🎥 Once a month, we'll meet, socialize, and hear speakers present topics on unstructured data and generative AI. This event was sponsored by Zilliz and GetYourGuide.
Timeline:
00:20 - An intro from GetYourGuide
03:30 - Speaker Morena Bastiaansen, Fact vs. Fiction: Autodetecting Hallucinations in LLMs
34:55 - Speaker Stephen Batifol, Vector Databases 101 - An introduction to the world of Vector Databases
59:05 - Speaker Bo Wang, Training state-of-the-art general text embedding
~~~~~~~~~~~~~~~ CONNECT ~~~~~~~~~~~~~~~
🎥 Playlist • Unstructured Data Meetup
🖥️ Website: www.meetup.com...
X Twitter - / milvusio
🔗 Linkedin: / zilliz
😺 GitHub: github.com/mil...
🦾 Invitation to join discord: / discord
~~~~~~~~~~~~~~ MEETUP VIDEO CONTENTS ~~~~~~~~~~~~~~
1. Host: Stephen Batifol
LinkedIn: / stephen-batifol
2. Speaker: Morena Bastiaansen, Data Scientist at GetYourGuide
Title: Fact vs. Fiction: Autodetecting Hallucinations in LLMs
Abstract: The rise of Large Language Models has revolutionized the landscape of AI, unlocking huge potential across society. However, it has also introduced the challenge of hallucinations - instances where the model generates rather trippy content in a scarily convincing way. Rest assured, Morena will guide you through an exploration of how we can automatically detect these instances of hallucination to fully unleash the potential of LLMs.
3. Speaker: Stephen Batifol, DevRel at Zilliz
Title: Vector Databases 101 - An introduction to the world of Vector Databases
Abstract: An introduction to Unstructured Data and the world of Vector Databases, we will see how they different from traditional databases. In which cases you need one and in which you probably don’t. I will also go over Similarity Search, where do you get vectors from and an example of a Vector Database Architecture.
4. Speaker: Bo Wang, Jina AI
Title: Training state-of-the-art general text embedding
Abstract: Embeddings have become a crucial component in contemporary vector search and Retrieval Augmented Generation (RAG) systems. In this talk, I aim to provide a comprehensive overview of training a versatile embedding model, strategies for encoding longer information within such models, along their benefits and limitations. Additionally, I'll delve into various forms of deep learning-powered retrievers.
3 окт 2024
