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

AWS re:Invent 2023 - Building applications with generative AI and live data (BOA307)

AWS re:Invent 2023 - Best practices for querying vector data for gen AI apps in PostgreSQL (DAT407)

AWS re:Invent 2023 - CEO Keynote with Adam Selipsky

Ultra-low latency vector search with Amazon MemoryDB | AWS Events

Prem Chandrasekaran - Optimizing the engineering value stream

Vector Search: Powering the Next Generation of Applications

AWS re:Invent 2023 - Accelerate mission outcomes with no-code and low-code machine learning (IMP209)

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

SecTor 2024: Hacking Deepfake Detection Systems | MTCC Canada

What is a vector database? Why are they critical infrastructure for #ai #applications?

AWS re:Invent 2023 - Amazon DynamoDB zero-ETL integration with Amazon OpenSearch Service (DAT339)

How to Start Coding | Programming for Beginners | Learn Coding | Intellipaat

AWS re:Invent 2023 - Building an AWS solutions architect agent with Amazon Bedrock (BOA306)

The Race to Harness Quantum Computing's Mind-Bending Power | The Future With Hannah Fry

AWS re:Invent 2023 - What's new with AWS Backup (STG203)

Machine Learning Tutorial | Machine Learning Basics | Machine Learning Algorithms | Simplilearn

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

Vector Databases and the Future of AI-powered Search - Sam Partee

RAG But Better: Rerankers with Cohere AI

AWS re:Invent 2023 - Building Falcon LLM: A top-ranked open source language model (WPS209)