Event Archive

2022

October

• An information-theoretic framework for grounded dialogue modelling

  12 October 2022, 14:00 - 15:00

  What are the decision making processes by which humans choose words to achieve goals in their environment? Can we replicate them in a computer system? These are the core questions of grounded dialogue modelling, the study of interactive language use in context. We will start by looking at a few...

September

• Aligning the use of AI in business to real world opportunities

  21 September 2022, 12:00 - 13:00

  A session to present how organisations with their in-built challenges need to be carefully managed to accept the inevitably of AI systems in their daily work processes.   Examples will be shared of real world scenarios and where AI is already adding value and what the future could look like as...

June

• Accelerating Research Software Understandability Through Knowledge Capture

  15 June 2022, 14:00 - 15:00

  Research Software is key to understand, reproduce and reuse existing work in many disciplines, ranging from Geosciences to Astronomy or Artificial Intelligence. However, research software is usually difficult to find, reuse, compare and understand due to its disconnected documentation (dispersed in manuals, readme files, web sites, and code comments) and...

• Decolonising science

  08 June 2022, 14:00 - 15:00

  The phrase “decolonising the curriculum” very much seems like a buzzword, but what does it really mean?   In particular, what does it mean for sciences?   I intend to explore the background to “decolonising science”, address some of the issues that this raises, and look at some ideas which not only...

• A Personal Perspective on Impact

  01 June 2022, 14:00 - 15:00

  Most of our funders would like to see non-academic "impact" from the projects they support. In this talk, I'll give a personal perspective on impact, looking at both successes such as the Arria NLG spinout company and the simplenlg open-source package, and failures where expected impact did not materialise, such...

May

• Representation Learning for Relational and Cross-Lingual Data

  18 May 2022, 14:00 - 15:00

  Utilising real-world relational signals (e.g., structured knowledge) and understanding different languages are two (of the many) fundamental goals of Artificial General Intelligence. The corresponding explorations, however, have been relatively separate. In this talk, I will introduce our recent research outputs on bridging this gap:  - We discovered the unnoticed connections between...

• The challenge of adherence to digital healthcare - the case of ASICA

  11 May 2022, 14:00 - 15:00

  Patient-directed digital healthcare delivery is becoming increasingly prominent and has received impetus from the recent COVID pandemic. Patient-directed digital healthcare is viewed positively by policy makers as a means to increase healthcare access, reduce costs and increase efficiency. Patient-directed digital healthcare also appears to be popular with certain patient groups....

April

• Evolutionary Multi-objective Learning and its Application to Metabolic Engineering Design

  13 April 2022, 10:00 - 11:00

  Many real-world applications involve optimisation of multiple conflicting objectives simultaneously. Examples include maximizing comfort and minimizing cost while buying or rent a home, minimizing the cost and maximizing the durability of constructed structures, and minimizing the traveling cost and maximum cover of distance.  Such multi-objective optimisation problems require solutions that...

March

• Intention Progression in Multi-Agent Settings

  30 March 2022, 14:00 - 15:00

  A key problem for rational agents is 'what do do next': which goal the agent should be trying to achieve, and which means it should use to achieve it. In the Belief-Desire-Intention approach to agents, this is termed the 'intention progression problem', and has largely been studied in a single...

February

• Realising Accountability and Audit of AI Systems Using Knowledge Graphs

  09 February 2022, 14:00 - 15:00

  To realise accountable AI systems, different types of information from a range of sources need to be recorded throughout the system life cycle. In the RAInS project, we argue that knowledge graphs can support capture and audit of such information; however, the creation of such accountability records must be planned...