ai and bi presentation
DESCRIPTION
A presentation on Artificial Intellegence Leading into Business IntellegenceTRANSCRIPT
Computer based Intellegence?Computer based Intellegence?
Supporting History
● Greeks– Formal logic
● 1700's and forward– Reverend Thomas Bayes/Perrier-Simon
Laplace– WWII– 1962 predict elections–
Cultural Differences
● Japanese Warm and cuddly
● West more heart burn than heart warm
The Start
● New toy – Computer● Not very fast but very big● Lets copy the way Humans do it
– Model the human vocal system
Early Software
● ChatterBots - 1966– Dungeon and Dragons
● Checkers● Chess
● Could master individual games but not transfer ability to other tasks or games
Unintended Consequences
● Internet● Hardware
– CPU's, RAM– Disk– Cloud
● Google/FaceBook/etc
Current Approach
● Lots of hardware– Racks of CPU's– Access to Wikipedia– The Internet
● Markov Chains● Bayes' Theorem● Statistics
–
In the news
● ‘Eugene’ becomes first computer to pass the Turing Test ' - theStar.com
● That Computer Actually Got an F on the Turing Test – wired.com
● IBM's Watson Gets A 'Swear Filter' After Learning The Urban Dictionary - http://www.ibtimes.com
Intellegence - the Definition
?
● Deep Blue● Watson ● ELIZA/Alice/Eugene
Personnal Assistants
● Cortina– http://www.engadget.com/2014/06/04/cortana-microsoft-windows-phone/?ncid=rss_truncated
● SIRI● Google Voice
Robot Location Example
11
Robots Google Car
Robots Additional Uses
● Agriculture– Vineyard robot
● Robot Herder– https://www.youtube.com/watch?feature=player_embedded&v=AQXJbYDGvPg
Tools Generated
● Genetic Algorthims● Neural networks● Random Forests● Regression● Markov Chains
● Most are available as OOS Tools
From IBM - 10 + 18 zeros
● Every day, we create 2.5 quintillion bytes of data — so much that 90% of the data in the world today has been created in the last two years alone. This data comes from everywhere:
– sensors used to gather climate information,– posts to social media sites, – digital pictures and videos, – purchase transaction records, – cell phone GPS signals to name a few. – This data is big data.
Business Intellegence?
● Inter/intranets creating tons of data– Disk prices cheap enough to store it
● People and Companies using networks● Computers relatively cheap
– Cloud allows connecting of thousands of computers to one task
–
AI Alogrithums/Math
● Genetic algorithm● Pattern Detection● Regressions● Markov Changes● Languages R/Julia/● Variety of databases
– Nosql/graph
BI OOP's
● Airlines in the 60's– Send thank you to Wifes that traveled – Turned out some were not the wifes– Bad press ensued
● Today– Wal Mart– Shoppers– Target– Any large retail operation
Forbes
How Target Figured Out A Teen Girl Was Pregnant Before Her Father Did
● One Target employee I spoke to provided a hypothetical example. Take a fictional Target shopper named Jenny Ward, who is 23, lives in Atlanta and in March bought cocoa-butter lotion, a purse large enough to double as a diaper bag, zinc and magnesium supplements and a bright blue rug. There’s, say, an 87 percent chance that she’s pregnant and that her delivery date is sometime in late August.
BI Awes
● Tracking Flu outbreaks– Google– Twitter
● NICU– Babies monitored
● Dr Carolyn McGregor, from the University of Ontario Institute of Technology. Dr. McGregor built a system at Toronto’s SickKids hospital to monitor newborns and predict dangerous infections 24 hours earlier than traditional visual methods
● http://www.ibmbigdatahub.com/blog/fusion-big-data-and-little-babies
Tasks in Data Analysis
● Data Munging– Correct the data
● Analysis– Issues with data size– May take days to process
● Reporting– Tables just don't cut it anymore
Causation vs Coralation
● There's A Shocking Connection Between Eating More Chocolate And Winning The Nobel Prize
http://en.wikipedia.org/wiki/File%3aPiratesVsTemp%28en%29.svg
http://www.johnquarto.com/2012/10/i-deceiver/
Learning in the BI Field
● MOOCS– UDACITY– Coursea– Edx– University
● Practicing– Kaggle.com
The End - Sorta
● http://nurses.3cdn.net/e5a15534f25c2375b8_enm6va18v.mp3●
●