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Topic-Mapper: ai-one for Text
  •   ai-one technical overview
  •   Topic-Mapper SDK
  API for building
  •   Data organization and import
  •   API Structure - interacting with Topic-Mapper
                                       Topic Mapper
  learning machines
  l
  •    i        hi
      Topic-Mapper command overview
  using automatic
  •   API demonstration using BrainBoard

  lightweight ontologies

   June 2011
                                              ai‐one™
                                              biologically inspired intelligence

 © ai-one inc. 2011
“biologically inspired intelligence”
    biologically          intelligence




                     logic   creativity




© ai-one inc. 2011
The Technology | ai one description
                     ai-one

       ai-one s
       ai one’s technology is an adaptive holosemantic dataspace
       (“biologically inspired intelligence”) that allows users to quickly
       analyze and discover meaningful patterns of interleaved text, time
       related data, and images. It provides complex AI with reasoning and
       learning capability.




         … it provides answers to questions you
              didn't know you wanted to ask….
                          y



© ai-one inc. 2011
…ai-one


 … the secret of ai-one….!

 ai-one detects the intrinsic (inherent) semantic
 structure in any language with unsupervised
 learning!




© ai-one inc. 2011
© ai-one inc. 2011
Application - Lightweight Ontologies

                     physical exercise               smoking

                             0.9                      0.9
                                         lifestyle
                              0.75                   0.9
                                         0.6
                         stress           obesity    nutrition


       Lightweight ontologies may also be called associative networks




© ai-one inc. 2011
© ai-one inc. 2011
ai-one™ vs. traditional methods

    Full-fledged ontologies                             [Supervised learning]
         -    Works only with detailed models
         -    Language dependent,
    Sharing / reuse of ontologies                         [limited possibilities]
         -    Based on models and reservations about the quality
         -    Language dependent
    Folksonomies                                  [WEB 2.0 / semantic WEB]
         -    No controlled quality or validation
         -    Often incomplete or not existent, language dependent
                                       existent




© ai-one inc. 2011
© ai-one inc. 2011
…ai-one

        … language is not math ….

        1. Detects more words of higher relevance
        2. Faster processing the corpus
        3.
        3 Much faster incremental updates

                          =
        Faster implementation of semantic solutions



© ai-one inc. 2011
© ai-one inc. 2011
ai-one™ - Performance Comparison
                         p




© ai-one inc. 2011
© ai-one inc. 2011
Case Study - SEMPER Project
          y             j
   Concept Based Retrieval and Lightweight Ontologies


    The SEMPER Team is creating an interactive web
                                         interactive,
    based platform for out-patient assistance for alcohol
    dependency and work related disorders.

    "Learning a Lightweight Ontology for Semantic
    Retrieval i P ti t C t I f
    R ti    l in Patient-Center Information S t
                                       ti Systems".
                                                 "

    Prof. Dr. Ulrich Reimer, University of Applied Sciences St. Gallen et al.


    In this paper Prof. Reimer describes the use of ai-one (Association
    command) t l
              d) to learn associated nets of related t
                                  i t d    t    f  l t d terms t b ild
                                                               to build
    ‘lightweight ontologies” and then how they created “seed concepts”
    of over lapping related terms with the teaching commands to give
    the content a notion of relevance. A keyword query then resulted in
    the return of content that included related concepts.

    The paper also describes the testing of the ai-one approach versus
    the classical cosine similarity measure on a tf-idf document term
    matrix.




