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Transcript

ARTIFICIAL INTELLIGENCE & BIG DATA

WGI11-3

Lena, Niko, Sharon, Marc, Johanna

VWL, Fr. Cheng-Höhn

Definition 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

The development of AI

  • 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

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.

What is "Big Data"

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

The three types of 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

  • 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


AI technologies

  • 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

The benefits of AI

ARTIFICIAL INTELLIGENCE & BIG DATA

AI in action

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

LOREM IPSUM DOLOR SIT AMET

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