AI

Research Disclaimer This tutorial is based on: OpenAI GPT-4 API (as of January 2025) LangChain v0.1.0+ with langchain-community v0.0.20+ (LLM orchestration framework) Pinecone v3.0+ (vector database with new Serverless API) FastAPI v0.109+ (high-performance Python web framework) Streamlit v1.30+ (rapid UI development) ChromaDB v0.4+ (open-source vector database) Sentence Transformers v2.3+ (embedding models) Rasa v3.6+ (traditional NLP chatbot framework) All implementation patterns follow production best practices for enterprise chatbot deployments. Code examples have been tested with production workloads as of January 2025. Note: Pinecone v3.0 introduced significant API changes moving to a Serverless architecture; all code uses the updated API patterns. ...

Scalable Serverless AI/ML Pipelines: A Production Guide Research Disclaimer: This guide is based on AWS SDK for Python (boto3) v1.34+, SageMaker Python SDK v2.200+, and AWS Step Functions State Language (Amazon States Language) official documentation. All code examples follow AWS Well-Architected Framework for ML workloads and include production-tested patterns for serverless deployment, monitoring, and cost optimization. Serverless ML pipelines eliminate infrastructure management while providing automatic scaling, pay-per-use pricing, and high availability. This guide covers production-ready patterns for deploying ML models using AWS Lambda, SageMaker, Step Functions, and EventBridge, with complete working examples that you can deploy immediately. ...

As a SOC analyst, one of the most critical tasks is analyzing network flow data to identify potential security threats. In this post, we’ll explore how to combine cloud-based data storage, SQL querying, and AI-powered analysis to streamline this process. Collecting Flow Data in Amazon Athena Amazon Athena provides a serverless query service that makes it easy to analyze data directly in Amazon S3 using standard SQL. Here’s how we set up our flow data collection: ...

Update (January 2026): The AI landscape has evolved dramatically since this post was written in July 2024. GPT-4, mentioned below, has been succeeded by GPT-5 and GPT-5.2. Claude has advanced to Opus 4.5, and Google released Gemini 3 with a 1-million token context window. The core message of this post - that AI is becoming accessible to everyone - has only accelerated. The tools mentioned (AutoML, no-code platforms) have matured significantly, and new players have entered the market. The democratization trend continues at an even faster pace than predicted. ...

I spent today neck deep in rego so I thought it would be fun to take a break from documenting something technical and instead talk about a funny moment in AI tinkering. Yes, Artificial Intelligence is the latest buzz so it just makes sense to blog about it, right? Also, yes, there’s a minor plug embedded in here for my wife and daughter and their business. I’m a geek. I am not a marketing wiz. If you’ve read my blog so far, you know I have my own version of English. I’m also very horrible at writing product descriptions and things of the sort. I’ve been helping my and wife put together stuff for their handmade soap business, Momma Bears Creations (That’s the shameless plug). ...