© ai-one inc. 2011
The Fundamental Theory
                        y
   USP of the Technology

    •   Self optimized information processing 
        Self‐optimized information processing
    •   Self‐controlled content organization
    •   Multiple higher‐order concept formation
    •   Autonomic learning via multiple context recognition 
                           g          p             g
    •   Self‐generalizing of learned concepts




                             Biologically inspired 
                             intelligence in computing
                             intelligence in computing
        Leads to:




© ai-one inc. 2011
© ai-one inc. 2011
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I0I00II0I00I0I0I0I0I00I0IIII0I0I0I0II00I0II0I000II00II0II0I00II0I0I0I00III000I0I0III0II00I
0I0I0I0II0I00I0I0I0I0I00I0IIII0I0I0I0II00I0II0I000II00II0II0I00II0I0I0I00III000I0I0III0II0
0II0I0I00II0I00I0I0I0I0I00I0IIII0I0I0I0II00I0II0I000II00II0II0I00II0I0I0I00III000I0I0III0I
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0II0I00I0I0I0I0I00I0IIII0I0I0I0II00I0II0I000II00II0II0I00II0I0I0I00III000I0I0III0II00I0II0
I00I0I0I0I0I00I0IIII0I0I0I0II00I0II0I000II00II0II0I00II0I0I0I00III000I0I0III0II00I0II0I00I
0I0I0I0I00I0IIII0I0I0I0II00I0II0I000II00II0II0I00II0I0I0I00III000I0I0III0II00I0II0I00I0I0I
0I0I00I0IIII0I0I0I0II00I0II0I000II00II0II0I00II0I0I0I00III000I0I0III0II00I0II0I00I0I0I0I0I
00I0IIII0I0I0I0II00I0II0I000II00II0II0I00II0I0I0I00III000I0I0III0II00I0II0I00I0I0I0I0I00I
0IIII0I0I0I0II00I0II0I000II00II0II0I00II0I0I0I00III000I0I0III0II00I0II0I00I0I0I0I0I00I0IIII
0I0I0I0II00I0II0I000II00II0II0I00II0I0I0I00III000I0I0III0II00I0II0I00I0I0I0I0I00I0IIII0I0I
0I0II00I0II0I000II00II0II0I00II0I0I0I00III000I0I0III0II00I0II0I00I0I0I0I0I00I0IIII0I0I0I0I
I00I0II0I000II00II0II0I00II0I0I0I00III000I0I0III0II00I0II0I00I0I0I0I0I00I0IIII0I0I0I0II00I
0II0I000II00II0II0I00II0I0I0I00III000I0I0III0II00I0II0I00I0I0I0I0I00I0IIII0I0I0I0II00I0II0
I000II00II0II0I00II0I0I0I00III000I0I0III0II00I0II0I00I0I0I0I0I00I0IIII0I0I0I0II00I0II0I00
0II00II0II0I00II0I0I0I00III000I0I0III0II00I0II0I00I0I0I0I0I00I0IIII0I0I0I0II00I0II0I000II0

                                                                   ai-one
                                                                   ai one
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00II0I0I0I00III000I0I0III0II00I0II0I00I0I0I0I0I00I0IIII0I0I0I0II00I0II0I000II00II0II0I00II
Inherent Associations in a Corpus




         Terms “Christiano” and “Ronaldo” in corpus of 50
         documents about the 2010 World Cup
         d       t b t th          W ld C

© ai-one inc. 2011
ai-one SDKs | API for building learning machines
                             g        g


Topic-Mapper
Topic Mapper
ai-one for Text




                               API
Ultra-Match
ai-one for Images



Graphalizer                                                                   ai‐one
                                           “Sensors”
ai-one for Signal Processing                                                  HSDS
                                     Text, Images, Signal Processing   Smallest Input = Data Quant




© ai-one inc. 2011
Our Product for Text | Topic Mapper SDK
                         Topic-Mapper

      • Provides inherent semantic associative search and
        phonetic analysis
      • Human language independent
                   g g         p
      • Requires only basic structuring of input text
      • Ongoing/incremental learning
      • “teaching” via user defined contexts and relations




© ai-one inc. 2011
Topic-Mapper
 Topic Mapper SDK | Description
•    ai-one™ core Text library (out-of-process COM server)
      – .NET 3.5 CLR wrapper (dll)
•    Small footprint instantiation (<700k)
•    API documentation
•    Developer’s guide
•    Code examples
•    BrainBoard
     B i B d workbench application f rapid proof of concept
                      kb    h     li ti for     id     f f          t
     development
•    Text focused support libraries and tools to assist in text preparation,
     processing, parsing, and l di i t ai-one
             i         i      d loading into i




