Saturday, December 10, 2016

Benefits of static web sites hosted on Google Cloud Storage, Azure Storage, or Amazon S3

Most of my sites have no dynamic content but I often still hosted them as a Ruby Sinatra app or use PHP.

A few years ago I experimented with using the static site generator Jekyll but still hosted the generated site on one of my own servers using nginx. After a while I decided to revert the site to its old implementation as a Sinatra web app (even though the site was always static, that is, no server side actions required except for serving up static HTML, JS, and CSS files).

I am now using a far superior setup, and I am going to document this new setup to document it for myself, and perhaps other people may find this useful also:

I chose to use Google Cloud Storage for personal reasons (I used to work as a contractor at Google and I fondly remember their infrastructure, and using GCP is slightly similar) but using Amazon S3 or Microsoft Azure is also simple to set up.

Start by installing Harp and a static site local web server:

npm install -g harp
npm install -g local-web-server

Harp by default uses Jade, and I spent about 10 minutes of "furious editing" for each of my static sites to convert to the Jade format from HTML, ERB, or PHP files. This is optional but I like Jade and I thought that long term it would save me maintenance effort using Jade. As you edit your site use "harp server" to test the site locally. When you compile a web site using "harp compile" a subdirectory www is created with your static site ready to deploy. You can test the generated static site using "cd www; ws" where ws is the local web server you just installed.

You need to create a storage bucket with your domain name, which for this example we will refer to as DOMAIN.COM. I created two buckets, one DOMAIN.COM and one www.DOMAIN.COM and for www.DOMAIN.COM I created a single index.jade file (that gets compiled to www/index.html) that just has both a HTML redirect header and Javascript for a redirect to DOMAIN.COM.

The only part of this process that takes a little time is proving to Google that you own the domain, if you have not done so in the past. Just follow the instructions when creating the buckets and then copy your local files:

cd www
gsutil -m rsync -R . gs://DOMAIN.COM
gsutil defacl ch -u AllUsers:R gs://DOMAIN.COM

I had to also manually set the static files copied to GCS to have public access. You will have to change the DNS settings for your site to create a CNAME for both www.DOMAIN.COM and for www.DOMAIN.COM pointing to Whenever you edit a local file use "cd www; gsutil -m rsync -R . gs://DOMAIN.COM" to re-sync with your GCS bucket.

After waiting for a few minutes test to make sure your site is visible on the web. For one of my sites I also used a free Cloudflare service for HTTPS support. This is very easy to setup if you already have a Cloudflare login. Just add a free web site and make the same to CNAME definitions pointing to and then Cloudflare will give you two DNS servers of their own that you need to use instead of whatever DNS service you were using before. 

Saturday, November 19, 2016

My new Haskell book Haskell Tutorial and Cookbook now available

My new Haskell book Haskell Tutorial and Cookbook  is now available for a minimum price of $4.

This book has a Creative Commons share and share alike, no commercial use license - so you can legally (and with my blessings) share it with your friends.

Monday, September 05, 2016

Great short video by Douglas Rushkoff that summarizes his latest book 'Throwing Rocks at the Google Bus'

Those of you who know me in "real life" might remember me talking about how much I enjoyed Rushkoff's newest book that was published recently. Well, he just put out a short video that summarizes many of the useful and interesting best-parts of the book: YouTube Link

I especially like the part where he explains why family owned businesses are so much more stable than other businesses. Makes sense. He also explains the flow of how the economy has worked since the dark ages, and how modern technology platforms, while a mostly good thing, necessitate doing things differently now, or else.

Anyway, enjoy the video, or not :-)

Wednesday, August 24, 2016

The Julia programming language: amazingly nice

Well, at least I am amazed. I took a brief look at Julia a few years ago but since I understood it to be somewhat derivative of GNU/Octave (or Matlab) and R (I sometimes use GNU/Octave, but not often), I only gave Julia a very short look.

Fortunately, a current customer uses Julia so I have been ramping up on the language and I very much like it. A bit off topic but I would like to give a shout-out to the O'Relly Safari Books Online service which I recently joined when they had a $200/year guaranteed for life subscription price (half regular price). I am reading "Getting Started with Julia" by Ivo Balbaert which is fine for now. I have "Julia for Data Science" by Zacharias Voulgaris and "Mastering Julia" by Malcolm Sherrington in my reading queue. When learning a new technology having up to date books available really is better than finding information on the web (or at least augmentation to material on the web).

