AWS re:Invent 2023 - Use RAG to improve responses in generative AI applications (AIM336)

AWS re:Invent 2023 - Data patterns for generative AI applications (DAT338)

AWS re:Invent 2023 - Choosing the right generative AI use case (AIM212)

AWS re:Invent 2023 - I didn’t know Amazon API Gateway did that (SVS323)

AWS re:Invent 2023 - Best practices for serverless developers (SVS401)

The Art of Embracing Failures

AWS re:Invent 2023 - Generative AI for decision-makers (TNC214)

Ragsys Webinar

Andrew Ng: Opportunities in AI - 2023

AWS re:Invent 2023 - Simplify generative AI app development with Agents for Amazon Bedrock (AIM353)

How to build Multimodal Retrieval-Augmented Generation (RAG) with Gemini

Prompt Engineering, RAG, and Fine-tuning: Benefits and When to Use

AWS re:Invent 2023 - Utilizing machine learning & vector databases for advanced AI search (BOA312)

Data Analytics for Beginners | Data Analytics Training | Data Analytics Course | Intellipaat

AWS re:Invent 2023 - Innovate faster with generative AI (AIM245)

AWS re:Invent 2023 - Evaluate and select the best FM for your use case in Amazon Bedrock (AIM373)

AI and Human Collaboration - a future with AI Agents - Felipe Augusto Chies & András Kővári (AWS)

AWS re:Invent 2023 - Generative AI: Architectures and applications in depth (BOA308)

AWS re:Invent 2023 - Putting your data to work with generative AI | AIM250-INT

AWS re:Invent 2023 - Prompt engineering best practices for LLMs on Amazon Bedrock (AIM377)

AWS re:Invent 2023 - Accelerate generative AI application development with Amazon Bedrock (AIM337)