Administrative information

Title	Introduction to resurgence of AI and ML
Duration	45-60
Module	C
Lesson Type	Lecture
Focus	Technical - Future AI
Topic	Introduction

Keywords

Turing test, Birth of AI, Resurgence of AI, AI definition,

Learning Goals

Understanding emergence of AI
Knowledge of events leading to the AI winters
Raionale key factors responsible for the Resurgence of AI

Expected Preparation

Learning Events to be Completed Before

Obligatory for Students

Machine learning concepts
Deep learning concepts

Optional for Students

None.

References and background for students

None.

Recommended for Teachers

None.

Lesson materials

Slides

The materials of this learning event are available under CC BY-NC-SA 4.0.

Instructions for Teachers

The goal of this lecture is to provide students with a brief history of AI and the events/developments that have lead to an explosion of AI applications and the current wave of AI research, investment and the call for AI regulation. It should set the stage for more in-depth studies of advanced AI concepts, technological and regulatory developments that will shape future AI. The lecture should:

Present a chronological timeline of AI developments from past to present
Use real-world examples to illustrate AI landmarks through time
Focus on the impact and direction of AI research leading to the current wave of AI applications
Pay particular attention to the recent explosion of AI, its ubiquitous nature and the need to focus on ethical considerations

Outline

Duration	Description	Concepts	Activity	Material
10 min	Birth of AI: tracing the first notions of AI	AI in Greek mythology, automotons, early science fiction, 3 laws of robotics (Asimov), questions driving AI, categorising AI	Taught session and examples	Lecture materials
5 min	Events & developments leading to the first AI winter	Formal logic and AI, thinking machines, turing test, early success stories (Arthur Samuel checkers program 1955), early machine translation, Dartmouth summer project (1956), Rosenblatt's perceptron (1957), fall of connectionism (Minsky & Papert 1969), Lighthill report (1973)	Taught session and examples	Lecture materials
5 min	Events & developments leading to the second AI winter	Expert systems (DENDRAL, MYCIN 1972), Japanese fifth generation project (1982), Backpropagation (1986), early character recognition (LeNeT-1 1989), commercialisation of AI, limitations of expert systems, slow progress in nerual network development (Support Vector, Bayesian style methods)	Taught session and examples	Lecture materials
10 min	Big data: how the collection of big data has impacted AI and machine learning	Web 2.0 and explosion of data, knowledge bottleneck (Halevy et al. 2009), growth of social media (semi-structured and unstructured data), mobile device and health data, sensor-based internet enabled devices (IOT), race to extract meaningful data	Taught session and examples	Lecture materials
10 min	Resurgence of AI: how data and computational power has given rise to a new wave of ubiquitous AI and the call for regulation	GPU-based computation (CUDA 2012), rise of personal assistants (Google, Apple, Amazon, Microsoft), AlexNet (ImageNet 2012), Google Brain (2012), Tensor Processing Units (2016), AlphaGo & AlphaFold (2016, 2020), self-driving cars Waymo (2020), EU AI Act (2021)	Taught session and examples	Lecture materials
5 min	Conclusion, questions and answers	Summary	Conclusions	Lecture materials

More information

Click here for an overview of all lesson plans of the master human centred AI

Please visit the home page of the consortium HCAIM

Acknowledgements

The Human-Centered AI Masters programme was co-financed by the Connecting Europe Facility of the European Union Under Grant №CEF-TC-2020-1 Digital Skills 2020-EU-IA-0068.

The materials of this learning event are available under CC BY-NC-SA 4.0

The HCAIM consortium consists of three excellence centres, three SMEs and four Universities

Colofon

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Auteur: HCAIM Consortium
Laatst gewijzigd: 2024-02-19 16:04:33
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Gebruikte Wikiwijs Arrangementen

HCAIM Consortium. (z.d.).

Acknowledgement

https://maken.wikiwijs.nl/198386/Acknowledgement

HCAIM Consortium. (z.d.).

Lecture: Guest Lecture on Future of AI

https://maken.wikiwijs.nl/202200/Lecture__Guest_Lecture_on_Future_of_AI

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