I very much like the tooling for Julia. Julia is a new language but there are already many useful libraries available. Julia uses github for storing modules in the standard library and the integration works very well, at least on Ubuntu Linux. So far, I have been happy just using GNU/gedit for development. I haven't tried Julia on OS X or Windows 10.

The Julia repl is great! Color coding and auto completion are especially well done.

I like just about everything about the Julia language except for 1-based indexing of matrices. Oh well.

Julia is readable, functions are first class objects and programming in Julia is very "Lisp like." With optional type hints (mostly in defining function arguments) Julia is a very high performance language. I love developing in Ruby but I do dream of much higher performance. Julia does not seem like a complete replacement for Ruby (for me) however. That might change.

In addition to doing work with Julia, I have also been experimenting with lots of little coding projects: the Merly web framework (simple, sort of like Sinatra), using the standard HiddenMarkovModels library, and experimenting with a few of the neural network libraries. All good stuff.

Sunday, August 21, 2016

My prediction: Immersive real-time VR in Olympic closing ceremonies in 8 years

My wife and I are watching the closing ceremonies right now. Great visual effects that will be even better with immersive virtual reality. I expect that in 8 years we will have the option of being able to change our point of view from the stands to down on the central floor in a complete immersive VR experience with 3D sound and head tracking.

I haven't worked in VR in almost 20 years when I helped found the virtual reality systems division at SAIC (where I handled 3D sound with head related transfer functions, motion, haptics, and some graphics) and then a year later did a virtual reality project for Disney while working at Angel Studios. Even if I don't work in VR anymore I am a huge fan and I have high expectations for what is to come in user experience.

Sunday, August 14, 2016

I was surprised that so many of the NACL 2016 papers described deep learning projects

I attended the North American Chapter of the Association for Computational Linguistics conference last June in San Diego. Here is a link to the published papers.

The conference was great. The keynote talks, panel discussions, and the talks I attended were interesting! As an independent consultant I payed my own way to the conference and I found it to be a good investment. Sometime I would enjoy attending a European chapter of the ACL conference.

Saturday, August 13, 2016

Some new love for Scala and Python

I am a practical developer. I do have my favorite programming languages (Ruby, Haskell, Clojure, and Java) but I tend to look first at what libraries are available in different languages for whatever project I am currently working on.

I did a lot of work in machine learning in the 1980s (mostly in neural networks) and since then I have probably spent about 30% of my work time directly working on machine learning problems. That has changed in the last few years since several of my consulting customers wanted help spinning up on machine learning.

I have used Scala a fair amount but it has never been a "favorite language," mostly because I didn't care for the tooling. Now I find myself motivated to use Scala because of the awesome Apache MLlib and Breeze machine learning libraries. Also, I have solved my "tooling problem" for Scala development; if you are interested here is my setup: I use a remote high-memory, high-CPU server instance for fast builds. I used to use IntelliJ for Scala development but now I just keep a SBT console open and use Emacs with Ensime and sbt-mode using SSH shells. This is a simple setup but now I am happier using Scala.

I have also been spending a fair amount of time with Google's TensorFlow deep learning tools and the easiest path to solving problems with TensorFlow is working in Python. If you are interested, I do almost all of my work with Python using the free community edition of PyCharm.

So, in general I am trying to avoid the "want to use my favorite programming language trap." The joy is in solving problems and not in wanting to use a favorite language and software stack.

Friday, July 15, 2016

Using TensorFlow Deep Learning neural network with the University of Wisconsin cancer data set

My example of using a TensorFlow Deep Learning neural network to build a prediction model using the University of Wisconsin cancer data:

This short example also shows how to use CSV files with TensorFlow. It took me a short while getting my data in CSV files into TensorFlow so hopefully this complete example, with data, will save people a little time.

Look at the source code for a documentation link if you want to change default parameters like using L1 or L2 regularization, etc.

Friday, June 10, 2016

Action items after attending the Decentralized Web Summit

I attended the first six hours of the Decentralized Web Summit  on Wednesday (I had to leave early to attend a family event). Great talks and panel sessions and it was fun to have conversations with Tim Berners-Lee and Vint Cerf, and also say hello to Cory Doctorow. I would like to thank all of the people I talked with during breaks, breakfast, and lunch: good conversations and shared ideas. The basic theme was what can we as technologists do to "lock open the web" to prevent governments and corporations from removing privacy and freedoms in the future.

