Almost ten years ago, my prediction was, in next ten years neuro dynamic programming language will receive more adoption and become a common computer programming language. Variance in my prediction and actual result is significant. Recent announcement of unmanned car from google is very encouraging that my predication will become a reality one day.
In simple words, in machine learning field, there are two types of learning. Supervised learning and un-supervised learning. Unsupervised learning is a type of learning which makes a system to learn in dynamically changing environment. Neuro dynamic programming language concept is based on unsupervised learning type. Whereas, supervised learning are widely used in voice recognition (in your voice phone directory at office), face recognition and etc. Techniques like neural network, Bayesian learning are used in supervised learning.
Q-Learning, Dynamical programming are some of the techniques available in unsupervised learning. It is a method used by humans to learn and the framework is very simple. In a dynamic environment, the sequence of events are random and an action for the random events is taken. A feedback (reward) for the action is received and based on the immediate and long time reward of the action taken for the random event, a weight is assigned to the action. Based on the exploration and exploitation strategy of the system, weight assigned to the action in the past for the random event, the action is repeated if the same or similar random event happens.
In the current computation paradigm, programming logic is deterministic. In the future, deterministic logic is not sufficient in computation. A car that uses set of techniques to drive itself will be used to learn about that specific car. At any given time, for a given VIN, all the necessary details about the car will be available. It applies to all entities including humans.
Pagerank is an algorithm used by google to assign importance of each page in world wide web. The order of search results depends on the page rank assigned to each page. A web site has multiple pages and page rank assigned to each page in the web site. The page rank of the page depends on number of external links coming to the page and number of links going out of the page. The page rank of an incoming link also plays a role on determining the page rank of the page.
Page rank is used to decide the sequence of search results for a google search. Companies want their page to be at the top of the search result. The easiest way to be at top of the search result is to pay google for the adwords. The sponsored web sites appear above and to the right hand side of its regular search results.
Not all companies can afford to pay google for their Adwords. There is cost effective alternative which requires an understanding of how google works. Google’s internal working knowledge will aid to define analytical (or mathematical) strategies and implemented in the web site to improve the page rank and eventually with more visitors to the web site.
To validate the theory with emprical analysis, a plan with following steps drafted.
- Find a key word that is not in google’s index server
- Create a graph (random graph) and find the initial transition probability
- Evaluate the steady state of transition probability matrix using power methods – Which is the page rank of the graph (I will post the technical/mathematical details in a pdf. It is time-consuming to write matrix and other math notation in word press editor)
- Develop a set of web sites (pages) adhering to the random graph and each web site to contain the new key word
- Allow google crawler to include the new sites in their index server for the new key words
- Search for the new key word and absorb the order of search results
- Report the results
1. A new key word was selected and is given below. There is no google search result for the key word.
2. The random graph (a representation of how web sites are linked to each other) and the graph will be implemented with various blog post and each blog post will have the key word adhering to the graph. Each node of the graph denote a blog posting. The links connecting the nodes are the hyperlinks connecting the nodes.
Note: This page is used for google’s page rank emprical analysis. The links will be created based on the random graph created. This is node #1 which has the key word: xysivabodzinyx , xysivabodzinxy . As per the graph, it links out to page 2, page 4
The next generation computation devices are lurking around in TED as sixth sense devices and labs are experimenting contact lens devices to present the most relevant information in real-time with out manually seeking. The devices will search for relevancy and the present the information to the user. It is very similar to Terminator movie (please watch video carefully at 2.13) where the aliens receive the most relevant information for the given circumstance. The future devices will make the information readily available based on our circumstance, situation, and mood. Well, it is not science fiction any more and it will soon become a reality.
For those future devices, which are currently in experimental labs, the key component is an information gateway. Information gateway will seek relevant information for each user based on location, mood, and circumstance. The information gateway are nothing but the next generation smart phones. These information gateway will replace personal usage of PCs and laptops.
Google strategy team stuck a good balance to compete in the current market with Apple iPhone, RIM’s blackberry and laid basic foundation for information gateway market. Google launched Nexus one as their phone product today to consumer using Android operating system. Nexus one provides easy integration for all social networking tools and techniques. There are more detail comparison done between Nexus one and iPhone and this article focus is to study Google’s strategy and it’s alignment for future technology evolution.
Google’s strategy to provide options to consumer to select the service providers invites more customer base. However, I’m not excited about its pricing strategy. The device cost around $520 per unit. The pricing strategy will not let current iPhone users to migrate to Nexus one and also blackberry users will not quickly migrate to Nexus one since it does not focus more on running business application (like VIN locator, inventory management and etc).
Nexus one is an another great thing for Google but the unit price needs to come down..