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YouTube-Claude
2023/03/22Overview of Anthropic Claude 3
Explanation of the RAG system using MongoDB and Anthropic's Opus
Article, Dataset and code repository
Dataset Overview
Step-by-step guide to installing necessary libraries and setting up the environment
Loading and cleaning the dataset for use in the RAG system
Creation of MongoDB database and collection setup
How to create a vector search index in MongoDB
Connecting to MongoDB and ingesting the dataset
Implementing the vector search function
Explanation of converting user queries into embeddings
Using Anthropic's API to implement the RAG system
Formatting the query results and integrating with the Opus model
Example query and response from the RAG system
Review of the articles used to generate the system's advice
Final thoughts and invitation for suggestions on future content
Introduction
Tell us about the Claude 3 launch.
What's constitutional AI?
Can you share examples of Anthropic success with customers?
What does success look like for enterprises and consumers?
What are the options for deploying Anthropic models through Amazon's Bedrock?
What's your experience with Salesforce and Slack?
What will AI models get better at in the next few years?
What are the key building blocks to improve AI?
Can you describe the day-to-day at Anthropic?
How do large language models (LLM's) work?
How do we educate the next generation to succeed in an AI era?
What does AI look like in 2034?
What advice do you have for Trailblazers in the next 12 months?
Can you talk about how you shifted from physics to AI?
What has it been like to be a part of so many milestones in AI?
What are Anthropics goals?
Three takeaways from Clara