There was a lot of discusion why the GPL is a powerful tool for maintaining freedom. The call to action for the summit was (quoting from the web site) "The current Web is not private or censorship-free. It lacks a memory, a way to preserve our culture’s digital record through time. The Decentralized Web aims to make the Web open, secure and free of censorship by distributing data, processing, and hosting across millions of computers around the world, with no centralized control."

I have been thinking about my own use of the Internet and the trade-offs that I sometimes make in order to have an easier and more polished web experience and things that I will try to do differently. My personal list of action items, which I am already starting is:

  1. Separate my working use of computers from my mobile experience: on my Linux laptop, setting maximal privacy settings on IceCat (privacy tuned Firefox) and avoiding social media use (Twitter, Facebook, and Google+). I also use Fastmail for most email that does not involve travel arrangements.
  2. For convenience travelling, I allow myself on my Android phone to use Google Inbox for email related to travel arrangements, Google Now alerts (travel reminders, etc.) and generally use social media. I have been merging all of my email together but I have now started to keep GMail distinctly separate from my personal email account on Fastmail.
  3. Re-evaluating the use of Cloud Services. I am experimenting with using GNU Note (GNote) for note taking on my Linux laptop. I am continuing my practice of encrypting backups (saved as date-versioned ZIP files) before transferring to OneDrive, Dropbox, and Google Drive. I have been using three Cloud storage services to effectively have three backup locations.

Modern smartphones are not privacy friendly devices and I decided to just live with some compromises. On the other hand, on my Linux laptop used for writing and consulting work, I am attempting to take all reasonable steps to maintain privacy and security.

Tim Berners-Lee mentioned the W3C Solid design and reference implementations for decentralized identity, authorization, and access control. The basic idea is to have common decentralized data for a user that is secure and private, and can be used by multiple clients by each user, using their secure data.

In the past, I have tried running my own instance of Apache (used to be Google) Wave and asking family and friends to use it as our personal social media. To be honest, people I know mostly didn't want to use it. Since I view my smartphone as already "damaged goods" as far as privacy goes, I will continue using it to check social media like Facebook, Google+ and Twitter. I have been trying to use GNU Social more often (my feed is I do use GNU Social on my Linux laptop.

Last week a friend of mine asked me why I care about privacy and protecting the web against corporate and governmental over reach. That is not an easy question to answer with a simple short answer. Certainly, laws like Digital Millennium Copyright Act have a chilling effect of making it legally dangerous for security experts to evaluate the safety of electronic devices like medical treatment, etc. Studies have shown that the lack of privacy has a chilling effect on using the rights of free speech. In addition to my own practices, as an individual one of the best things that I do to help is in making donations to the FSF, EFF, ACLU, Mozilla, and

Wednesday, June 01, 2016

As AI systems make more decisions, we need Libre Software now more than ever

I have been using AI technology on projects since the 1980's (first using mostly symbolic AI, then neural networks and machine learning) and in addition to the exponentially growing progress the other thing that strikes me is how a once small AI developers community has grown by perhaps almost three orders of magnitude in the number of people working in the field. As the new conventional wisdom goes AI services will be like cloud computing services and power: ubiquitous.

As AI systems decide what medical care people get, who gets mortgages and at what interest rates, the ranking of employees in large organizations, nation states automatically determining who is a threat to their power base or public safety, control of driverless cars, maintain detailed information on everyone and drive their purchasing decisions, etc., having some transparency in algorithms and software implementation is crucial.

Notice how I put "Libre Software" in the title, not "Open Source." While business friendly permissive licenses like Apache 2 and MIT are appropriate for many types of projects, Libre Software licenses like the GPL3 and AGPL3 will ensure that the public commons of AI algorithms and software implementation stays open and transparent.

What about corporations maintaining their proprietary intellectual property for AI? I am sensitive to this issue but I still argue that the combination of a commons of Libre open source AI software with proprietary server infrastructure and proprietary data sources should be sufficient to protect corporations' investments and competitive advantages.

Monday, May 16, 2016

Writing technical books: the craft of simplifying ideas

I am in the process of writing a fairly broad book on setting up a laboratory for cognitive technology / artificial intelligence. I don't find writing to be easy but I enjoy the process a lot. The main problem that I have is removing unnecessary materials and ideas, leaving just enough so readers can understand the core ideas and experiment with these core ideas using example programs. Unnecessary complexity makes understanding difficult and generally does not help a reader solve their specific problems.

If a reader understands the core ideas then they will know when to apply them. It is easy enough, when working on a project, to dig down as necessary to learn and solve problems but the difficult thing for most people is knowing what ideas and technologies might work.

