Change the Mirror

Things I can change
Rate of Change
Things I can change slowly Things I can change quicker
Executing Change Training Build Buy
Need for Change Ambition Money Passion
Things I cant change
Things I need not change Things that are too expensive for me to change
Executing Non- Change Ignore the thing to be changed Outsource the task to be changed

Heaven is a place on Mars

A few years ago, on a flight, in a land far far away, I was asked by a another person, What do you think we should do. I said, lets go to Mars.Why is that? the man asked. Because, I paused and said, this planet is going to run out of resources.

Perhaps that is what we should tell the Russians and Chinese and the Anglo-Saxons to do. Kill ISIS together, stop fighting over the Arctic, and reignite the battle to make empires but on Mars.

One more thing, climate change is the 100 billion dollar opportunity. Any startups willing to hack climate change?

Think of the market opportunities, yall.



Data Science to kill and Data science to sell

My computer science professor at University of Tennesse tried to teach me genetic algorithms. I managed to score an A thanks to the brilliance of my team member who created a genetic algorithm using C. For some reason the loveable professor had something against C ++. Real men talk to the metal using C.

Anyways the professor had this theory to say about computer science. He said computer science had two principal sources of revenue.  One is increase kill ratio. The other is to make people sing your tune.

Department of Defense consumes the maximum revenue a nation produces globally across most nations and it funds the maximum data science atleast in the USA.  Making people click you ad is the other source that data science gets funded for. Apparently there is history involved here.  The Italian navy funded Galileo’s telescope ( but stood aside when the Pope disagreed). DARPA funded the internet. Insert here- standard joke on Al Gore inventing the internet.

Principal sources of data for this signal intelligence (sigint) fueled data science comes from telecom, websites and sensors. Principal sources of analysis is actually a huge amount of reports (written on conversations with humint) that are better of  mathematically text mined but are in practice dissected one by one.

Real intelligence begins when no guns are fired. The cold war on the internet is a real threat to free internet and cyberwar is just a way to combine kill ratios for servers to data sourced from ads.

In the meantime, I prefer the maths of Good Will Hunting than the maths of Patriot Games. I prefer the music of Bourne again.



Java by Code Academy

I love the Java by Code Academy course, even though it is very new and quite possibly one of the first of many Java courses that hopefully appear on this beloved website. I crossed 800 points today on CodeAcademy.

Summaries  from Code Academy on Java- these are sourced by the nifty help provided and are cited to Code Academy ( how does one cite it!)

Java is an object-oriented programming (OOP) language, the coder can design classes, objects, and methods that can perform certain actions. These behaviours are important in the construction of larger, more powerful Java programmes. Java is a programming language designed to build secure, powerful applications that run across multiple operating systems. The Java language is known to be flexible, scalable, and maintainable.


  • Data Types are int, boolean, and char.
  • Variables are used to store values.
  • Whitespace helps make code easy to read for you and others.
  • Comments describe code and its purpose.
  • Arithmetic Operators include +, -, *,/, and %.
  • Relational Operators include <, <=, >, and >=.
  • Equality Operators include == and !=.



Control flow allows Java programs to execute code blocks depending on Boolean expressions.

  • Boolean Operators: &&, ||, and ! are used to build Boolean expressions and have a defined order of operations
  • Statements: if, if/else, andif/else if/else statements are used to conditionally execute blocks of code
  • Ternary Conditional: a shortened version of an if/else statement that returns a value based on the value of a Boolean expression
  • Switch: allows us to check equality of a variable or expression with a value that does not need to be a Boolean


Garbage Collection in a technology startup

Garbage collection (GC) is a form of automatic memory management. The garbage collector, or justcollector, attempts to reclaim garbage, or memory occupied by objects that are no longer in use by the program. Thats garbage collection from Jimmypedia. When you dont do enough garbage collection in a program you can end up with Stack Overflow.

Tech Startups have garbage collections too. A garbage collector looks only for garbage. In the edges, on the floor, below the carpet, under ths stairs. In meetings, in team discussions, in stock options, in business plans, in cash burn projections. These are negative anti social emotionally dysfunctional people. Their over abundant IQ (Intelligence Quotient)is balanced by their teenager like EQ ( Emotional Quotient). To balance the cyncial Einstein, you generally need a shiny eyed startup founder who has dreams of ringing the NASDAQ bell every night.

Tech Startups also have unicorn catterpillars. These are people who think they will shed their legs, wrap them in a silky cocoon and become unicorn butterfliess with wings. The shiny eyed founder can become an unicorn butterfly very fast, till the garbage is collected from the cocoon and the oyster returns to being an oyster than turning into a pearl.

Tech Startups have over caffienated engineers and under caffienated salesmen. I wonder how the industry would react if they introduce mandatory drug testing for startups. Maybe we will all migrate to Canada under a Treudian utopia of hemp and grass.


Web Analytics is funny statistics

I have a simple question for my Web Analytics software. I want to know who is reading what, and how much are they being impacted ?

In return my Web Analytics gives me dashboards that can be line charts, bar plots, path diagrams (including Google Analytics).

  • Some questions for my Web Analytics to answer-
  • Will it count 500 CEOs reading my blog as less significant as 5000 college students. Thats not a problem if I am on a social network or is it?
  • I get 15000 unique viewers every month . How many people is that? Does that mean the same 500 people visited every day. Does it mean every day a different 500 people visited. Yes I know Google Analytics has some kind of pie chart (horrible) split and returning and new users- but HOW MANY PEOPLE DID I reach?
  • What did they do after the read my blog? Where did they go? Google shares Adsense revenue. Can it share data too- lets call it DataSense. Even create a new internet data bureau (like we have credit data bureau for financial data)
  • How can I use the web analytics software to give me a forecast of future traffic ( by a time series plot with an added regressor of number of posts per category type ?)
  • How can I get some ANALYTICS to take a decision from the web analytics- (A Siri for Web Analytics?-  You last posted X days ago. Please consider posting. Please consider delaying posting to a more appropriate time?)
  • Is there more to life for a blogger than views and visitors. Is there some way we can measure satisfaction?
  • Is there a SEO penalty for boasting on blog traffic boasting when meeting another blogger. Is there a SEO incentive for openly sharing your web statistics
  • Can Google Analytics give a big data dump for open data analytics (sigh). Can you use custom JS libraries for making your own dashboard with GA

Screenshot from 2015-10-22 08:01:27