10 posts
   IBM's Watson is a computing system that became famous in 2011 for beating human champions at the televised game Jeopardy. This game, as most of you know, involves answering questions on a variety of subjects. Contestants can win up to one million dollars.  Watson fits into this picture as a question and answer system. Where Web search engines take key words and deliver mountains of links to possibly relevant documents a question and answer technology such as Watson aims to parse the question, reason about it, and reply with a precise answer. Although Watson is a proprietary hardware and software platform for deploying question and answer applications if you are adventurous and handy with Java code you can roll your own using open source code.      The OAQA project, Open Advancement of Question Answering Systems at https://oaqa.github.io/  is an endeavor that has defined a question and answer architecture to be used for research in the field. They have also built Java libraries useful for constructing question and answer systems.  This ongoing effort is a collaboration between the Language Technologies Institute of the School of Computer Science at Carnegie Mellon University and IBM's Deep QA Group http://researcher.watson.ibm.com/researcher/view_group.php?id=2099 .  A Carnegie Mellon professor, Eric Nyberg http://www.cs.cmu.edu/~ehn/ , is a key figure in the advancement of this research that is the underpinning of Watson. Nyberg, along with IBM researcher David Ferrucci  http://www-03.ibm.com/innovation/us/watson/research-team/dr-david-ferrucci.html , conceived of a question and answer architecture that could be and has been extended far beyond winning at Jeopardy.    The project provides their OAQA Tutorial on GitHub  https://github.com/oaqa/oaqa-tutorial/wiki/Tutorial  along with Java code libraries CSE-Framework https://github.com/oaqa/cse-framework and BaseQA  https://github.com/oaqa/baseqa From the tutorial: “Unstructured Information Management applications are software systems that analyze large volumes of unstructured information in order to discover knowledge that is relevant to an end user. An example UIM application might ingest plain text and identify entities, such as persons, places, organizations; or relations, such as works-for or located-at.”    I am not suggesting that you try to compete with IBM with their platform of 2880 execution cores running simultaneously. But if you are interested in seeing how Watson gets things done with natural language question and answer it is entirely possible to build a tiny Watson that operates in a limited universe of data.
Coming as a Web based service. Java/Akka based technology models, each of which model a different technology, are active in a distributed Internet community.  Any of the technology models may have a definition of a better future version of itself.  A technology model that aspires to improve itself engages in conversations with other models in the community; seeking to discover behaviors that are exportable from other technology models which it can integrate into itself to achieve its goal.
Exciting information technologies emerge from new discoveries and re-emerge from past discoveries at a rapid rate.  Despite the glamor and curiosity appeal engendered by cutting edge technologies when they debut, after the hype fades and we look at what actually is there in the cold light of reason we find ourselves turning to our pragmatic side and asking:   

Filter Blog

By date: