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AIML Research Seminar: From Data to Discoveries - machine learning and optimisation in space
- Date: Tue, 28 May 2024
- Location: AIML
During his time as internal research fellow at the European Space Agency, Marcus M盲rtens organised several open competitions that paved the way for applying modern machine learning (ML) techniques to space-related challenges. This talk provided an overview of this process from the original idea to the preparation of the datasets, the management of the actual competitions, and an analysis of the resulting aftermath.
AIML Special Presentation: Google Research Visit
- Date: Thu, 16 May 2024
- Location: AIML
Generative LLMs are transforming multiple industries and have proven to be robust for multitude of use cases across industries and settings. One of the key impediments to their widespread deployment is the cost of serving and its deployability across multiple devices/settings. In this talk, Grace and Prateek discussed the key challenges in improving efficiency of LLM serving and provided an overview of some of the key techniques to address the problem. They also discussed tandem transformers and HIRE, novel methods to speed up decoding in LLMs.
[Read more about AIML Special Presentation: Google Research Visit]
CAR Special event - Data61
- Date: Tue, 7 May 2024
- Location: AIML
David and Lars presented an overview of their research interests and capabilities, highlighting their involvement in external projects. Afterwards, Dr Russell Tsuchida and Buse Turunctur discussed their research interests and possible collaborations.
AIML Special Presentation: Active Learning with Deep Neural Networks
- Date: Wed, 1 May 2024
- Location: AIML
In Active Learning the system gives select data to an expert to annotate, which is costly and should be minimised. Prof Butine proposes the first general Bayesian method to work well in this context, and his experiments show it is the only method consistently better than random.
[Read more about AIML Special Presentation: Active Learning with Deep Neural Networks]
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