MongoDB at
AI Engineer World’s Fair 2024

In-Booth Sessions

Tuesday, June 25
5 p.m. PST

It’s Not Just Vectors: Augment LLM Capabilities with MongoDB Aggregation Framework (Fabian Valle, Sr. Engineer)

Wednesday, June 26
11 a.m. PST

Unifying Vectors and Metadata: An Introduction to Data Modeling for RAG with MongoDB Atlas Vector Search (Henry Weller, Product Manager)

Speakers: Ben Flast, Director, Product Management at MongoDB
Date: Wednesday, June 26
Time: 11:20 - 11:35 a.m. PST

In this talk, we will explore the cutting-edge techniques for Retrieval Augmented Generation with MongoDB. We will focus on leveraging Vector Search, specifically Atlas Vector Search, over MongoDB data to improve information retrieval and generation processes.

We will show how to build a RAG system using a Parent Child Retrieval Strategy to enable more efficient and accurate retrieval of relevant information. Additionally, we will show how all of this can be done within the MongoDB document model rather than relying on implementing these relationships in the application layer. And finally, we will introduce the concept of Search Nodes which enable you to serve vector search workloads at scale.

This talk is aimed at developers, ML engineers, and data scientists interested in building AI powered experiences with RAG. By the end of the session, attendees will have a solid understanding of how Retrieval Augmented Generation, Vector Search, and MongoDB can be leveraged to build innovative and scalable AI-powered applications.

Speaker: Ben Perlmutter, Sr. Engineer at MongoDB
Date: Wednesday, June 26
Time: 1:30 - 1:50 p.m. PST

It's long been said that "data is the new oil". With the recent rise of generative AI technologies, we have a new event, a more precious digital resource fueling the digital economy: knowledge. Retrieval-augmented generation (RAG) has presented a first generative AI use case for organizations to use their knowledge resources, like documentation, knowledge bases, and code repositories. This talk explores various other ways that organizations can use the knowledge resources they ingest for RAG to fuel growth and productivity. Use cases for knowledge resources covered in this presentation include: traditional natural language processing, fine-tuning models, and creating knowledge APIs for AI agents to consume. Attendees will come away from this talk with actionable guidance on how they can leverage their knowledge resources for maximum efficacy.

Speakers: Prakul Agarwal, Sr. Product Manager at MongoDB(Moderator)
Gabriel Paunescu - naologic.com
Chris Rec - whyhow.ai
Karthik Suresh - haveignition.com
Date: Wednesday, June 26
Time: 3:10 - 3:50 p.m. PST

Join an exciting 30-minute panel discussion featuring founders of 3 cutting-edge Gen AI startups building in the smart ERP, AI-powered Knowledge Graph, and AI product Copilot spaces. This session will be moderated by Prakul Agarwal, Sr Product Manager for AI at MongoDB. We will have 15 minutes towards the end for the audience to ask questions to the panelists. During the discussion, panelists will share insights into the following:

• What problems they’re trying to solve with their current startup.
• How did Gen AI transform the way they are building their company?
• Their preferred AI stack.
• Challenges with taking LLM applications from prototype to production.
• How did MongoDB accelerate their journey?
• What AI features they are currently working on.

Speakers: Henry Weller, Product Manager at MongoDB
Date: Thursday, June 27
Time: 1:30 - 1:50 p.m. PST

In this talk, we'll talk through how developers are getting the most out of Atlas Vector Search through intelligent data modeling of unstructured data. This enables both iterating on your search problem and operating your search system in a way that seamlessly syncs with your original source data. We will also discuss how to consider the capabilities of embedding and chat completion models so that you can effectively ingest data into MongoDB in a way that makes it easily searchable.

Speakers: Apoorva Joshi, Sr. AI Developer Advocate at MongoDB (Moderator)
Vivek Muppalla, Director of Forward Deployed Engineering (Cohere)
Jerry Liu, Co-Founder and CEO (LlamaIndex)
Heejin Jeong, Principal AI Product Manager (Together AI)
Date: Thursday, June 27
Time: 3:10 - 3:50 p.m. PST

This panel will feature a 30-minute discussion between one MongoDB representative and three of our AI partners. We will have 15 minutes towards the end for the audience to ask questions to the panelists. During the discussion, panelists will share insights into the following:

• Origins of the company, identifying the problem space
• What an ideal AI stack looks like today
• Main use cases of their products
• Favorite community projects that use their products
• Challenges with taking LLM applications from prototype to production
• What will the next few years in AI look like?