AWS AI Hours Singapore

About the event

Join us for a day dedicated to AI Engineering and Science. Dive deep into the technicalities of generative AI model training, fine-tuning, and inference on the cloud and in hybrid environments. Throughout the day, customize your learning experience and build your agenda from four specialized tracks, featuring expert-led sessions on Silicon for AI, Kubernetes for AI, Managing AI Training and Fine Tuning, High Performance File Systems, and AI Science topics. Experts featured include AWS AI specialists and AI scientists from AWS Generative AI Innovation Center, partners like Meta, LYMSYS, Weka and Rafay. This event delivers practical, implementation-focused knowledge that goes beyond basic concepts. With interactive sessions, technical demonstrations, and networking opportunities, this event is designed to equip you with the advanced skills needed to train and deploy the next generation of AI models.

How it works

Come together for the morning and afternoon keynotes, then customize your agenda with four breakout tracks to choose from. Throughout the day, check out the AWS and partner booth showcases. Network with peers and AWS experts at the end of the event over light snacks and drinks at the happy hour!

Highlights

AI on Amazon Elastic Kubernetes Service (EKS)

Generative AI Innovation Centre

Amazon SageMaker HyperPod

Who should attend

This event is intended for technical audiences working on generative AI development such as IT leaders, data CxOs, developers, data scientists, engineers, data and AI researchers, and AI architects. Sessions are of an intermediate or advanced level, covering best practices, details of service features, and technical demonstrations.

In collaboration with

Agenda

Time (SGT)	Session
8:00 AM	Registration and morning refreshments
9:00 AM	Morning Keynote by Meta Eissa Jamil, Llama Partner Engineer Leader, META
9:30 AM	Track 1.1 Leveraging NVIDIA GPUs on AWS for Gen AI models Track 2.1 Architecting Hybrid AI Platform on EKS Track 3.1 Sagemaker Jumpstart + Building datasets & Tuning models Track 4.1 Supercharging storage & KV caching for AI workloads on AWS with WEKA
10:30 AM	Track 1.2 Training and deploying Gen AI models with AWS AI Chips (Inferentia/Trainium) Track 2.2 Blueprint for Success: Architecting Modern AI Platforms on EKS with Rafay Track 3.2 Scalable Infrastructure for Large-Scale AI Training with AWS Sagemaker Hyperpod Track 4.2 Customizing LLMs with RLVR for Reasoning abilities
11:30 AM	Track 1.3 High Performance File Systems for AI workloads (FSx for Lustre) Track 2.3 Scaling LLMs on EKS: Building a Production-Grade Inference Platform with vLLM Track 3.3 SageMaker Inference for LLMs Track 4.3 Trends in Model Fine Tuning
12:30 PM	Lunch
1:30 PM	Afternoon Keynote \| SGLang: An Efficient Open-Source Framework for Large-Scale LLM Serving
2:00 PM	Afternoon keynote \| verl: An Open-Source Large-Scale LLM RL Framework for Agentic Tasks
2:30 PM	Track 1.1 Leveraging NVIDIA GPUs on AWS for Gen AI models Track 2.1 Architecting Hybrid AI Platform on EKS Track 3.1 Sagemaker Jumpstart + Building datasets & Tuning models Track 4.1 Supercharging storage & KV caching for AI workloads on AWS with WEKA
3:30 PM	Track 1.2 Training and deploying Gen AI models with AWS AI Chips (Inferentia/Trainium) Track 2.2 Blueprint for Success: Architecting Modern AI Platforms on EKS with Rafay Track 3.2 Scalable Infrastructure for Large-Scale AI Training with AWS Sagemaker Hyperpod Track 4.2 Customizing LLMs with RLVR for Reasoning abilities
4:30 PM	Track 1.3 High Performance File Systems for AI workloads (FSx for Lustre) Track 2.3 Scaling LLMs on EKS: Building a Production-Grade Inference Platform with vLLM Track 3.3 SageMaker Inference for LLMs Track 4.3 Trends in Model Fine Tuning
5:30 PM	Happy Hour

Time (SGT)	Session
8:00 AM	Registration and morning refreshments
9:00 AM	Morning Keynote by Meta Eissa Jamil, Llama Partner Engineer Leader, META speaker, title, company
9:30 AM	Track 1.1 Leveraging NVIDIA GPUs on AWS for Gen AI models Cheryl Abundo, Principal Solution Architect for Autonomous Computing, AWS
10:30 AM	Track 1.2 Training and deploying Gen AI models with AWS AI Chips (Inferentia/Trainium) Xiaoning Wang, Machine Learning Engineer, AWS Cheryl Abundo, Principal Solution Architect for Autonomous Computing, AWS
11:30 AM	Track 1.3 High Performance File Systems for AI workloads (FSx for Lustre) Ameen Khan S, Senior GTM Storage Specialist Solutions Architect, AWS
12:30 PM	Lunch
1:30 PM	Afternoon Keynote \| SGLang: An Efficient Open-Source Framework for Large-Scale LLM Serving Ke Bao, SGLang Core Developer & Member of LMSYS Org
2:00 PM	Afternoon keynote \| verl: An Open-Source Large-Scale LLM RL Framework for Agentic Tasks Jiarui Fang, VERL Engineer, ByteDance
2:30 PM	Track 1.1 Leveraging NVIDIA GPUs on AWS for Gen AI models Cheryl Abundo, Principal Solution Architect for Autonomous Computing, AWS
3:30 PM	Track 1.2 Training and deploying Gen AI models with AWS AI Chips (Inferentia/Trainium) Xiaoning Wang, Machine Learning Engineer, AWS Cheryl Abundo, Principal Solution Architect for Autonomous Computing, AWS
4:30 PM	Track 1.3 High Performance File Systems for AI workloads (FSx for Lustre) Ameen Khan S, Senior GTM Storage Specialist Solutions Architect, AWS

