Master AI development with LangChain tools. Build, prototype and monitor LLM apps using LangChain, LangGraph, LangFlow and LangSmith diagrams included.
Build a voice-enabled AI nutrition coach using GPT-4, Gradio, and gTTS. This beginner-friendly tutorial walks you through every step, from setup to deployment.
In the finale of this series, I use the A2A protocol to let my AI agents communicate and delegate tasks—unlocking true collaboration and orchestration.
Discover how Modal enables developers to run scalable Python-based AI and data workloads in the cloud, without managing servers, containers, or GPUs directly.
Based on real-world experience, this article explores how AI-powered Agentic DBAs are redefining database management through autonomy and intelligence.
This guide explains how N-gram language models work, how they estimate probabilities, handle unknown words, and evaluate performance using perplexity and other methods.
Domain-Specific Languages (DSLs) offer targeted solutions for rule-heavy domains. With GenAI, creating and managing DSLs becomes faster, easier, and more collaborative.
Langflow lets you visually build, test, and deploy LLM-powered apps, no backend coding required. Ideal for rapid GenAI prototyping and seamless integration.
The growing importance of Gen AI in software engineering isn’t just a buzz—it’s a shift that’s rewriting how we work and innovate in software engineering.
I created a team of specialist agents to handle different parts of a complex task. It's basically microservices for AI, making our app smarter, easier to update and more.
Revolutionizing real-time application development by combining high-performance, secure, and platform-independent computing with local AI-driven decision-making