In my field (artificial intelligence) the rate of progress has accelerated greatly, leading to much complexity and thus increasing difficulty just to "keep up" with new advances. I organize my thoughts by using a rough hierarchy of classes of useful technologies and form a taxonomy by mentally mapping problems / applications to the most appropriate class in this hierarchy. When I read a new paper or listen to a talk on YouTube, I try to place major themes or technologies into this hierarchy and when someone describes a new problem to me, I try to match the problem with the correct classification in my hierarchy of solutions / technologies. Vocabulary is important to me because I organize notes in small text files that might contain a synopsis of a web page with a URI, a business idea, interesting ideas from reading material, etc. Key vocabulary words are the search terms for finding relevant notes.

Monday, April 04, 2016

I am enjoying my business trip in Singapore

Singapore is a great place: a well run country that caters to business.


After a surprisingly easy trip from Arizona to Singapore I am getting settled in. No jet lag today! I took a very long walk first thing this morning and took a few pictures:!56414&authkey=!AJdcHJmgLjMlwWM&ithint=folder%2c 

The first picture is the sunset from 30K feet starting to descend into the Hong Kong airport, then a picture after landing. Carol and I have been in Hong Kong, so that was nice and familiar. I didn't have a window seat landing in Singapore, so no photos from the air. The other pictures are from outside my hotel in Singapore, deep inside the MRT (rapid transit center), and generally around the neighborhood. Singapore has a very nice feel about it. Everything from airport services, port of entry, transportation, hotel accommodations, etc. is well-run, friendly and first rate!

Late morning I took a second long walk, so some more pictures:!56426&authkey=!APSbUaijMVgBxOo&ithint=folder%2c 

The Indian Temple in the pictures was open for some sort of service today. I took off my shoes then entered it. There was a holy man in a loin cloth near the entrance and he greeted me warmly enough so I felt comfortable staying in an out of the way place and meditated a bit. Nice place. I didn't take any pictures inside the Temple because I remember that in India in Jain and other temples that photography was not appreciated. Inside, there were many pictures and sculpture reliefs of Ganesha the elephant God and you can see similar on the close up picture of the Temple roof.

Late this afternoon, I wanted to get a little more site-seeing in before my work week starts tomorrow morning so I walked to the Buddha Tooth Relic Temple and Museum: 

Before leaving my hotel I visited a rooftop garden in the hotel and while I was there it started monsoon-strength rains - a very sudden event since it had been sunny all day. I waited under an umbrella in the garden for the heavy rain to stop and then did the walk in a light drizzle. The Buddha Tooth Relic Temple was packed with people, a few tourists but mostly devotionals.


I started work today. I am here for two weeks and I am enjoying working on a great project.

Monday, March 21, 2016

In defense of iPads as productivity devices

I often hear or read people referring to iPads as toys. I don't agree.
I use my iPad Pro as a "productivity device." Multiple SSH terminals open at the same time to my servers, the publishing system I now use to write my books, cloud based note taking and research (using Google Keep, Evernote, Word and Notes, etc). I also read eBooks, listen to audio books, and my wife and I use it to watch Hulu TV, Netflicks, HBO Go, and purchased Google Play movies and TV shows.
I find the iPad an awesomely useful device. I only use my laptops for software development and since I use Emacs for Lisp, Haskell, and Ruby, with multiple SSH terms that I can flip between quickly, the device also supports programming.
I do spend a fair amount of time in IDEs like RubyMine and IntelliJ on one of my 4 laptops, but I just prefer mobile devices whenever I can use them. In addition to my iPad Pro, I also get a lot of use out of my iPad mini 4 and Android Note 4 phone. The trick is having all of my data available on all devices and realizing that most value of a knowledge worker (software developer in my case) comes from thinking to understand problems rather than typing on a keyboard.

Wednesday, March 09, 2016

History in the making: first Lee Sedol vs. AlphaGo match game

I was up to 1am this morning watching the game live. I became interested in AI in the 1970s and the game of Go was considered to be a benchmark for AI systems. I wrote a commercial Go playing program for the Apple II that did not play a very good game by human standards but did play legally and understood some common patterns. At about the same time I was fortunate enough to get to play both the woman's world Go champion and the national champion of South Korea in exhibition games.

I am a Go enthusiast!

The game played last night was a real fight in three areas of the board and in Go local fights affect the global position. AlphaGo played really well and world champion Lee Sedol resigned near the end of the game.

