Data is Everything: Finding needles in multimodal haystacks

Lightning Lessons

Practical skills & tools to accelerate your career

Data is Everything: Finding needles in multimodal haystacks

Hosted by Jason Liu, Rajan Agarwal, and Luke Igel

193 students

What you'll learn

Vector Embedding Strategies

Master techniques to encode multimodal data for efficient search and retrieval.

Chunking & Indexing Methodologies

Master approaches to segment and organize large datasets to enable precise searching across diverse data types.

Multimodal Query Optimization

Develop skills to formulate and process complex queries that span multiple data modalities for comprehensive results.

Why this topic matters

Understanding multimodal data search unlocks vast information potential that would otherwise remain hidden. As data volumes explode across formats, professionals who master these search techniques gain a competitive edge, enabling them to extract valuable insights faster than competitors and build more responsive, intelligent systems that delight users.

You'll learn from

Jason Liu

Consultant at the intersection of Information Retrieval and AI

Jason has built search and recommendation systems for the past 6 years. He has consulted and advised a dozens startups in the last year to improve their RAG systems. He is the creator of the Instructor Python library.

Rajan Agarwal

Research Engineering Intern @ Kino AI

Rajan Agarwal is a Machine Learning researcher studying at the University of Waterloo, specializing in multimodal models, self-driving software and multi-agent orchestration.

Luke Igel

CEO, Co-founder at Kino AI

Luke Igel is the co-founder and CEO of Kino. Previously he worked on autonomous systems at NASA and satellite planning software at SpaceX. He recently graduated from MIT, where he co-created an archival footage documentary on the history of America, inspiring the founding of Kino.

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