Unsupervised Learning

Ep 32: CEO and Founder of Pinecone Edo Liberty on Pioneering Vector Databases, Barriers to Productionalizing Models and Why What’s Happening with GPUs is Not Sustainable

Apr 16, 2024

CEO and Founder of Pinecone, Edo Liberty, discusses the evolving landscape of vector databases, challenges in building them, painful serverless model launch, common Pinecone use cases, and targeting areas for AI startups. Exploring image/video applications, myth-busting about Pinecone, and surprises in building the platform.

01:01:12

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Episode guests

Edo Liberty

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Episode notes

Podcast summary created with Snipd AI

Quick takeaways

Vector databases like Pinecone are essential for AI applications like semantic search and recommendation systems, despite market education challenges.

The transition to serverless models for Pinecone resulted in significant cost reductions, highlighting the need for efficient pricing strategies.

The AI industry is moving towards hardware changes away from GPUs, with a focus on improving data pipeline management and governance for models.

Deep dives

Vector Database Evolution and Importance in AI Apps

Vector databases like Pinecone play a crucial role in the AI landscape, underutilized for various use cases such as semantic search, candidate generation, and recommendation systems. The speaker highlighted the challenges in educating the market about the significance of vector databases, despite their adoption by major tech companies like Google and Amazon.

Introduction

2min

The Transition and Scalability Challenge

5min

Diverse Applications and Efficiency of Pinecone for Vector Workloads

18min

Efficient Scaling in Model Development

7min

Navigating Early Days and Transitioning to Serverless Model

20min

Pivotal Database Rewrite in Rust

2min

Advancing AI Beyond Pinecone

8min

Pinecone has raised over $130 million and was most recently valued at $750 million. On this week’s Unsupervised Learning, we sat down with CEO and Founder of Pinecone, Edo Liberty. Pinecone is arguably one of the most important elements in today's modern datastack. Edo shared with us the most common use cases of Pinecone, the evolving landscape of vector databases, challenges in building vector databases, the "painful" launch of serverless model, and what people get wrong the most about Pinecone.

(0:00) intro

(0:33) what was it like when ChatGBT came out?

(6:29) Edo’s favorite applications built on Pinecone

(10:34) will we see more image and video applications in 2024?

(14:58) best ways to deal with hallucinations

(18:12) the evolving landscape of vector databases

(20:27) if Edo had to build a product, what would his stack look like?

(31:45) helping clients versus letting them figure things out

(36:38) moving to a serverless model

(40:33) what areas of AI should new startups target?

(45:18) Amazon SageMaker

(50:38) over-hyped/under-hyped

(51:30) biggest surprises while building Pinecone

(56:13) Jacob and Pat debrief

With your co-hosts:

@jacobeffron

- Partner at Redpoint, Former PM Flatiron Health

@patrickachase

- Partner at Redpoint, Former ML Engineer LinkedIn

@ericabrescia

- Former COO Github, Founder Bitnami (acq’d by VMWare)

@jordan_segall

- Partner at Redpoint

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Unsupervised Learning

Ep 32: CEO and Founder of Pinecone Edo Liberty on Pioneering Vector Databases, Barriers to Productionalizing Models and Why What’s Happening with GPUs is Not Sustainable

Episode guests

Podcast summary created with Snipd AI

Quick takeaways

Deep dives

Vector Database Evolution and Importance in AI Apps

Scalability Challenges and Transition to Serverless Solutions

Future of AI Infrastructure

Applications Lead Future Innovation

Agent Reliability and Potential Challenges

Remember Everything You Learn from Podcasts