Embed Size (px)
Citation preview
Lora Aroyo @laroyo http://lora-aroyo.org
Turning Sci-Fi into Reality
Lora Aroyo
Lora Aroyo @laroyo http://lora-aroyo.org
Sci-Fi in 60’s, 70’s & 80’s
Lora Aroyo @laroyo http://lora-aroyo.org
Sci-Fi in 2002
Lora Aroyo @laroyo http://lora-aroyo.org
Sci-Fi in 2013
Lora Aroyo @laroyo http://lora-aroyo.org
Sci-Fi in 2015
Lora Aroyo @laroyo http://lora-aroyo.org
Turning Sci-Fi into Reality
Lora Aroyo @laroyo http://lora-aroyo.org
scientific challenge in 1997
Lora Aroyo @laroyo http://lora-aroyo.org
chess
finite, mathematically well-defined search space limited number of moves & states
grounded in explicit, unambiguous math rules
Lora Aroyo @laroyo http://lora-aroyo.org IBM Confidential
scientific challenge in 2011
Lora Aroyo @laroyo http://lora-aroyo.org IBM Confidential
natural language
ambiguous, contextual & implicit grounded only in human cognition
infinite number of ways to express same meaning
Lora Aroyo @laroyo http://lora-aroyo.org http://lora-aroyo.org @laroyo 11
keeps expanding to new domains
Lora Aroyo @laroyo http://lora-aroyo.org
Lora Aroyo @laroyo http://lora-aroyo.org http://lora-aroyo.org @laroyo 13
Lora Aroyo @laroyo http://lora-aroyo.org
1. Expand
“EXPANDs human cognition - makes the jobs we do easier, like a cognitive prosthesis. Especially when dealing with processing massive data, or data that requires human interpretation”
Lora Aroyo @laroyo http://lora-aroyo.org
“LEARNs as you use it – most machine errors are easy for a human to detect. We can instrument usage of systems to better understand the system and the problem it solves”
2. Learn
Lora Aroyo @laroyo http://lora-aroyo.org
“INTERACTs naturally - bringing machines closer to their users by letting them understand natural language, spoken or written, be able to process images & videos. These simple human problems are extremely complex for machines, but are hallmarks of a new computing era.”
3. Interact
Lora Aroyo @laroyo http://lora-aroyo.org
▪ A new software paradigm has emerged – Increasingly, computational tasks require inexact solutions that
combine multiple methods in unpredictable ways
▪ Knowledge is not the destination – Watson does not answer a question by translating natural language
input into formally represented knowledge and simply running queries against this knowledge
▪ Machine intelligence is not human intelligence – The difference is most notable in the mistakes they make
When Building Cognitive Computing Systems …
http://www.yovisto.com/video/19674 Chris Welty’s keynote at WWW2012
Lora Aroyo @laroyo http://lora-aroyo.org
Cognitive Systems
can fail and still
be useful
A dramatic shift for software systems Focus on improvement, not perfection
We must be able to answer, “Is it better?”
Cognitive Computing: It’s OK to be wrong!
Lora Aroyo @laroyo http://lora-aroyo.org
Cognitive Systems Engineering Pillars
MEASURE
MEASURE
MEASURE
DATA
DATA
DATA
TRUTH
TRUTH
TRUTH
Lora Aroyo @laroyo http://lora-aroyo.org
Cognitive Systems Engineering Pillars
MEASURE
MEASURE
MEASURE
DATA
DATA
DATA
TRUTH
TRUTH
TRUTH
They define the system. If you change one of them, the system should change
Lora Aroyo @laroyo http://lora-aroyo.org
Winning Human Performance
2007 QA Computer System
Grand Champion Human Performance
Top human players are remarkably
good.
Each dot – actual historical human Jeopardy! games
More Confident Less Confident
What it Takes to compete against Top Human Jeopardy! Players Our Analysis Reveals the Winner’s Cloud
Lora Aroyo @laroyo http://lora-aroyo.org
2007 QA Computer System
In 2007, we committed to making a Huge Leap!
Computers? Not So Good.
Winning Human Performance
Grand Champion Human Performance
What it Takes to compete against Top Human Jeopardy! Players Our Analysis Reveals the Winner’s Cloud
Each dot – actual historical human Jeopardy! games
More Confident Less Confident
Lora Aroyo @laroyo http://lora-aroyo.org
Prec
isio
n
% of Answered
Deep QA: Incremental Progress 6/2007-11/2010
Now Playing in the Winners Cloud
11/2010
04/2010
10/2009 5/2009
12/2008 8/2008
5/2008 12/2007
Baseline
Lora Aroyo @laroyo http://lora-aroyo.org
… and WATSON won
Lora Aroyo @laroyo http://lora-aroyo.org
Watch…
Day 2 (15 Feb 2011)
Day 1 (14 Feb 2011)
Also on YouTube: https://www.youtube.com/watch?v=i-vMW_Ce51w
Lora Aroyo @laroyo http://lora-aroyo.org
Crowd-Watson team 2013 http://lora-aroyo.org @laroyo 26
Lora Aroyo @laroyo http://lora-aroyo.org
CrowdTruth team growing, 2014 http://lora-aroyo.org @laroyo 27
Lora Aroyo @laroyo http://lora-aroyo.org http://lora-aroyo.org @laroyo 28
Lora Aroyo @laroyo http://lora-aroyo.org http://lora-aroyo.org @laroyo 29
Lora Aroyo @laroyo http://lora-aroyo.org
Lora Aroyo @laroyo http://lora-aroyo.org
Crowd-Watson 2015
Lora Aroyo @laroyo http://lora-aroyo.org
http://crowdtruth.org
![SPSNYC 2016 Event Slides [Opening / Closing Remarks]](https://img.pdfslide.net/doc/110x75/587c03da1a28ab7c668b7283/spsnyc-2016-event-slides-opening-closing-remarks.jpg)
