biologically inspired intelligence
ai-one™
© ai-one inc. 2012
Biologically Inspired Intelligence
creativitylogic
© ai-one inc. 2012
GARTNER’s© position: Maximizing decision impact
through business intelligence (BI) increases enterprise
effectiveness at all levels, contributing to mission or growth
goals by enabling workers and managers to direct
business or mission decisions toward desired outcomes.
Better decision-making through BIGARTNER © is strongly promoting BI strategy as well as consulting the
industry about how to get the best use of BI
© ai-one inc. 2012
BI Definition
Business intelligence (BI) mainly refers to computer-based techniques
used in identifying, extracting, and analyzing business data. BI
technologies provide historical, current and predictive views of business
operations.
BI uses technologies, processes, and applications to analyze mostly
internal, structured data and business processes while competitive
intelligence gathers, analyzes and disseminates information with a
topical focus on company competitors. Business intelligence understood
broadly can include the subset of competitive intelligence.
-- From WIKIPEDIA©
There are multiple definitions of BI. The following definition is our
preferred understanding…
Information & Data are the inputs for BI
The most important factor is the value of data input in BI processes
1. Source Who is the Source (sender)? Do we know the source? Could
there be a change in value since last use?
2. Receiver Who is the receiver? Do we know the receiver? Is there a
change in attributes and value since last use? Did receiver
further transport the data or behave and/or make decisions
on it?
3. Content What is the content of the information exchanged?
Facts to validate information value
© ai-one inc. 2012
Information & Data are the inputs for BIThe sources are structured & unstructured and in various dimensions
The rectangle must fit into the circle!
The challenge is to extract actionable knowledge from complex data that
contains many different types of information is constantly changing.
Humans have has an innate capacity to find patterns among different
sets of attributes quickly and easily. Our brains are hard-wired to find
similarities and differences by evaluating context.
ai-one’s API enables computers to analyze complex data to find patterns
in a way similar to a human – by simply finding the keys to context.
The HSDS, or holosemantic data space, makes it possible to find the
most unusual relationships – such as when a rectangle fits into a circle –
even when the signal is very faint.
© ai-one inc. 2012
…ai-one - Content Analytics
© ai-one inc. 2012
Traditional
ai-one
© ai-one inc. 2012
GARTNER© Chart from the L.A. 2012 Congress
GARTNER© positions ai-
one as a hybrid solution:
Combining structured data
and content (unstructured)
Hybrid solutionsGARTNER © is defining 3 types of content analytics :
Structured, Hybrid and Content.
© ai-one inc. 2012
Hybrid solutionsGARTNER © defines 3 types of content analytics:
Structured, Hybrid and Content.
GARTNER© Chart from the L.A. 2012 Congress
The ai-one hybrid
approach:
The HSDS, holosemantic data
space, is the environment
where multi layer higher order
patterns are found and where
heterarchical structures are
analyzed. The HSDS is the
perfect environment for
challenges 1, 2, & 3
© ai-one inc. 2012
Cool Vendors in Content Analytics, 2012ai-one is featuered in GARTNER © 2012 Cool Vendor Report:
“Data is growing in volume, variety, velocity and complexity. Cool
Vendors in content analytics offer innovative approaches, tools
and technologies for analyzing text, images, video or speech,
and for finding and acting upon insights and patterns across
content types and structured data.“
“ai-one provides machine learning technology that mimics how the
brain detects patterns in data, which developers can embed into any
application.“
http://www.gartner.com/DisplayDocument?ref=clientFriendlyUrl&id=1996718
Contents: Analysis
What You Need to Know
ai-one
Co-Decision Technology
Mattersight
ThoughtWeb
ai-one can give you an answer to
a question, you did not know to
ask!...changing the “search”
function to a “find” function
…ai-one is listening to the data –
© ai-one inc. 2012
… solves two problems:
• Sense making in unknown data
• Generalizing multi layer higher
order pattern foundation
…ai-one –
© ai-one inc. 2012
Traditional AI/KM
creativitylogic
© ai-one inc. 2012
Focus on logic, Boolean & statistics
approach. Manually programmed fuzziness
and high dependency on quality of
programmers and experts, thesauri and
Ontology as Models.
Problems with speed, intelligence and
incremental updates!
Traditional AI/KM
creativitylogic
© ai-one inc. 2012
Focus on neural or fuzzy & statistics
approach. Manually programmed fuzziness
and high dependency on quality of
programmers and experts, thesauri and
Ontology as Models.
Problems with speed, intelligence and
incremental updates!
© ai-one inc. 2012
…the ai-one hybrid–The holosemantic data space combines LOGIC & CREATIVE data
processing in a n-dimensional data space (including space-time).
