James Yi
Employers on the program
- 2022–2025Amazon Web Services3 talks
Appearances by year
- AWS re:Invent
Talks
| Date | Event | Conference | Role | Title | Links |
|---|---|---|---|---|---|
| Dec 1, 2025 | AWS re:Invent 2025 | AWS re:Invent | builders session | Build reliable agents with Amazon Bedrock AgentCore Observability as Amazon Web Services Build customer trust by implementing comprehensive monitoring and debugging for your AI applications. | |
| Dec 2, 2024 | AWS re:Invent 2024 | AWS re:Invent | chalk talk | Accelerate generative AI from POC to production via AWS Marketplace [REPEAT] as Amazon Web Services As organizations seek to use generative AI for improving process efficiencies and enhancing customer experiences, many find themselves at a critical juncture:…Show lessAs organizations seek to use generative AI for improving process efficiencies and enhancing customer experiences, many find themselves at a critical juncture: moving from proof of concept (POC) to production. | |
| Nov 27, 2023 | AWS re:Invent 2023 | AWS re:Invent | chalk talk | Accelerate generative AI deployments with solutions in AWS Marketplace [REPEAT]Organizations are looking to use generative AI to improve process efficiencies and customer experiences through more efficient content generation,…Show lessOrganizations are looking to use generative AI to improve process efficiencies and customer experiences through more efficient content generation, personalization, summarizations, and more. | |
| Nov 27, 2023 | AWS re:Invent 2023 | AWS re:Invent | chalk talk | Powering generative AI use cases with vector databases on AWS [REPEAT] Vector databases are an often-overlooked generative AI technology, and there are a multitude of options on AWS. | |
| Nov 28, 2022 | AWS re:Invent 2022 | AWS re:Invent | breakout | Building a product review classifier with transfer learning as AWS Natural language processing (NLP) models allow you to build applications that can classify text at scale. By using Hugging Face transformers, you can build…Show lessNatural language processing (NLP) models allow you to build applications that can classify text at scale. By using Hugging Face transformers, you can build models specializing in various NLP tasks from text classification to text summarization. | SlidesVideo |
Frequent co-speakers
| Speaker | Shared events | Shared talks | Last together |
|---|---|---|---|
| Aaron Sempf | 4 | — | 2025 |
| Abbas Mooraj | 4 | — | 2025 |
| Abhishek Srivastav | 4 | — | 2025 |
| Adam Hill | 4 | — | 2025 |
| Aditya Samant | 4 | — | 2025 |
| Adnan Bilwani | 4 | — | 2025 |
| Ahuva Hazan-Fuchs | 4 | — | 2025 |
| Alan Halachmi | 4 | — | 2025 |
| Alex DeBrie | 4 | — | 2025 |
| Alexander Dragunov | 4 | — | 2025 |
| Alexandra Huides | 4 | — | 2025 |
| Alexis Marcou | 4 | — | 2025 |
| Ali Alemi | 4 | — | 2025 |
| Ali Saidi | 4 | — | 2025 |
| Alicia Morrison | 4 | — | 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.