ÜBER DIESE EPISODE
In this episode, Chang She, CEO and Co-founder of LanceDB, discusses the challenges of handling multimodal data and how LanceDB provides a cutting-edge solution. He shares his journey from contributing to Pandas to building a database optimized for images, video, vectors, and subtitles.
Highlights include:
- The limitations of traditional storage systems like Parquet for multimodal AI.
- How LanceDB enables efficient querying and processing of diverse data types.
- The growing importance of multimodal AI in enterprise applications.
- Future trends in AI, including a shift from single models to holistic AI systems.
- Predictions and "spicy takes" on AI advancements in 2025.
Englisch
Vereinigte Staaten
TRANSKRIPT 🔗
Are you the producer of this podcast?
Add a podcast transcript
Need Audio-to-Text?
Transcribe with Listen411 in Just 60 Seconds
VERGANGENE FOLGEN SUCHEN
Vorhandene Folgen von Data Brew by Databricks durchsuchen.
WEITERE EPISODEN IN DIESEM PODCAST
In this episode, Yev Meyer, Chief Scientist at Gretel AI, explores how synthetic data transforms AI and ML by improving data access, quality, privacy, and model training.Highlights include:- Leveraging synthetic data to overcome AI data limitations.- Enhancing model training while mitigating ethica…
In this episode, Julia Neagu, CEO & co-founder of Quotient AI, explores the challenges of deploying Generative AI and LLMs, focusing on model evaluation, human-in-the-loop systems, and iterative development.Highlights include:- Merging reinforcement learning and unsupervised learning for real-t…
In this episode, Jure Leskovec, Co-founder of Kumo AI and Professor of Computer Science at Stanford University, discusses Relational Deep Learning (RDL) and its role in automating feature engineering. Highlights include:- How RDL enhances predictive modeling.- Applications in fraud detection and re…
In this episode, Sharon Zhou, Co-Founder and CEO of Lamini AI, shares her expertise in the world of AI, focusing on fine-tuning models for improved performance and reliability.Highlights include:- The integration of determinism and probabilism for handling unstructured data and user queries effecti…
In this episode, Shashank Rajput, Research Scientist at Mosaic and Databricks, explores innovative approaches in large language models (LLMs), with a focus on Retrieval Augmented Generation (RAG) and its impact on improving efficiency and reducing operational costs.Highlights include:- How RAG enha…
Rechtliche Hinweise: Der auf dieser Seite eingebettete Podcast und das Bildmaterial stammen von Databricks, das Eigentum seines Eigentümers ist und nicht mit Listen Notes, Inc. verbunden ist oder von diesen unterstützt wird.
BEARBEITEN
Vielen Dank, dass Sie uns helfen, die Podcast-Datenbank auf dem neuesten Stand zu halten.