. However, there seems to be no way to burst the bubble unless the complete dataset is lost or disassociated with your digital identity.

Getting back to the Bubble-game, the term that Google and I played with today is "Rosenthal" (try here) -- a vaguely familiar term that randomly popped up in my head, most probably by unconsciously noticing Umberto Eco's book "The Name Of the Rose" on the bookshelf in the passing. The bubble involves a host of url's, bookmarks, comments, that I happened to capture a couple of years ago.

(PS: Eli Pariser demonstrated the bubble effect in his 2011 TED talk with striking examples. His ongoing research effort is updated on his personal blog - The Filter Bubble.)

Monday, July 01, 2013

"Peter Drucker - Managing Oneself" on SlideShare.net

Posted on July 01, 2013 by admin with No comments
IN THE INTRODUCTORY paragraph of this legendary paper for Harvard Business Review, Peter Drucker writes:
We live in an age of unprecedented opportunity: If you've got ambition and smarts, you can rise to the top of your chosen profession, regardless of where you started out. 
But with opportunity comes responsibility. Companies today aren't managing their employees' careers; knowledge workers must, effectively, be their own chief executive officers. It's up to you to carve out your place, to know when to change the course, and to keep yourself engaged and productive during a work life that may span some 50 years. To do those things well, you will need to cultivate a deep understanding of yourself - not only what your strengths and weaknesses are but also how you learn, how you work with others, what your values are, and where you can make the greatest contribution.
Because only when you operate from strengths can you achieve true excellence.
Marking a small footnote today as this 10-slides synopsis (below) of Peter Drucker's "Managing Oneself" crosses a sort of a mini milestone on SlideShare with a thousand+ downloads from 26k+ views overall since its first publication.
Thank you all.






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