© ai-one inc. 2011
Topic Mapper
Topic-Mapper SDK | Semantic Commands
Association
returns the associative network for semantic
  t     th         i ti    t   kf          ti
correlation with the (one or more) input words;
referred to as "brainstorm“


AssociationReverse
the inverse of Association; referred to as "focus“



AssociationCheck
returns a list of all associative paths between
two input words (source and target);




© ai-one inc. 2011
Topic-Mapper
Topic Mapper SDK | Semantic Commands
KeyWords
Given a pointer t a context, return the
Gi         i t to       t t t       th
words and a score indicating the
semantic significance between the
words and information contained within
the context.

Phonetic
Returns list of words with phonetic similarity to the input word; includes a
score for each word.

Statistic
Returns frequency counts for input word; counts total occurrences, subtotal by
structures and includes handles for each structure.


 © ai-one inc. 2011
Topic Mapper
  Topic-Mapper SDK | Teaching Commands
 •    StopWords{Get|Set|Erase}: maintenance of a stop word list. stop
      words are words found in the dataspace, but not used for any of the
      semantic commands.
 •    Context{Get|Set|Erase|Find}: maintenance of contexts; contexts
      are bags of words which, by definition, have a strong relation among
      themselves.
 •    ContextTighten: increases the semantic relation within the
      reference handle
 •    Relation{Get|Set|Erase|Find}: maintenance of relational triple:
      subject, object and predicate. Used to teach explicit relationships
      from entities like thesauri, taxonomies, and ontologies.




© ai-one inc. 2011
BrainBoard | The SDK prototyping & testing tool




© ai-one inc. 2011
Working with us| Our Partner Program

      The ai one Partner Program is critical and inseparable from our
          ai-one
      mission to put “biologically inspired intelligence” in every computing
      device.


        Our mission is to build great technology and license it to IT
          p
          professionals so that they can use it to build the next
                                    y
                          generation of software.




© ai-one inc. 2011
Partner Program | Consulting and IT
    Services Partners
     This program is for individuals and firms that provide pre-sales
     consulting and post-sales implementation around ai-one's products
     and services. This category is for two types of partners:

           Consultants: domain specific business development

           IT professionals and p g
              p                 programmers: p j
                                             project management and
                                                           g
           programming services to enterprise clients, government or to
           software vendors




© ai-one inc. 2011
Partner Program | Advantages
    Benefits for Consulting Partners:
                          g

               Branding: Unique, Innovative and Disruptive technology
               More sales: marketing support materials and lead generation
                                        support,
               Residual income: commissions for SDK license sales and up
               to five years of royalties
               Resources: P t
               R            Partner community support for both programming
                                             it     t f b th           i
               and business development resources




© ai-one inc. 2011
Partner Program | Industry & Technical
    Expertise




© ai-one inc. 2011
Partner Program| OEM Partners

     The OEM Partner program is for integrators,
     VARs, ISVs and other IT firms that provide
     complete solutions to their customers with
     embedded ai-one technology.

     The OEM Partner is our customer and our
     mission is to help them build innovative
     solutions for their customers.




© ai-one inc. 2011
ai-one
ai one Technology and Programs



      Join us to begin building the next
        generation of computing solutions…




© ai-one inc. 2011
Thank You!

ai-one inc.            ai-one ag            ai-one gmbh
5711 La Jolla Blvd
              Blvd.,   Flughofstrasse 55
                                      55,   Koenigsallee 35a
                                                         35a,
Bird Rock              Zürich-Kloten        Grunewald
La Jolla, CA 92037     8152 Glattbrugg      14193 Berlin

cell: +18585310674     cell: +41794000589   cell: +4915112830531
main: +18583641951     main: +41448284530   main: +493047890050



© ai-one inc. 2011
© ai-one inc. 2011

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