
How do you give an AI system your specific knowledge?
Try a live AI chatbot powered by RAG (Retrieval Augmented Generation) that knows my content. See how AI systems can be grounded with specific data to avoid hallucinations.
🔥 Free Tutorial: Build a "Chat with My Data" app with LangChain, Pinecone, OpenAI and the Vercel AI SDK.
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Explore how large language models process and break down text into tokens for understanding.
Understand how language models process and interpret text at the token level
Learn how vectors represent data in AI systems and the mathematical principles that power them.
Create powerful semantic search capabilities with vector embeddings
Learn core data science tools and concepts for effective machine learning and analysis workflows.
Accelerate development time and ship AI applications with production-ready architectures
Discover proven patterns and approaches for designing and implementing robust AI systems.
Accelerate development time and ship AI applications with production-ready architectures
Build real-world machine learning projects through hands-on tutorials and code examples.
Accelerate development time and ship AI applications with production-ready architectures
Learn how to enhance LLMs with external knowledge sources to reduce hallucinations and improve accuracy.
Build AI systems that can access and reason with external knowledge sources
Master techniques for customizing pre-trained language models to perform specific tasks in your domain.
Customize LLMs for specific tasks with higher accuracy and lower costs
Design vector database backed applications that efficiently handle millions of queries.
Design vector databases that scale to handle millions of queries efficiently
Implement fine-grained security controls for RAG systems and document management on AWS.
Ensure your AI systems enforce proper access controls to sensitive information
Learn to create a chatbot that answers questions about your content.
“Thanks for publishing the tutorial, very helpful.”
Scott McCallum • Full Stack Developer at Intermine
Learn by doing! Explore how AI systems work under the hood through hands-on interactive experiences.
Try a live AI chatbot powered by RAG (Retrieval Augmented Generation) that knows my content. See how AI systems can be grounded with specific data to avoid hallucinations.
Visualize how text transforms into vectors that capture semantic meaning. See why similar concepts cluster together and understand the foundation of RAG systems.
See how language models break text into tokens. Understand why context windows exist, how pricing works, and optimize your prompts for better performance.
Explore my comprehensive library of AI engineering resources and implementation guides.
I tried a handful of services when I last needed to fine-tune an LLM, and I was mostly disappointed...
A step by step tutorial with companion notebook.
One of the better Jupyter Notebooks to GPU-backed environment experiences I've had...
I trained a neural net to recognize hand-drawn digits, then built a Next.js UI for it
You can chat with my writing and ask me questions I've already answered even when I'm not around
I wrote the RAG evaluation chapter for Pinecone's latest book
AI assisted developer tooling is not created equally...
It's been about a year since I last looked at Codeium - what has changed?
I have open sourced my automations project, which is a collection of shell scripts that automatically handle git operations, provide local code reviews, pull requests, and more!
Design your side projects, blog posts and even your fun experiments to triangulate multiple learning paths simultaneously. Then, use them to build out your portfolio.
Control your own destiny, build your personal brand, and master web technologies by running your own tech blog.
Going the extra mile only to be unrewarded by your company feels like a personal slight and a waste of your time. It is not.
I show step by step how to build a RAG chatbot to talk to your data in this easy to follow tutorial for beginners.
Did you know you can use ChatGPT in your terminal? No more copying and pasting...
Vector databases explained, featuring clowns, embeddings, neural networks, feature extraction, semantic search and Retrieval Augmented Generation (RAG).
A step-by-step walkthrough on how to generate arbitrary system load and flex Pinecone Serverless
Deploy production-ready systems using Pinecone in minutes with the AWS Reference Architecture
An examination of the Reference Architecture components and functionality