AI Engineer

Build, Evaluate and Deploy a RAG-Based Retail Copilot with Azure AI: Cedric Vidal and David Smith

Lessons from the Trenches: Building LLM Evals That Work IRL: Aparna Dhinkaran

Aparna Dhinakaran from Arize discusses LLM evaluations and observability, differentiating between model evals and task evals, and focusing on the latter. She explains how LLMs are used as judges in real-world applications, particularly in chat-to-purchase e-commerce setups involving routers and function calls. Aparna e...

Accelerate your AI journey with Azure AI model catalog: Sharmila Chokalingam

AI Templates: Gabriela and Aishwarya

Multi model multimodal and multi agent innovations in Azure AI: Cedric Vidal

Which Jobs Can Be Replaced Today: Fryderyk Wiatrowski and Peter Albert

Creating and scaling your own custom copilots with Azure AI Studio: Hanchi Wang

Ionic Launch: Opening the economy to AI agents

EyeLevel Launch: Your RAG is Tripping, Here's the Real Reason Why

The Rise of the AI Software Engineer: Jesse Han

How to evaluate a model for your use case: Emmanuel Turlay

Building efficient hybrid context query for LLM grounding: Simrat Hanspal

Best Practices for Evaluating Large Language Model Applications with llmeval: Niklas Nielsen

BotDojo Launch: Enhancing AI Assistants with Evaluations and Synthetic Data

No-code fine-tuning: Mark Hennings

Prompt Engineering Tactics: Dan Cleary

Scaling AI in Education: A Khanmigo case study: Shawn Jansepar

Cohere for VPs of AI: Vivek Muppalla

Mastering LLM Inference Optimization From Theory to Cost Effective Deployment: Mark Moyou

Navigating Challenges and Technical Debt in LLMs Deployment: Ahmed Menshawy