Events

Join Isaac, a Data Scientist from GovTech’s AI Practice, as he shares his experience empowering developers in government to build effective RAG (and more generally, LLM-based) applications. Discover his team’s approach to evaluating RAG and learn how developers can build and iterate their RAG pipelines more systematically. […]

In this talk, we will delve into my personal journey as a UX designer, highlighting the essential design processes that drive successful projects. We will discuss the myriad opportunities available in the field, from emerging technologies to innovative methodologies, and how these can shape your career trajectory. To enrich our discussion, I am excited to introduce my colleague, a seasoned UX researcher, who will present for 15-20 minutes on the UX research process. He will cover key methodologies, tools, and techniques used to gather user insights that inform design decisions. […]

This talk will “delve” into Cohere’s strategies for harnessing the potential of Large Language Models (LLMs) within the enterprise domain. By exploring fine-tuning techniques and the integration of Retrieval Augmented Generation (RAG), we aim to showcase how these methods can be tailored to solve complex, industry-specific challenges. […]

This talk will present some key techniques in modern LLM pre-training, including scaling laws, data quality engineering, data mixture optimization, and efficient training strategies. We will use Sailor, a family of open language models (0.5B to 14B parameters) tailored for South-East Asian languages, as a case study. […]

Generative modelling (GM) has advanced significantly in recent years, especially in computer vision, where it is used for various purposes, from supplementing limited sample datasets to creating art. As GMs become more integrated into our daily activities, discussions about their efficacy are becoming more prevalent. This is largely due to the potential biases they may contain, which could then influence downstream tasks and proliferate biases in society. In this dissertation, we make important contributions in improving fairness in generative models by identifying and addressing constraints which may limit their broader adoption. […]

Understanding and analyzing animal behaviors is crucial for gaining profound insights into the health, needs, and overall well-being of the animal. This involves measuring and monitoring factors such as size, growth, poses, and actions. The analysis of animal behavior holds significant importance in a wide range of domains and industries, such as livestock farming, veterinary sciences, scientific research, ecological and conservation studies. […]

We explore the modern application of deep learning techniques in portfolio construction, presenting innovative methodologies that significantly enhance traditional investment strategies. Central to this research are three advanced frameworks that leverage deep learning to optimize financial portfolios. […]

Neural networks are known to be over-parametrized and sparse models have been shown to perform as well as dense models over a range of image and language processing tasks. However, while compact representations and model compression methods have been applied to speech tasks, sparsification techniques have rarely been used on text-to-speech (TTS) models. We seek to characterize the impact of selected sparse techniques on the performance and model complexity. […]

This talk will provide an insightful glimpse into the world of defence R&D, shedding light into an often secretive industry and hopefully inspire aspiring graduates to consider a career in the Defence Technology Community. […]

3D digital human has been widely used in fields like virtual reality, fashion, and film/game production. Traditionally, creating and animating digital humans requires skilled engineers and expensive equipment, typically accessible only to large companies. Thus, developing deep learning tools to democratize the creation and animation of digital humans is urgently needed. […]