See How AI Agents Get Smarter With Data Flywheel!
## 📊 Building Scalable AI Agents with Data Flywheel | NVIDIA NeMo Microservices Full Walkthrough Dataflywheel: https://nvda.ws/4jmmJlu In this video, we explore the **Data Flywheel** – a powerful framework to create AI agents at scale. Learn how **data processing, model customisation, model evaluation, guardrails, and information retrieval** work together to build efficient, safe, and accurate AI agents. This video breaks down the essential components for building **AI agents** at **AI scale** using the **data curation** process. It highlights the importance of data processing, model customisation through **fine-tuning**, and ensuring reliability with guardrails. Learn how these elements come together to create powerful **AI-driven systems**. We’ll walk you through **NVIDIA NeMo Microservices**, including: * 🛠️ NeMo Curator * ⚙️ NeMo Customizer * ✅ NeMo Evaluator * 🛡️ NeMo Guardrails * 🔍 NeMo Retriever See how **NVIDIA's NV InfoBot** works using a real-world example to answer complex enterprise questions by retrieving private data with fast, accurate responses. 👉 You’ll also learn how to: * 🚀 Deploy the Data Flywheel on the cloud * 💻 Run it on your own server * 🔧 Fine-tune small models to achieve performance comparable to large 70B models * 🗂️ Process and load custom datasets * 🔁 Continuously retrain using updated data via API endpoints By the end, you’ll know how to set up, customise, and deploy an **AI-powered customer service assistant** using NVIDIA’s tools. 📌 Timestamps: 00:00 – What is Data Flywheel? 01:00 – NVIDIA NeMo Microservices Explained 03:00 – Full Step-by-Step Tutorial Starts 05:00 – Loading Data and Starting Training 07:00 – Model Evaluation and Accuracy Results 09:00 – Final Thoughts and Next Steps 👍 If you found this helpful, please like, subscribe, and comment your thoughts or questions! #NVIDIA #DataFlywheel #NeMo #AIagents #AITutorial #CloudAI #ModelFineTuning #APIAutomation