Saturday, March 05, 2016

OK, now I remember why I like Ruby: reading through the code for the Reality Wikipedia/DBPedia interface

I have been diving deep this year using Haskell, largely in working on examples for the Haskell tutorial and cookbook-style book I am writing. I was revisiting some of my own (old) code for using Wikipedia/DBPedia data and I ran across the very nice Reality library which is written in Ruby. Reality is so very much better than my old code and I enjoyed looking at the implementation.

Ruby and Haskell complement each other in the sense that they are in the opposite ends of programming languages spectrum. If you were forced to only use two programming languages Ruby and Haskell would be good choices. Ruby, like Clojure, has ready access to the vast Java ecosystem via JRuby so the combination of Haskell and Ruby really does cover the bases.

The ability to integrate real world data as found in Wikipedia/DBPedia into systems is a powerful idea. In building AI systems, large companies like Google, Facebook, and Microsoft preprocess and use available world knowledge (I worked for a while with the Knowledge Graph at Google, so I know their process and I assume that Microsoft and Facebook are similar), however, for small organizations and hobbyists/enthusiasts caching and indexing the world's knowledge just isn't possible but some of the same effect can be had by making live API calls to DBPedia, Wikidata, etc.

While I appreciate the work the 800 pound gorillas (Google/Microsoft/Facebook) are doing, I also hope that a rich cooperating ecosystem of small organizations continues to also claim relevance in building systems that help everyone integrate their own data / knowledge / experience with the deep knowledge that we all (hopefully) contribute to on the web.

I find myself pushing back against the "gorillas" by preferring, when feasible, to participate in community efforts. A good example is using GNU Social as a partial replacement to Google+, Facebook, and Twitter (you can follow me on GNU Social at In a similar way, I hope that developers contribute to and use good open source projects that support deep knowledge management, deep learning (yeah, "deep" is probably used too often), and AI in general.

In a world where global corporate powers centralize power and control, I believe that it becomes more important for people to make personal decisions to support local businesses, care about the financial and environmental health of their local communities, and continue to use the Internet and the WWW to promote individualism and community, not globalism.

Tuesday, January 26, 2016

Great talk on Spark

I just listened to an ACM sponsored talk Making Big Data Processing Simple With Spark by Matei Zaharias. You may need to be an ACM member to watch the webinar. I first joined ACM in the mid 1970s - recommended.

For handling huge datasets Spark is evolutionary or revolutionary depending on your point of view. A bit of personal history before I talk specifically about Spark:

In the late 1980s I was an architect and developer on a multinational project to use seismic data from 38 data collection stations to detect atomic bomb tests. All of our data handling software was custom; if we had Spark, or even Hadoop, we would have saved a ton of effort. Similarly, in the 1990s I was tech lead on a fraud detection system that used massive real time telephone records data sets. Modern infrastructure would have saved a lot of time and money.

My first serious use of map reduce was processing large Twitter data sets at Compass Labs. We used Hadoop on Amazon ElasticMapreduce. Later when I worked as a contractor at Google, in addition to using map reduce, I was introduced to realtime interactive tools like Dremel that made it easy to interactively use large data sets.

With Spark, everyone gets to interactively work with massive datasets! I think that Spark is evolutionary in that it builds on and plugs into existing work like the Hadoop File Sytem and supports familiar map reduce style operations. I think that it is revolutionary in the memory based distributed architecture and application programming model. Spark was designed based on limitations of map reduce systems like Hadoop that while providing easy to use programming models, have ineffiencies in data access. With Spark, you have an easy to use programming model, more efficiency, and built in interactivity. I have examples of using Spark in my last book Power Java. You can experiment with Spark on your laptop and only worry about accessing a cluster when you need to scale.

Saturday, January 23, 2016

Simple Haskell: using a sqlite3 database

I have been using Lisp languages professionally since the early 1980s. While I now use Java, Ruby, and Clojure for much of my work, I have been slowly been getting up to speed using Haskell over the last 5 years. My difficulties using Haskell are caused almost 100% when I need write impure Haskell code. This occasional discomfort is made up for by the fun and productivity of writing pure Haskell code. Using haskell-mode in Emacs I get the same happy feeling writing pure Haskell code that I used to get using Common Lisp, Scheme, and Clojure - and with the advantages of a strongly typed language!

I like to mock up test data and write the pure code first and then write impure code that needs to access the web, RDF data stores, relational databases, file IO, etc. For me, as a student of Haskell, this is the easiest way to write Haskell programs.

