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Cloud Computing for Christmas

My second book – R for Cloud Computing : An Approach for Data Scientists is now ready for sale ( ebook). Softcover should be available within a month. Some of you have already booked an online review copy. It has taken me 2 years to write this book, and as always I accept all feedback on how to be a better writer.

I would like to especially thank Hannah Bracken of Springer Publishing for this.

and I dedicate this book to my 7 year son Kush.


Screenshot from 2014-12-10 10:23:45

Everything that is good in me, come from your love, Kush

Imagine a world with many Googles not just one

Screenshot from 2014-11-30 07:46:53In their 2004 founders’ letter[9] prior to their initial public offering, Larry Page and Sergey Brin explained that their “Don’t be evil” culture prohibited conflicts of interest, and required objectivity and an absence of bias


If you can sue the NSA why cant there be a class action lawsuit against Google et al

If the NSA can be sued for collection of data, why cant Google be sued for sharing my data with NSA without my permission.

Any thoughts- anyone who knows Tort law here?

What did the terms and conditions of google’s policy say back then in those good old days of quiet cooperation

What about global liability across different countries (like EU and India)


_ I think there should be a lawsuit to discover more (click the link)

The truth is out there!




How cheap is cloud computing anyway?

So I wanted to really find out how cheap the cloud was- but I got confused by the 23 kinds of instances than Amazon has http://aws.amazon.com/ec2/pricing/ and 15 kinds of instances at https://developers.google.com/compute/pricing.

or whether there is any price collusion between them ;)

Now Amazon has spot pricing so I can bid for prices as well (http://aws.amazon.com/ec2/purchasing-options/spot-instances/ ) and upto 60% off for reserved instances (http://aws.amazon.com/ec2/purchasing-options/reserved-instances/) but charges $2 for dedicated instances (which are not dedicated but pay as you go)

Dedicated Per Region Fee

  • $2 per hour – An additional fee is charged once per hour in which at least one Dedicated Instance of any type is running in a Region.

Google has sustained discounts ( will not offer Windows on the cloud though!)

The table below describes the discount at each usage level. These discounts apply for all instance types.

Usage Level (% of month) % at which incremental is charged Example incremental rate (USD/per hour) for an n1-standard-1 instance
0%-25% 100% of base rate $0.07
25%-50% 80% of base rate $0.056
50%-75% 60% of base rate $0.042
75%-100% 40% of base rate $0.028


Anyways- I tried to create this simple table to help me with it- after all  hard disks are cheap- it is memory I want on the cloud !

Or maybe I am wrong and the cloud is not so cheap- or its just too complicated for someone to build a pricing calculator that can take in prices from all providers (Amazon, Azure, Google Compute) and show us the money!

vCPU RAM(GiB) $ per Hour Type -Linux Usage Provider Notes
t2.micro 1 1 $0.01 General Purpose – Current Generation Amazon (North Virginia) Amazon also has spot instances
t2.small 1 2 $0.03 General Purpose – Current Generation Amazon (North Virginia) that can lower prices
t2.medium 2 4 $0.05 General Purpose – Current Generation Amazon (North Virginia)
m3.medium 1 3.75 $0.07 General Purpose – Current Generation Amazon (North Virginia)
m3.large 2 7.5 $0.14 General Purpose – Current Generation Amazon (North Virginia)
m3.xlarge 4 15 $0.28 General Purpose – Current Generation Amazon (North Virginia)
m3.2xlarge 8 30 $0.56 General Purpose – Current Generation Amazon (North Virginia)
c3.large 2 3.75 $0.11 Compute Optimized – Current Generation Amazon (North Virginia)
c3.xlarge 4 7.5 $0.21 Compute Optimized – Current Generation Amazon (North Virginia)
c3.2xlarge 8 15 $0.42 Compute Optimized – Current Generation Amazon (North Virginia)
c3.4xlarge 16 30 $0.84 Compute Optimized – Current Generation Amazon (North Virginia)
c3.8xlarge 32 60 $1.68 Compute Optimized – Current Generation Amazon (North Virginia)
g2.2xlarge 8 15 $0.65 GPU Instances – Current Generation Amazon (North Virginia)
r3.large 2 15 $0.18 Memory Optimized – Current Generation Amazon (North Virginia)
r3.xlarge 4 30.5 $0.35 Memory Optimized – Current Generation Amazon (North Virginia)
r3.2xlarge 8 61 $0.70 Memory Optimized – Current Generation Amazon (North Virginia)
r3.4xlarge 16 122 $1.40 Memory Optimized – Current Generation Amazon (North Virginia)
r3.8xlarge 32 244 $2.80 Memory Optimized – Current Generation Amazon (North Virginia)
i2.xlarge 4 30.5 $0.85 Storage Optimized – Current Generation Amazon (North Virginia)
i2.2xlarge 8 61 $1.71 Storage Optimized – Current Generation Amazon (North Virginia)
i2.4xlarge 16 122 $3.41 Storage Optimized – Current Generation Amazon (North Virginia)
i2.8xlarge 32 244 $6.82 Storage Optimized – Current Generation Amazon (North Virginia)
hs1.8xlarge 16 117 $4.60 Storage Optimized – Current Generation Amazon (North Virginia)
n1-standard-1 1 3.75 $0.07 Standard Google -US Google charges per minute
n1-standard-2 2 7.5 $0.14 Standard Google -US of usage (subject to minimum of 10 minutes)
n1-standard-4 4 15 $0.28 Standard Google -US
n1-standard-8 8 30 $0.56 Standard Google -US
n1-standard-16 16 60 $1.12 Standard Google -US
n1-highmem-2 2 13 $0.16 High Memory Google -US
n1-highmem-4 4 26 $0.33 High Memory Google -US
n1-highmem-8 8 52 $0.66 High Memory Google -US
n1-highmem-16 16 104 $1.31 High Memory Google -US
n1-highcpu-2 2 1.8 $0.09 High CPU Google -US
n1-highcpu-4 4 3.6 $0.18 High CPU Google -US
n1-highcpu-8 8 7.2 $0.35 High CPU Google -US
n1-highcpu-16 16 14.4 $0.70 High CPU Google -US
f1-micro 1 0.6 $0.01 Shared Core Google -US
g1-small 1 1.7 $0.04 Shared Core Google -US

