Wednesday
Room 6 - Level 5
10:20 - 11:20
(UTC±00)
Talk (60 min)
What comes after ChatGPT? Vector Databases - the Simple and powerful future of ML?
What comes after ChatGPT? Vector database projects like Weaviate, Pinecone, and Chroma recently got millions of dollars of funding for their projects. But what are vector databases? And why will they be so important in the future?
Let us see how Vector Databases can help you define and run your machine learning business use cases. We will explore some real-world use cases and try to understand the potential of vectors and vector databases. A brief hands-on demonstration just using open source will give you an idea, of how to use the new generation of databases in praxis.
We will also cover how vector databases can work together with chatGPT and helps you to overcome some limitations of chatGPT.
Erik Bamberg
Erik is a Java and machine learning Enthusiast - Java -Coach, -Expert, -Consultant and Software Architect - who loves to talk about elegant software solutions and the achievement from the 8-bit area to today.
He spends his energy, enthusiasm and research time in machine learning and vector databases.
Formerly a Open Source Contributor & Community Lead for the Deep Java Learning ML Framework (Amazon AWS), he is on a mission to transform machine learning from the research labs into real-world applications.
As a musician and Indy Film Maker, he always sees elegant software solutions with the eye of an artist and knows about creativity and art and the importance of these skills as a software engineer.