Manual prompt crafting doesn't scale. In this session, we'll explore how to replace it with a test-driven, automated approach. You'll see how to define output evaluators, write minimal prompts, and let agents iterate toward optimal performance—all without…

Build invincible apps with Temporal's open source durable execution platform. Eliminate complexity and ship features faster. Talk to an expert today!

In this workshop, you’ll learn how to use Heroku Managed Inference and Agents to build agentic applications. We’ll cover how to provision and deploy LLM models to your app, run untrusted code securely in Python, Node.js, Go, and Ruby using built-in tools…

The rapid progress in LLM capability has not translated to increased reliability for business critical AI use cases. The root-cause? Data is ""not ready"".
Conversational analytics doesn't go beyond the analyst team because it's hard to verify if the generated…

You’ve trained the model—now it’s time to train the business. This talk dives into the engineering behind pricing systems that can evolve as fast as your AI stack.

Orb CTO Kshitij Grover will walk through how leading AI companies design infrastructure to…

Agentic workflows often become complex, brittle, and hard to maintain when they need to retrieve and reason across both structured data (typically requiring precise query execution) and unstructured data (commonly handled via vector search in RAG). In this…

Jonathan Larson is a Senior Principal Data Architect at Microsoft Research working in Special Projects(opens in new tab). He currently leads a research team focused on the intersection of graph machine learning, LLM memory representations, and LLM orchestration.…

Advanced GraphRAG techniques apply graph ML and algorithms, wrapped into tidy notebooks.

About Alison Cossette
Alison Cossette is a dynamic Data Science Strategist, Educator, and Podcast Host. As a Developer Advocate at Neo4j specializing in Graph Data…

Are you ready to give your AI agents a memory upgrade?
Join us for a fast-paced workshop exploring how memory can transform your agents.

What You'll Do:
Learn Leading Memory Solutions: Gain practical experience with open-source tools like Neo4j, Cognee,…

You're trying to guide how your agents think and act. Code-orchestrated workflows are too rigid, but LLMs charting their own course feel too chaotic. When you need a middle ground, it’s time to reach for the secret weapon: ontologies. These graph-shaped fragments…

In this hands-on workshop, you will build a multimodal AI agent capable of processing mixed-media content—from analyzing charts and diagrams to extracting insights from documents with embedded visuals. Using MongoDB as a vector database and memory store,…

The H1 2025 issue of the ESET Threat Report reviews the key trends and developments that shaped the threat landscape from November 2024 to May 2025

*Thank You for Watching!*Support my work and help spread Bitcoin education:⚡ Send Bitcoin over Lightning: https://pay.blink.sv/joen⛏️ On-chain Bitcoin: bc1qu...

In the rapidly evolving landscape of agentic systems, memory management has emerged as a key pillar for building intelligent, context-aware AI Agents. Inspired by the complexity of human memory systems—such as episodic, working, semantic, and procedural memory—this…

In this talk, we examine the state-of-the-art in AI-powered search and retrieval. We detail techniques for enhancing performance beyond base embedding models, including hybrid search, reranking strategies, query decomposition and document enrichment, the…

The talk will have three parts
1.Roadmap debate: RAG vs. finetuning vs. long-context
2.RAG today: benefits, challenges, and current solutions
3.RAG tomorrow: AI models do more work

About Tengyu Ma
Tengyu Ma is the Chief AI Scientist @ MongoDB and an Assistant…

Open weights models and open source inference servers have made massive strides in the year since we last got together at AIE World's Fair.

Where once we had only pirated LLaMA 2 weights and Transformers, we now have an embarrassment of riches. In fact,…

This workshop offers a hands-on introduction to developing Large Language Model (LLM)-powered AI agents using Microsoft’s Azure AI Agent Service. Participants will build a conversational agent capable of analyzing sales data, generating visualizations, and…

As AI agents transition from experimental assistants to critical components of enterprise workflows, reliably evaluating their performance becomes essential. But how do you systematically measure an AI agent’s capabilities, contextual understanding, and accuracy…

GitHub Copilot's agentic capabilities enhance its ability to act as a peer programmer. From the IDE to the repository, Copilot can generate code, run tests, and perform tasks like creating pull requests using Model Context Protocol (MCP). This instructor…