Time (SGT)	Session
8:00 AM	Registration and morning refreshments
9:00 AM	Morning Keynote by Meta Eissa Jamil, Llama Partner Engineer Leader, META speaker, title, company
9:30 AM	Track 2.1 Architecting Hybrid AI Platform on EKS Eng-Hwa Tan, Principal Containers Solutions Architect, AWS
10:30 AM	Track 2.2 Blueprint for Success: Architecting Modern AI Platforms on EKS with Rafay Eng-Hwa Tan, Principal Containers Solutions Architect, AWS Dennis Goh, Managing Director, Rafay
11:30 AM	Track 2.3 Scaling LLMs on EKS: Building a Production-Grade Inference Platform with vLLM Eng-Hwa Tan, Principal Containers Solutions Architect, AWS Girish Dilip Patil, Head of Technology, Generative AI, ASEAN, AWS
12:30 PM	Lunch
1:30 PM	Afternoon Keynote \| SGLang: An Efficient Open-Source Framework for Large-Scale LLM Serving Ke Bao, SGLang Core Developer & Member of LMSYS Org
2:00 PM	Afternoon keynote \| verl: An Open-Source Large-Scale LLM RL Framework for Agentic Tasks Jiarui Fang, VERL Engineer, ByteDance
2:30 PM	Track 2.1 Architecting Hybrid AI Platform on EKS Eng-Hwa Tan, Principal Containers Solutions Architect, AWS
3:30 PM	Track 2.2 Blueprint for Success: Architecting Modern AI Platforms on EKS with Rafay Eng-Hwa Tan, Principal Containers Solutions Architect, AWS Dennis Goh, Managing Director, Rafay
4:30 PM	Track 2.3 Scaling LLMs on EKS: Building a Production-Grade Inference Platform with vLLM Eng-Hwa Tan, Principal Containers Solutions Architect, AWS Girish Dilip Patil, Head of Technology, Generative AI, ASEAN, AWS

Time (SGT)	Session
8:00 AM	Registration and morning refreshments
9:00 AM	Morning Keynote by Meta Eissa Jamil, Llama Partner Engineer Leader, META speaker, title, company
9:30 AM	Track 3.1 Sagemaker Jumpstart + Building datasets & Tuning models Vasileios Vonikakis, Senior Solution Architect for Generative AI, AWS
10:30 AM	Track 3.2 Scalable Infrastructure for Large-Scale AI Training with AWS Sagemaker Hyperpod Keita Watanabe, Senior Worldwide Specialist Solutions Architect, Generative AI, AWS
11:30 AM	Track 3.3 SageMaker Inference for LLMs Melanie Li, Senior Specialist Solutions Architect, AWS
12:30 PM	Lunch
1:30 PM	Afternoon Keynote \| SGLang: An Efficient Open-Source Framework for Large-Scale LLM Serving Ke Bao, SGLang Core Developer & Member of LMSYS Org
2:00 PM	Afternoon keynote \| verl: An Open-Source Large-Scale LLM RL Framework for Agentic Tasks Jiarui Fang, VERL Engineer, ByteDance
2:30 PM	Track 3.1 Sagemaker Jumpstart + Building datasets & Tuning models Vasileios Vonikakis, Senior Solution Architect for Generative AI, AWS
3:30 PM	Track 3.2 Scalable Infrastructure for Large-Scale AI Training with AWS Sagemaker Hyperpod Keita Watanabe, Senior Worldwide Specialist Solutions Architect, Generative AI, AWS
4:30 PM	Track 3.3 SageMaker Inference for LLMs Melanie Li, Senior Specialist Solutions Architect, AWS

Time (SGT)	Session
8:00 AM	Registration and morning refreshments
9:00 AM	Morning Keynote by Meta Eissa Jamil, Llama Partner Engineer Leader, META speaker, title, company
9:30 AM	Track 4.1 Supercharging storage & KV caching for AI workloads on AWS with WEKA Ronald Peirara, Sr. Sales Engineer - ASEAN, WEKA
10:30 AM	Track 4.2 Customizing LLMs with RLVR for Reasoning abilities Bill Cai, Senior Applied Scientist, AWS Girish Dilip Patil, Head of Technology, Generative AI, ASEAN, AWS
11:30 AM	Track 4.3 Trends in Model Fine Tuning Bill Cai, Senior Applied Scientist, AWS Xiaogang Wang, Senior Applied Scientist, AWS
12:30 PM	Lunch
1:30 PM	Afternoon Keynote \| SGLang: An Efficient Open-Source Framework for Large-Scale LLM Serving Ke Bao, SGLang Core Developer & Member of LMSYS Org
2:00 PM	Afternoon keynote \| verl: An Open-Source Large-Scale LLM RL Framework for Agentic Tasks Jiarui Fang, VERL Engineer, ByteDance
2:30 PM	Track 4.1 Supercharging storage & KV caching for AI workloads on AWS with WEKA Ronald Peirara, Sr. Sales Engineer - ASEAN, WEKA
3:30 PM	Track 4.2 Customizing LLMs with RLVR for Reasoning abilities Bill Cai, Senior Applied Scientist, AWS Girish Dilip Patil, Head of Technology, Generative AI, ASEAN, AWS
4:30 PM	Track 4.3 Trends in Model Fine Tuning Bill Cai, Senior Applied Scientist, AWS Xiaogang Wang, Senior Applied Scientist, AWS