PIM Process In Memory, and “where the circle fits the rectangle”
The Fundamental TheoryGeneral introduction | The enabling elements
© ai-one inc. 2012
Motivationrefers to the intrinsic activation of goal-oriented behavior , like a clock driven by a
flywheel
Self-organizationis a key of function of our holosemantic data space in combination with the
motivation and in order to optimize information structure
Impulsive information detection & multiple higher-
order concept formation a result of the combination between motivation, self-organization and the ai-one™
algorithms
© ai-one inc. 2012
Features of ai-one™
The Topic-Mapper™; Ultra-Match™ or Graphalizer™
library and SDK focuses on different solutions:
Text/Linguistic: Topic-Mapper focuses on LWOs (Light Weight
Ontology) for semantic applications for expert systems; dialogue
robot’s, text & content analysis, keyword generation, matching
associative, semantic decision/conclusion systems.
Image Analysis/Matching: Ultra-Match focuses on images
where multi layer higher order pattern foundation and complex
pattern or concept matching is important.
Signal Processing: Pattern recognition in data streams of
various kinds of signals and sources. Multi layer higher order
complexity is enabled here as well.
The Fundamental TheoryGeneral introduction
• Self-optimized information processing
• Self-controlled content organization
• Multiple higher-order concept formation
• Autonomic learning via multiple context recognition
• Self-generalizing of learned concepts
Biologically inspired
intelligence in computingLeads to:
© ai-one inc. 2012
© ai-one inc. 2012
… the SDK:
Core
Utilities (sensors)
MVPs
Documentation
Best Practice
Source Samples
ai-one™ SDK | The Learning Machine
© ai-one inc. 2012
The ai-one approach
… our SDK is an API to build a
learning machine
… ai-one enables biologically
inspired intelligence in computing
ai-one –
© ai-one inc. 2010
SDK with | Source, MVPs & Utilities…
© ai-one inc. 2012
© ai-one inc. 2012
The content fingerprint
The Corporate Structure
© ai-one inc. 2012
ai-one inc.Corporate HQ
La Jolla CA
ai-one gmbhEurope Sales & Support
Berlin
ai-one agResearch Lab
Zurich
• Offices in La Jolla, Zurich and Berlin
• US Delaware C Corporation with wholly owned subsidiaries
• Founded in 2003 in Zurich; former name: “semantic system ag”
• Approximately 15 FTEs
• Privately funded
The Sales Concept for the Solution
© ai-one inc. 2012
ai-one™Distribution Network
OEM-PartnerSW & HW Vendors
Consulting PartnerExperts in Various Markets
Solution ProviderIn-house & Whole Supplier
• Slim and effective ai-one organization
• High scalability trough partners
• Distributed risk because the massive numbers of vertical markets
• Sustainable markets and revenue streams once the approach is established
• High exit and cash potential because of already installed JV - Partnerships
The ai-one Incubation Strategy
© ai-one inc. 2012
ai-one inc.Corporate HQ
La Jolla CA
ai-one gmbhEurope Sales & Support
Berlin
ai-one agResearch Lab
Zurich
ai-ibiomics gmbhGenomics Joint Venture
Forensity AGSwiss Forensic Solutions
Brainup AGData Intelligence
Business CasesMultiple vertical markets as SW or HW solutions
© ai-one inc. 2012
Biometry:
Forensics:
Intelligent Services:
Security:
Fraud:
Sociology:
Data bases:
Computing:
Life Science:
Pharmacy:
Dermatology:
more…
Pattern recognition …
Tracks, patterns, profiles …
Profiles, behavior, semantics
Cryptography, compression
Fraud, camouflage…
Human behavior profiles
Analyses, data mining …
Intelligence in computing
Pattern recognition
Clinical tests, profiling
Cosmetics, pattern recognition
… recognizing the content
… understanding the meaning and
generalizing its application
… deciding about its importance
… knowing what to do with this
learned information
ai-one – The Next Evolution in
Information and Communications
Technology?
© ai-one inc. 2012
Thank You!
© ai-one inc. 2012
ai-one inc. 5711 La Jolla Blvd.,
Bird Rock
La Jolla, CA 92037
cell: +18585310674
main: +18583641951
ai-one agFlughofstrasse 55,
Zürich-Kloten
8152 Glattbrugg
cell: +41794000589
main: +41448284530
ai-one gmbhKoenigsallee 35a,
Grunewald
14193 Berlin
cell: +4915112830531
main: +493047890050
ai-one ™
© ai-one inc. USA, ai-one ag, SUI , Diggelmann / Hoffleisch 1985 - 2010
© ai-one inc. 2010
2003 2011
semantic system agSwitzerland R&D LAB
Walt Diggelmann
Tomi Diggelmann
Manfred Hoffleisch
20072004 2005 2006 2008 2009 2010Fundamental Theorie R&D Applied Solutions R&D API and libraries development API and libraries commercialization
New name for Swiss
company:
ai-one ag
Founding world HQ:
ai-one inc. USA
Founding European HQ:
ai-one GmbH GER
The media
picks up the
story
GLOBUS
The first 6 years were
characterized by a very sharp
focus on R&D. A new fundamental
theory also requires a whole
infrastructure to be built. Hence we
first had to create a development
environment (API/libraries) for the
commercialization.
So far we have spent approx.
7.0 Mio. of investment capital for
R&D.
Early stage partners
The History of ai-one™
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