ΑΙhub.org

resources


Welcome to our “resources” page – this is in no way exhaustive – and we’ll be updating the content regularly. Please send any ideas and updates to aihuborg[at]gmail.com.

Seminars

List of seminars for 2024.
List of seminars for 2023.
List of seminars from 2022.
List of seminars from 2020 and 2021.
List of organisations that run regular seminars on machine learning and artificial intelligence.

Courses and tutorials

Elements of AI
Fast.ai
Google AI Education
Intro to Artificial Intelligence – Udacity
Intro to Deep Learning – Google via Udacity
Machine Learning Course – Stanford
Machine Learning Course – Columbia
Foundations of Machine Learning – Delta Analytics

Lecture series and talks

Reinforcement learning lectures, a lecture series by Emma Brunskill, Stanford University.
Multi-task and meta-learning, a lecture series by Chelsea Finn, Stanford University.
Information theory, pattern recognition, and neural networks, a lecture series by the late David MacKay, University of Cambridge.
Machine learning course, by Nando de Freitas, taught at the University of Oxford.
Why reinforcement learning is the next big thing in AI, a talk at the India Science Festival by Balaraman Ravindran, Indian Institute of Technology Madras.
A series of talks for students, organised by the Youth AI Lab and the OpenCode Foundation.
UC Berkeley’s Fall 2020 deep reinforcement learning course.
School of AI The Netherlands – a combination of self-study and webinars. You can watch the past events here.
MIT introduction to deep learning – 2021 lecture series given by Alexander Amini and Ava Soleimany.
Data Science Nigeria – lectures and tutorials from the 2020 AI bootcamp.
Basics of mobile robotics, an introductory course by Kshitij Tiwari.
Introduction to Deep Learning, a lecture course with tutorials and exercises, from Matthias Niessner.

Podcasts

Radical AI is a podcast featuring the voices of the future in the field of Artificial Intelligence Ethics. Hosted by Dylan Doyle-Burke and Jessie J Smith.
The GRACE podcast. This podcast accompanies a new student-run AI Ethics Journal at Stanford.
Machine Ethics Podcast is hosted by Ben Byford and features interviews with academics, authors, business leaders, designers and engineers.
The Good Robot is a podcast which explores the many complex intersections between gender, feminism and technology. Hosted by Eleanor Drage and Kerry Mackereth.
Computing Up: Conversations about computation writ large, with Michael Littman and Dave Ackley.
Futuremakers, from the University of Oxford and hosted by Peter Millican. Series one focused on AI.
TWIML AI is a podcast hosted by Sam Charrington and brings some of the top minds and ideas from the world of ML and AI.
Engineering Out Loud from Oregon State University. Season nine focused on robotics and AI.
Living with AI is a podcast from the UKRI Trustworthy Autonomous Systems Hub. It considers key issues that arise when building, operating, and using machines and apps that are powered by artificial intelligence.

Ethics

The IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems.
Ethics Guidelines for Trustworthy AI
OECD Principles on Artificial Intelligence
Check Alan Winfield’s running list for an up-to-date overview.
The AI ethics reading list is a compilation of books, papers, and resources recommended by AI Ethicists. Hosted by AI Truth.
Tutorial on fairness, accountability, transparency and ethics in computer vision by Timnit Gibru and Emily Denton.
AI ethics resources compiled by Rachel Thomas on fast.ai.
TWIML AI playlist on ethics bias and fairness in AI.
The future of AI for social good, an AI ethics mini course by Saiph Savage. The slides are here.
AI ethical guidelines and checklist, guidelines for start-ups from Torrens University.

Reports and initiatives

One Hundred Year Study on Artificial Intelligence (AI100), Stanford University.

Videos

AI Notes – Beril Sirmacek describes various AI concepts.
Humans of AI: Stories, Not Stats – Devi Parikh talks to well-known figures in the field of AI.
Expert interviews – Beril Sirmacek interviews AI experts.
AI explained in 5 Levels, by IIT Madras Prof & Alumni – Balaraman Ravindran explains AI in five levels through conversations with school kids, IIT Madras students and alumni.

Other AI learning resources

Better Images of AI – a new and growing collection of stock images of AI beyond cliché glowing brains and shiny robots.
A to Z of AI by Gina Neff, Oxford Internet Institute, and Google UK.
“Meet AI” – a scientific comic about the Human-AI story, by Falaah Arif Khan.
Mirror, mirror – a comic book from Data Responsibly (Falaah Arif Khan and Julia Stoyanovich).
Fairness and friends – the second comic book in the Data Responsibly series (Falaah Arif Khan, Eleni Manis and Julia Stoyanovich).
Insights into the MLOps tooling landscape from Chip Huyen.
An introduction to AI story generation by Mark Riedl.
AI Art Gallery – an online collection of art, music and design using machine learning. Curated by Luba Elliott.
Unite.AI – have an extensive glossary of many AI basic terms as a part of their AI 101 series.
Generative AI glossary – from AIPRM.
Towards Data Science – a collection of blog posts from various authors on a range of data science topics.
The AIhub list of resources, articles, and opinion pieces relating to large language models.

For journalists and science writers

How to report effectively on artificial intelligence, an article by Lakshmi Sivadas and Sabrina Argoub.
Guidelines for journalists and editors about reporting on robots, AI, and computers, an article by Ben Shneiderman.
AI and Responsible Journalism Toolkit, the Leverhulme Centre for the Future of Intelligence, University of Cambridge.

AIhub focus series

You can find articles relating to the UN sustainable development goals (SDGs) that we’ve covered in our focus series, to date, at the links below:
Good health and well-being
Climate action
Quality education
Life below water
Reduced inequalities
Affordable and clean energy
Life on land
Sustainable cities and communities

You can find all of the interviews in our New voices in AI series here.

The articles in our AI around the world series are here.

Guidelines

Guidelines for promoting your AI research – how to avoid AI hype



AIhub is supported by:






©2024 - Association for the Understanding of Artificial Intelligence


 












©2021 - ROBOTS Association