Sean Smith
Employers on the program
- 2026Lambda1 talk
- 2022–2024Amazon Web Services2 talks
Appearances by year
- AWS re:Invent
- STAC Summit
Talks
| Date | Event | Conference | Role | Title | Links |
|---|---|---|---|---|---|
| May 20, 2026 | STAC Summit New York, Spring 2026 | STAC Summit | speaker | From GPUs to Production: How Financial Institutions Deploy AI with Hands-On ML as Lambda | |
| Dec 2, 2024 | AWS re:Invent 2024 | AWS re:Invent | builders session | Accelerate FM pre-training on Amazon SageMaker HyperPod [REPEAT] as AWS Amazon SageMaker HyperPod removes the undifferentiated heavy lifting involved in building and optimizing machine learning (ML) infrastructure for training…Show lessAmazon SageMaker HyperPod removes the undifferentiated heavy lifting involved in building and optimizing machine learning (ML) infrastructure for training foundation models (FMs), reducing training time by up to 40%. | |
| Nov 27, 2023 | AWS re:Invent 2023 | AWS re:Invent | builders session | Build and train state-of-the-art FMs on Amazon SageMaker [REPEAT] Amazon SageMaker offers advanced training tools to help you accelerate scalable, reliable, and secure generative AI application development. | |
| Nov 27, 2023 | AWS re:Invent 2023 | AWS re:Invent | chalk talk | Design, engineering & simulation on AWS using HPC & virtual desktops This chalk talk shows you how to combine HPC workloads with cloud-based virtual desktops. | |
| Nov 27, 2023 | AWS re:Invent 2023 | AWS re:Invent | builders session | PyTorch best practices for generative AI & LLM inference architectures [REPEAT]Generative AI and large language models (LLMs) are rapidly disrupting workflows. Inference architectures for these large-scale models need to be carefully…Show lessGenerative AI and large language models (LLMs) are rapidly disrupting workflows. Inference architectures for these large-scale models need to be carefully constructed to achieve optimal cost performance. | |
| Nov 28, 2022 | AWS re:Invent 2022 | AWS re:Invent | chalk talk | A day in the life of a cloud-empowered aerodynamics engineer as AWS Imagine yourself as an aerodynamics engineer who uses computational fluid dynamics (CFD) to design new cars and planes, and you want the fastest turnaround…Show lessImagine yourself as an aerodynamics engineer who uses computational fluid dynamics (CFD) to design new cars and planes, and you want the fastest turnaround times while retaining accuracy. This interactive chalk talk walks through techniques for optimizing complex workflows by combining AWS capabilities with optimization tricks to reduce simulation time for popular CFD codes such as OpenFOAM... | Slides |
Frequent co-speakers
| Speaker | Shared events | Shared talks | Last together |
|---|---|---|---|
| Kanwaljit Khurmi | 3 | 1 | 2024 |
| Aaron Sempf | 3 | — | 2024 |
| Aaron Sengstacken | 3 | — | 2024 |
| Abbas Mooraj | 3 | — | 2024 |
| Abhay Saxena | 3 | — | 2024 |
| Abhinav Jawadekar | 3 | — | 2024 |
| Abhisheikh Lahoti | 3 | — | 2024 |
| Abhishek Srivastav | 3 | — | 2024 |
| Adam Hill | 3 | — | 2024 |
| Adam Keller | 3 | — | 2024 |
| Adam Palmer | 3 | — | 2024 |
| Adam Seligman | 3 | — | 2024 |
| Adam Wagner | 3 | — | 2024 |
| Aditya Samant | 3 | — | 2024 |
| Adnan Bilwani | 3 | — | 2024 |
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.