Florian Maximilian Stahl
Employers on the program
- 2024–2025Amazon Web Services3 talks
The year around now
Talks in the past 12 months and announced talks ahead, one row per conference, January to December. Hover a mark for the talk.
Appearances by year
- AWS re:Invent
Talks
| Date | Event | Conference | Role | Title | Links |
|---|---|---|---|---|---|
| Dec 1, 2025 | AWS re:Invent 2025 | AWS re:Invent | chalk talk | Scalable and resilient distributed AI with Ray on SageMaker HyperPod as AWS Join us to learn how to leverage Ray jobs on SageMaker HyperPod to build resilient, distributed AI workloads. Ray offers a unified programming model that allows…Show lessJoin us to learn how to leverage Ray jobs on SageMaker HyperPod to build resilient, distributed AI workloads. Ray offers a unified programming model that allows you to seamlessly scale applications from a single machine to a distributed cluster while SageMaker HyperPod offers a resilient infrastructure. | |
| Dec 2, 2024 | AWS re:Invent 2024 | AWS re:Invent | workshop | Accelerating distributed ML with containers & high-performance storage as Amazon Web Services In this workshop, learn how AWS storage can help increase the performance of machine learning (ML) training jobs and reduce the complexity for containerized…Show lessIn this workshop, learn how AWS storage can help increase the performance of machine learning (ML) training jobs and reduce the complexity for containerized environments using Amazon EKS. | |
| Dec 2, 2024 | AWS re:Invent 2024 | AWS re:Invent | builders session | Fine-tune Llama 3 models cost-effectively on Amazon SageMaker [REPEAT] as Amazon Web Services In this builders’ session, get step-by-step implementation experience fine-tuning Llama 3 8B using the QLoRA strategy. Learn how you can fine-tune Llama 3…Show lessIn this builders’ session, get step-by-step implementation experience fine-tuning Llama 3 8B using the QLoRA strategy. Learn how you can fine-tune Llama 3 models at scale using the memory-efficient PyTorch Fully Sharded Data Parallel (FSDP2) library with access to built-in debugging and GPU utilization metrics. |
Frequent co-speakers
| Speaker | Shared events | Shared talks | Last together |
|---|---|---|---|
| Arun Kumar Lokanatha | 2 | 1 | 2025 |
| Kanwaljit Khurmi | 2 | 1 | 2025 |
| Roy Allela | 2 | 1 | 2025 |
| Shreyas Adiyodi | 2 | 1 | 2025 |
| Tomonori Shimomura | 2 | 1 | 2025 |
| Aaron Chen | 2 | — | 2025 |
| Aaron Dailey | 2 | — | 2025 |
| Aaron Sempf | 2 | — | 2025 |
| Aarthi Raju | 2 | — | 2025 |
| Abbas Mooraj | 2 | — | 2025 |
| Abhi Khanna | 2 | — | 2025 |
| Abhi Shivaditya | 2 | — | 2025 |
| Abhijeet Jangam | 2 | — | 2025 |
| Abhilash Nagilla | 2 | — | 2025 |
| Abhishek Pandey | 2 | — | 2025 |
Speakers with the same name are merged into one entry, so this page may combine more than one person. Affiliations are shown as each conference listed them.