Saffron at IBM Almaden Cognitive Computing

Associative Memories

Cognitive Distance

Early Warning System
Protect The Foundation from physical and reputation threats

Detect weak signals to predict threat
Early warning system to score threats from people & groups based
on dynamic incremental machine learning
Structured and Unstructured Data

Incidence Reporting
Metadata + E-mails

Harvested Web Pages
(Terabytes & growing )

Strategic Early Warning
System – Igor Ansoff
Scan environment to
detect weak signals &
rare events to predict
surprises

Pattern Recognition In Healthcare
Automate Echocardiogram Diagnoses
90 metrics, 6 locations, 20 time frames
10,000 attributes/beat*patient
-> 100 million triples / beat*patient
Heat maps show separation of disease
states. Associations between variables in
restrictive cardiomyopathy (red) separate
from dominant associations in constrictive
pericarditis (green)
Intelligent Platforms for Disease Assessment
Novel Approaches in Functional Echocardiograph,
Partho P. Sengupta, in JACC: Cardiovascular Imaging, 11/2013

Saffron 90%
Best doctor 76%
State of the art
C-tree 54% using 7
attributes

Watch The Video With Dr. Sengupta
Part 1
http://www.youtube.com/watch?v=rGkyDkDmZts
10:30 - nice Big data setup
12:30 - 14:00 Intelligent Computing
Part 2
http://www.youtube.com/watch?v=SAby6-tMvng
4:40 - Look inside the dataset as a matrix
5:30 - Saffron <<< here it is
6:16 - Associate Memory Reasoning
7:17 - heat map where I can see a pattern
7:56 - 8:26 compare patterns and accuracy of 89.6%
8:51 - 9:07 need to do pattern recognition for intelligent assessment

11/22/20
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Saffron Technology, Inc. All Rights Reserved.

Match Made in Heaven
Cognitive Distance Associative Memories
Universality
• Cognitive Distance is universal
•

C. Bennett, IBM, 1997; M Hutter, IDSIA, 2000 AIXI

• Nonparametric, incremental, deterministic weights

Context
• Cognitive Distance depends on context
• AM fabric stores context – complete graph

Compression
• K Complexity measures compressibility
• Associative Memories are perfect compressor

Kolmogorov Complexity – Signal vs. Noise

Snake eyes are regular sequence -> regular cause, meaning
probability > 0
for snake eyes!

100X

Place a huge bet on
simple outcomes – fair
dice have no pattern

How Do Extract Similarity Automatically?

xy=73M

What is closer to cowboy?
1. saddle or
2. movie

“movie”
y=1,890M

xy=8M

x=131M

Cognitive Distance based on Kolmogorov Complexity
Approximating Kolmogorov Complexity K(x) ~ log x/N we get
CD ~ max {log(fx),log(y)}-log(x,y) / ( logN-min{log(x),log(y)}
 the saddle is closer to the cowboy

“saddle”
y=87M

Not Always So Easy - Context Resolves Ambiguity

Cognition Is About Context
Cognitive Distance Allows for Condition
CD|c ~ max {log(xc|c),log(yc|c)}-log(xc,yc|c) /
( logN-min{log(xc|c),log(yc|c)} )

The Bride: Scaling Associative Memory

NoSQL - Associative Memories Are Truly
Asynchronous Computing
Ising Model for order  disorder phase transition
e.g. Ferromagnetism
H = -J / 2å SiSj - hå Si
i, j

i

Hopfield Network
weights are
deterministic 

parameter free
Connections and counts
synapses and strengths

Saffron’s Solution - Large Scale Machine Learning on
Sparse Matrices
Build the Brain
1. Unify structured & un-structured data
2. Extract entities
3. Build semantic graph with counts on edges  stored as triples
John Smith flew to London on 14 Jan 2009 aboard United Airlines to meet with Prime Minister for 2 hours on a rainy day.
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Why is this so special?
• Non-parametric, nonlinear & instant
incremental learning
• Graph & statistics
• Millions of features
• Saffron stores &
queries billions of triple
counts

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Make the Brain Think
• Reason by similarity with
cognitive distance

Happy Ending – Offspring of KC & AM
 Discovery – Search
– Entity ranking and semantic context
– Convergence – the distance over time

 Classification
– Predicting risk (bad, good)
– Customer life time value
– Echocardiogram diagnosis

 Clustering
– Evolutionary trees, languages, music
– Novelty detection: spare parts, planes, etc.

Take Away
Advanced cognitive computing to
perform like super brains
Google

rss

Twitter

FACEBOOK

Email

STOCKS EXCEL
Word

DATABASE
SOCIAL NETWORKS

PDF

DATABASES

By matching Cognitive Distance with
Associative Memories we are able to
• reason by similarity
• learn instantly &
incrementally w/o parameters
• Discern Context
Enterprise proven

11/22/20
13

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©2013 Saffron Technology, Inc. All rights reserved.

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@paul_hofmann
phofmann@saffrontech.com
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Watch Dr. Sengupta Partho’s video on YouTube
http://www.youtube.com/watch?v=rGkyDkDmZts
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Saffron at IBM Almaden Cognitive Computing

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