Here is a list of event, includes speaker session and other intermediate slots (e.g. lunch):
This chalk talk delves into optimizing and deploying large language models (LLMs) at scale. Explore large model hosting, optimization techniques, model partitioning, batch processing, and model fine-tuning.
There are times when using official statistics might not immediately suit your usagemight not immediately suit your usage. This presentation illustrates some innovative ways to overcome the gaps, seeing the unseen data insights for public policy research.
Identification of spatial patterns of deprivation in Hong Kong, that extend beyond low income definitions, helping identify locations of greatest need
Since Android 14, Google has officially recommended migrating from Foreground Services to WorkManager for dataSync-related jobs. This talk aims to share how this can be done for different use cases, issues that may arise, and workaround for them.
PMPC(Public Money, Public Code) is a concept promoted by EU since 2017. Which is a good for promoting the free/open-source culture, yet still leave some pitfalls which might be used to underturn the original ideal if not executed carefully. This talk gives a brief introduction of PMPC, followed by reviewing certain failed cases in Taiwan in the past 20 years and what still going wrong right now.
While writing a Dockerfile is easier than ever (AI can help you generate a sample in a second!), but the resulting images might not be good enough. In this talk, we will discover a comprehensive guide to optimizing Docker images for JVM applications. Learn a series of tactics to reduce image size, speed up build time, and enhance overall performance and developer experience. We will illustrate the performance improvements achieved by applying these tactics to commonly used web frameworks. Additionally, we will explore the use of Gradle plugins to streamline the optimization process.
The library code of the Linux kernel contains numerous fundamental data structures and algorithms, mostly located in the lib/ directory. These have been refined by many skilled developers, resulting in highly efficient implementations. However, further optimization possibilities remain. This talk introduces how data structures and algorithms used in the Linux kernel are implemented, along with recent optimization contributions made to the Linux kernel.