This unit introduces students to a range of methodologies and applications across the field of AI. Each week will focus on a different theme, with three activities:
This is a new unit, and you are a small cohort, so please do give us feedback at any time on how we can make the unit work better! In particular, if you find some topics assume prior knowledge you don't have, or would like to go further into certain topics, let us know.
Please see below for some great all-round
on MS Teams. Please do use it to ask us questions, discuss AI topics you are interested in, post interesting blogs, videos or papers, etc...
Week |
Reading (to complete before Monday's lecture) |
Guest Seminar |
Discussion chair (Link to spreadsheet with session chairs) |
Lecturer responsible |
TB1
1 (w/c 16/09/24) |
Data and labels for image and Video understanding:
- ImageNet, the competition that kick-started the deep learning revolution in Computer Vision
- Kitti, a highly impactful dataset in vision and robotics.
- Optional extra: The winner of the ImageNet 2015 competition, ResNet.
|
Dima Damen -- tutorial on data and labels for video understanding
|
Jono
|
ES |
2 (w/c 23/09/24) |
Text embeddings and sequence processing:
|
Edwin Simpson
|
Moses
|
ES |
3 (w/c 30/09/24) |
Attention and Transformers. Both of the following are really good introductions to attention and transformers
- you can pick one to read, or go through both if that helps your understanding. Please cover one of these before Monday:
For the Friday reading group, please also read:
|
Mike Wray
|
James
|
ES |
4 (w/c 07/10/24) |
Large language models:
|
Conor Houghton -- linguistic perspectives on LLMs
|
|
ES |
5 (w/c 14/10/24) |
Philosophy of AI:
|
James Ladyman
|
Berenika
|
JC |
6 (w/c 21/10/24) |
CONSOLIDATION WEEK
|
(no seminar/reading group)
|
|
7 (w/c 28/10/24) |
Knowledge representation and reasoning:
-
R. Davis, H. Shrobe, and P. Szolovits. What is a Knowledge Representation? AI Magazine, 14(1):17-33, 1993 (16pp. + references)
-
Delgrande, J. P., Glimm, B., Meyer, T., Truszczynski, M., and Wolter, F. (2023). Current and future challenges in knowledge representation and reasoning. arXiv preprint arXiv:2308.04161 (30pp. + appendices and an extensive bibliography)
- Additional
reading: What
are Non-classical Logics and Why Do We Need Them? An Extended
Interview with Dov Gabbay and Leon van der Torre
|
Peter Flach
|
Moses
|
JC |
8 (w/c 04/11/24) |
Bayesian inference and decision making:
|
Laurence Aitchison (slides)
|
Jack
|
JC |
9 (w/c 11/11/24) |
Causality:
|
James Cussens
|
|
JC |
10 (w/c 18/11/24) |
Bias, fairness and transparency:
|
Miranda Mowbray
|
Jake
|
JC |
11 (w/c 25/11/24) |
Ethical and regulatory frameworks of AI:
- Charlesworth, A. Regulating Algorithmic Assemblages: Looking Beyond Corporatist AI Ethics, in Kohl, U. and Eisler, J. (eds.) (2022) Data-Driven Personalisation and the Law. Cambridge University Press.
- Charlesworth A. AI Regulation in the UK in Raposo, V.L. (ed.) The European Artificial Intelligence Act, Springer (forthcoming 2025).
-
Additional Reading: Guihot, M., Matthew, A. F., and Suzor, N. P., (2020)
Nudging Robots: Innovative Solutions to Regulate Artificial Intelligence, Vanderbilt Journal of Entertainment and Technology Law 20, 385-456.
-
Additional Reading: EU Artificial Intelligence Act (Regulation (EU) 2024/1689) Chapter II
- Prohibited AI Practices, Article 5 ; Chapter III- High
Risk AI Systems, Arts. 6-17; Chapter V - General-Purpose AI
Models, Arts. 51-56; Chapter X - Codes of Conduct &
Guidelines, Art.95.
|
Andrew Charlesworth
|
Jack
|
JC |
12 (w/c 09/12/24) |
Assessment period
|
TB1 essay due
|
|
TB2
13 (w/c 13/01/25) |
Discrete and continuous optimisation:
|
James Cussens
|
David
|
JC |
14 (w/c 20/01/25) |
Reinforcement learning:
|
Taku Yamagata
|
Berenika
|
ES |
15 (w/c 27/01/25) |
Tactile robotics:
Nathan has kindly provided us a sneak preview of two of his papers:
you can find them here on Blackboard
(you'll need to log in first). Please don't share the papers as they have not yet been published.
|
Nathan Lepora
|
Jono
|
ES |
16 (w/c 03/02/25) |
Multi-agent systems:
-
Please skim through this chapter: Gerhard Weiss (2013). 2013. Intelligent agents. In Multiagent
Systems, 2nd ed., pages 3--50. MIT Press. [eBook available
through University
of Bristol library]
-
Pradeep
K. Murukannaiah, Nirav Ajmeri, Catholijn Jonker, and
Munindar P. Singh. New Foundations of Ethical Multiagent
Systems. Proceedings of the 19th International Conference on
Autonomous Agents and Multiagent Systems (AAMAS), Blue Sky
Idea Track, Auckland, May 2020, pages 1706--1710.
-
Jessica
Woodgate, Paul Marshall, and Nirav Ajmeri. Operationalising
Rawlsian Ethics for Fairness in Norm-Learning
Agents. Proceedings of the 39th AAAI Conference on
Artificial Intelligence (AAAI), Philadelphia, Feb 2025,
pages 1--9.
|
Nirav Ajmeri
|
Bezawit
|
JC |
17 (w/c 10/02/25) |
Weak supervision:
|
Raul Santos-Rodriguez
|
James
|
ES |
18 (w/c 17/02/24) |
CONSOLIDATION WEEK
|
No seminar/reading group
|
|
19 (w/c 24/02/25) |
Learning from Temporal Data for Healthcare:
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|
Zahraa Abdallah
|
Berenika
|
JC |
20 (w/c 03/03/25) |
Explainable and interpretable AI:
placeholder,
|
Weiru Liu
|
Jake
|
ES |
21 (w/c 10/03/25) |
Privacy:
placeholder,
|
Miranda Mowbray
|
Jack
|
JC |
22 (w/c 17/03/25) |
AIOps and deploying AI in production:
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|
TBC
|
Bezawit
|
ES |
23 (w/c 24/03/25) |
Human-in-the-loop AI -- design and evaluation:
placeholder,
|
Kenton O'Hara
|
James
|
ES |
24 (w/c 16/09/24) |
Assessement preparation week
|
TB2 essays due
|
|
At the end of each Teaching Block students submit an essay of about 5,000 words (10 pages) on a research topic jointly chosen by them and their Academic Mentor.
The essay should describe the background, state of the art, and open challenges with regard to the chosen topic.
Each essay is assessed on a pass/fail basis in terms of scholarly content and academic writing.
Narrative feedback is also provided, indicating strong points as well as areas for improvement. Passing the unit requires passing both essays.
More guidance will be provided by the unit lecturers during the first term.
to books. Youtube has many video lectures, including
, which is very good.