The Education of Larry Page

From naming the algorithm after himself ( PageRank ?) to forsaking his professors at Stanford ( who legally own the rights to many intellectual property), to first learning under Eric Schmidt and then pushing him out on the pretense of a political appointment to never came, to the era of silent cooperation with the US Government, to collecting a lot of data by assessing the risk of litigation (especially mobile), and to push intellectual property rights between open source and patent rights, to massive expensive lobbying and now even sidelining his brother in arms- Larry Page has emerged as the most ruthless combination of business savvy and formidable technological skills since Bill Gates.

He now owns a representative sample of nearly all the data on video (Youtube) , email (Gmail), website analytics ( Google Analytics), search engine (Google.com), advertising clicks ( Adwords and Adsense), a majority of mobile phones (Android).

And he wants more. To collect data from your thermostat. Your glasses. His government will not file an anti trust case because of national security. As an extension of US foreign policy, he will lead protests against Chinese hackers, censorship and even abandon the market than comply with Chinese Law, but he will gladly pay fines and delete links to comply with European Law.

There are ways to make money that are not evil. But they do not teach what is evil or not, at Stanford. Not even to dropouts.


Informatin Asymmetry is the most evil business

What is information asymmetry?

information asymmetry deals with the study of decisions in transactions where one party has more or better information than the other. This creates an imbalance of power in transactions which can sometimes cause the transactions to go awry, a kind of market failure in the worst case. Examples of this problem are adverse selection,[1] moral hazard, and information monopoly

Most commonly, information asymmetries are studied in the context of principal–agent problems. Information asymmetry causes misinforming and is essential in every communication process

Adverse selection, anti-selection, or negative selection  refers to a market process in which undesired results occur when buyers and sellers have asymmetric information (access to different information); the “bad” products or services are more likely to be selected.

The principal–agent problem or agency dilemma occurs when one person or entity (the “agent“) is able to make decisions that impact, or on behalf of, another person or entity: the “principal“. The dilemma exists because sometimes the agent is motivated to act in his own best interests rather than those of the principal.

Monopolies of knowledge arise when ruling classes maintain their political power through their control of key communications technologies.[3] An example of this occurs in ancient Egypt where a complex writing system conferred a monopoly of knowledge on literate priests and scribes.


  1. This especially is true in enterprise software
  2. and online advertising and spam
  3. and commodities across the globe (oil spikes after iraq, oil slumps after heating oil data, climate data, or even releases from strategic reservoirs)
  4. and internet spying which may be for economic espionage or trade negotiations but are justified as looking for terrorists.
  5. and inflation in the developing and poor countries
  6. and lobbying in the developed and rich countries


People who enable information asymmetry are corrupted people, misled by their own greed and agent-employees in decisions that run counter to the principles when they founded their corporation.

Do you think information asymmetry is evil? Or do you think we should jump on the bandwagon and play the game. Click those ads, while we share your data with the government!


Google Trends for Game of Thrones and Lost

Is Game of Thrones more popular than Lost

Not quite. But its getting there!



Screenshot 2014-06-28 13.22.29


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