[In-person] Vector DB & LLM Hackathon

Join us on Saturday, June 17 in Berlin for an all-day Vector DB & LLM Hackathon with the MLOps.community and Weaviate using a large corpus of community Slack and Videos! We'll also be hosting a welcome BBQ on Friday, June 16th.

You can register for both events here (spots will not be held for those who only register through meetup.com)

💪 Collaborate with and learn from other like-minded MLOps practitioners in AI, ML, and Data Science industries.

💻 Get access to tools and credits from Weaviate to build end-to-end solutions.

👨🏻‍💻 Get support in-person from Weaviate engineers – who will help you go from 0 to 100 in no time.

💰 Chance to win cash prizes!

📣 Selected teams will be invited to share their solutions at an upcoming Berlin MLOps Community meetup

🦾 Intro:
Vector embeddings generated by LLMs – like those provided by OpenAI, Cohere, Hugging Face, and Google PaLM, or those you may fine-tune yourself – opened up a world of possibilities in how we understand and query our data.

Combine this with Weaviate – an AI-native vector database – and you have a recipe for running LLMs at a scale of millions or even billion data objects.

🦾 The Challenge(s):
Now the question (and the challenge) is:

“What can you build with a dataset + LLM + vector database in a day?”

Option 1 – MLOps community Slack search
MLOps.community is a 17K+ member community, primarily online in a thriving slack channel and through virtual and in-person events. There is a lot of tribal knowledge in the community where experts answer questions from other MLOps practitioners in Slack and via in-person meetups and online videos. We want you to build an LLM-powered application (Web/Mobile/Slack) to answer MLOps and other ML/DS/AI questions that community members may have using the historical knowledge in Slack, videos, etc. For example - you may implement the solution as a chatbot that uses embeddings and a vector datastore to generate the answers.

Option 2 – bring your own use case
Bring in your own data and a use case – that you were itching to build but never had the time for.
We will help you generate vector embeddings***** and show you how to query your data******. Then you will be able to focus on building the rest of the app to impress us all.
****** if you already have vector embeddings for your data ready, that is cool too – we will show you how to load your data with your embeddings.* ******warning: you may be surprised how little code it takes to do it all.

🔨 What you’ll be building:
We’d love to see your creativity in designing your LLM Stack and showcase how useful your app can be to help MLOps practitioners learn from the experience of others. We encourage participants to discover, experiment, and build high-impact solutions using the dataset during this hackathon, and improve their skills to build powerful LLM Stacks! That being said, here are a few dimensions you could consider when creating your LLM

Stack solution:

• Correctness of the answers (and explainability/citations)
• LLM chains
• Data pipelines
• User Interfaces
• System Design tradeoffs
• Security
• Bonus points for transparently sharing your solution so that the community can learn (e.g. OSS, documentation, etc.)
• etc.

💽 The Data:

• Slack data from public MLOps Community channels
• Transcripts of videos from MLOps.community Youtube page
• Other data from the communities’ past events, blogs, etc. (make sure you share the sources used)
• Starter Kit

🗺️ Location:

• 42 Berlin (exact location will be shared with participants on sign-up)

💫 Why we’re having this hackathon: As part of enhancing our community, we are looking to provide the opportunity to our members and other participants to learn to improve their knowledge on building LLM-powered solutions to a common problem of knowledge discovery by designing and building an app that uses LLMs to answer community member questions, just like the human experts.

Here’s everything you need to know to get started:
👷 You can work individually or in groups of up to 4 people
🔨 You can use any Open Source tools to build your solutions and your code need not be open-source.
💽 The data provided for the purposes of this hackathon is under the CC-BY-NC 4.0 license, intended for non-commercial use only.
📅 Projects should be started at the event kick-off to maintain fairness across projects
🔢 Credits: To be announced.
💸 Cash prizes: To be announced.
💫 Looking for creative solutions in the LLM App Stack (UI, System Design, Microservices) that solve real-world problems using emergent LLM technologies.