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™