AI

1. Artificial narrow intelligence (ANI)
1. basic/weak
2. narrow AI is driven by highly complex algorithms & neural networks
1. eg.: Facial recognition, internet searches, selfdricing
2. Artificial general intelligence (AGI)
1. should succesfully perform any task that human can
2. learns from experience
3. extrapolate knowledge across a wide range of tasks
1. eg.: the summit supercomputer
3. Artificial superintelligence (ASI)
1. theoretically fully self-aware
2. human traits & further argumented with processing
3. present distopian, sci-fi future

The three types of AI

• AI is one of the fastest growing areas of technological development

What is "Big Data"

It is all the data sorrounding us, everyday. "Big" doesn´t just define it´s size but also it´s complexitie. The data comes from evywhere on earth that we can monitor. eg.: satallites, traffic, trends Today it´s about 44 zettabytes (44 trillion gigabites) that number is dubeling every three years.

• AI is short for artificial intelligence
• came from one of it´s founding fathers (-> Martin Minsky)
• science of making machines do what reqires intelligence, if done by mankind

The development of AI

• First half of 20th century: AI is fiction
• 1950:
• First discussions on intelligent machines
• first AI programm: Logic Theorist
• DSRPAI: First conference about artificial intelligence
• 1960s-1979s:
• AI flourished, computer became faster, cheaper, more accesible & more capable
• machines lerned algorithms, people got better at knowing which algorithm to apply for a problem
• Nowdays: Big Data era, more cpacity to collect datas, fruitful for many industies

=> Development until today

Definition of AI

VWL, Fr. Cheng-Höhn

Lena, Niko, Sharon, Marc, Johanna

WGI11-3

ARTIFICIAL INTELLIGENCE & BIG DATA

• healthcare =>diagnosis
• banking => transactions
• manufacturing =>connect between send and receive
• tail => demand analyzes
• Agriculture =>innovative resear in sustainability

AI in action

ARTIFICIAL INTELLIGENCE & BIG DATA

The benefits of AI

• Bussiness wide resillience:
• automation of complex processes
• used more efficiently
• better prediction of disruptions & opportunities
• Better Customer Service:
• personolized service offerings
• market shifts from "lead" to "conversation"
• more data -> better egagement
• Confident desicion making:
• prompt & informed desicions
• supported by advanced data analysis and actionable insights
• Relevant Products and Services:
• data sets allow modifying existing products & creating new ones
• forward looking R&D model
• Engaged workforces:
• reduce burden of mondane tasks
• AI helps notice when employees are anxious, tired or bored
• restore a healthy work-life balance

AI technologies

• Machine learning:
• Part of AI.

=>cannot exist without AI

• AI getting smarter through machine learning
• for businesses machine learning can be applied to any problem or goal that requires predictive outcomes
• NLP:
• allwoing machines to recognize written language and voice commands
• convert human language to digital
• Computer vision:
• handling of pictures and videos

=> self-driving cars

• Robotics:
• without application of AI =>manual programming& calibration needed
• AI in robotics => more efficient