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24 Feb Intro to the End of Code

By: Joe Roushar – February 2013

In the Beginning

Punched Card StackWhen computer programming began, it consisted mostly of written computer instructions called code. Data was minimal. Decks of dozens to hundreds of punched cards told the computer what to do with the data, which was also encoded on punched cards. The process of writing and debugging code was tremendously tedious. As computing devices and the art of programming have matured, the balance between code and data has dramatically reversed. It is now common for users to have multiple terabytes of word processing and graphics files that are managed by a few megabytes of code.  Data sources tend to grow quickly. Petabytes of data can be generated, especially in social networking sites, without much code, especially when the data includes rich media video, still image and sound.

Understanding Context Cross-Reference
Click on these Links to other posts and glossary/bibliography references

  

Section 9 Intro

The End of Code Icon

 

Table of Context

The rise of graphical user interfaces (GUIs), and later, mobile computing, had interesting effects on code:

  1. Graphical rendering processes are slower with GUI screens than text-based screens because text can be written to the screen more quickly.
  2. Code grew dramatically to include screen images (in some programs, the interface portions comprise more than half the code).

Blog Section Objectives

This section takes us from the present, where computing is reaching further and further into the realms of thought, into the future, where mechanical thinking or sentient computing will be as commonplace as today’s word processing. To arrive at that future, though, we must first get past the model in which the dominance of code makes process “king”. How do we do that? Here are the steps we take in our journey to the snackbar at the end of code:

  1. Early on, I will try to describe code, database systems, and techniques. As I look at Programming Paradigms and Database Models  you will see ideas reminiscent of other  sections, especially “Cybernetic Modeling” and its AI approaches. In this section, I intend to go back to the computing basics.
  2. After looking at database systems and techniques, I’ll look at object-oriented programming (OOP) and Service-Oriented Architectures (SOA). These posts will provide a primer on the value of OO techniques, including how they compare to the paradigms described in the sections on programming and database models, as well as big data.
  3. Next, I will deal with the importance of expressiveness and patterns, which brings us back to neuromorphic and cognitive models for treating information in brain-like ways.
  4. Finally, I’ll introduce a complete model for sentient computing in which content is “king” and processes are selected by the context of the content, rather than vice-versa.

Artificial Intelligence SymbolsIf you can hang with me for  awhile, I promise you a deeper look at some of the ideas that will shape the real information revolution, which is just around the corner. Some of the ideas in these posts are pretty basic, but others are complex, radical, even controversial. The whole idea of sentient computing will certainly make some people cringe. The camps are firmly divided on many of the subjects I try to take by the horns. As you probably guessed, I reserve the right to take a stand, and yes – context is central. But this is just the starting point of the discussion.

Kafatos and Nadeau inform us that physical theories in a quantum mechanical universe do not exist beforehand outside “the mind that conceives and applies them” (p. 91). They talk about how language, culture, science and religion combine to create a framework within which the theories (and effectively-the universe) can take shape and live. They admit that “a commitment to epistemological and metaphysical realism” leads us to acknowledge that a pre-scientific ontology “‘happened’ to serve the progress of science quite well” (p. 108). Armed with these clear assessments, I have taken a pragmatic approach, and built a model around classic premises, with the insertion of quasi-random doping agents, to deliver what I believe to be the magic carpet that leads through the door at the end of code.

Please look in every now and then, and see if you can suspend disbelief for long enough to find a gem that is more than just entertaining.

Click below to look in each Understanding Context section


 

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