Fireworks Founder Lin Qiao on the Power of Small Models to Democratize AI Use Cases
In the first wave of the generative AI revolution, startups and enterprises built on top of the best closed-source models available, mostly from OpenAI. The AI customer journey moves from training to inference, and as these first products find PMF, many are hitting a wall on latency and cost.
Fireworks Founder and CEO Lin Qiao led the PyTorch team at Meta that rebuilt the whole stack to meet the complex needs of the world’s largest B2C company. Meta moved PyTorch to its own non-profit foundation in 2022 and Lin started Fireworks with the mission to compress the timeframe of training and inference and democratize access to GenAI beyond the hyperscalers to let “thousands of flowers to blossom.”
Lin predicts when open and closed source models will converge and reveals her goal to build simple api access to the totality of knowledge.
Hosted by: Sonya Huang and Pat Grady, Sequoia Capital
00:00 - Introduction
02:01 - What is Fireworks?
02:48 - Leading Pytorch
05:01 - What do researchers like about PyTorch?
07:50 - How Fireworks compares to open source
10:38 - Simplicity scales
12:51 - From training to inference
17:46 - Will open and closed source converge?
22:18 - Can you match OpenAI on the Fireworks stack?
26:53 - What is your vision for the Fireworks platform?
31:17 - Competition for Nvidia?
32:47 - Are returns to scale starting to slow down?
34:28 - Competition
36:32 - Lightning round
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