About 15 years ago, in one of my Java artificial intelligence books I wrote an example program that provides a natural language processing (NLP) interface to relational databases. I have decided that I would like to do the same, but in Haskell, and take advantage of what I have learned in the last 15 years. Writing the code to convert natural language queries into SQL queries is pure Haskell code (given mockup data for database metadata and sample table data, and test NLP queries) and I am enjoying working on that. Eventually I will need to write some impure code that accesses the popular databases. To make the initial development as easy as possible (a good idea since I may never totally finish this side project) I have decided that I will use sqlite and the sqlite-simple library. For the first proof of concept/prototype, I don't expect to need much impure code. A good thing!

This reminds me of a comment Erik Meijer made when he was teaching the edX functional programming class. He said that as developers we can think of pure Haskell code a being islands and impure code that has to maintain state and interact with the world as the ocean containing the islands. I like this metaphor!

I write little code snippets (or sometimes mini-projects) to experiment with nonpure Haskell code and the following listing, derived from the sqlite-simple library, contains the small experiments with the functionality that I need for now. I thought it was worth sharing in case this saves anyone else some time:

{-# LANGUAGE OverloadedStrings #-}
import Database.SQLite.Simple

   Create sqlite database:
     sqlite3 test.db "create table test (id integer primary key, str text);"

   This is derived from the example at

main :: IO ()
main = do
  conn <- open "test.db"
  -- start by getting table names in database:
    r <- query_ conn "SELECT name FROM sqlite_master WHERE type='table'" :: IO [(Only String)]
    print "Table names in database test.db:"
    mapM_ (print . fromOnly) r
  -- get the metadata for table test in test.db:
    r <- query_ conn "SELECT sql FROM sqlite_master WHERE type='table' and name='test'" :: IO [(Only String)]
    print "SQL to create table 'test' in database test.db:"
    mapM_ (print . fromOnly) r
  -- add a row to table 'test' and print out the rows in table 'test':
    execute conn "INSERT INTO test (str) VALUES (?)"
      (Only ("test string 2" :: String))
    r2 <- query_ conn "SELECT * from test" :: IO [(Int, String)]
    print "number of rows in table 'test':"
    print (length r2)
    print "rows in table 'test':"
    mapM_ print  r2
  close conn

Just to make this example complete, here is my stack.yaml file:

resolver: lts-4.0
packages: - '.'
extra-deps: []
flags: {}
And here is my sqlite.cabal file:
name:                sqlite
synopsis:            Experiment with sqlite-simple
description:         Derived from example in
license:             Apache2
license-file:        LICENSE
author:              Mark Watson
copyright:           2016 Mark Watson
category:            Web
build-type:          Simple
-- extra-source-files:
cabal-version:       >=1.10

executable test1
  hs-source-dirs:      .
  main-is:             test1.hs
  ghc-options:         -threaded -rtsopts -with-rtsopts=-N
  build-depends:       base
                     , sqlite-simple
  default-language:    Haskell2010

Here is a build and sample run (assuming that the sqlite database test.db has been created as per the comments in the first source listing):

✗ stack build
✗ stack exec test1
"Table names in database test.db:"
"SQL to create table 'test' in database test.db:"
"number of rows in table 'test':"
"rows in table 'test':"
(1,"test string 2")
(2,"test string 2")
(3,"test string 2")

I would like to thank Janne Hellsten for maintaining the sqlite-simple library and I would also like to thank the developers of stack. Using stack has solved most of my build issues with Haskell. Thanks!

Thursday, January 14, 2016

I will not vote for Hillary Clinton. I reject the "lesser of two evils" argument.

I believe that Hillary Clinton is in the pocket of Wall Street, a lacky by any definition. I also believe that she is, as Ralph Nader says, a poster child for the military industrial complex. I also don't like her close ties to agribusiness giant Monsanto and her advocacy for the industry's genetically modified crops.

I believe that our two party system is broken, almost never giving us a choice that matches the preferences of the electorate. Corporate news corporations favor Clinton over Bernie Sanders in subtle and unfair ways, basing so much of their slanted (as directed to the financial interests of the network owners) discussion in terms assuming Hillary Clinton will be the Democratic candidate and pushing the false narrative that Bernie Sanders has no chance of winning the general election.

Some of my friends who are Democrats believe that it is a mistake to not vote for whatever Democratic toadie the establishment runs. What if a Republican wins? Oh NOoos! The sky will fall.

I believe that the sky will fall on our representative democracy if people don't stand up to the political establishment and the corporations that their preferred candidates represent.