What if AI could talk back instantly—and naturally?In this episode, Karan Goel, Co-founder & CEO of Cartesia, joins Barr Yaron to unpack the future of voice AI, state space models (SSMs), and why audio is the next frontier in AI.
Karan shares the founding story behind Cartesia, explains how alternate architectures like Mamba enable ultra-efficient, low-latency inference, and walks through how his team is building the fastest text-to-speech model in the world—while obsessing over every millisecond.
Whether you’re into model architectures, AI infrastructure, or the future of voice interfaces, this episode delivers technical depth, startup lessons, and a roadmap for what’s coming next.This episode is broken down into the following chapters:
00:00 – Intro
01:06 – Karan’s journey from CMU PhD to startup founder
03:56 – Why Cartesia is built around state space models
06:49 – What makes SSMs different from transformers
09:14 – Why compression matters for long-running AI systems
11:13 – What data types SSMs are best (and worst) for
13:39 – Scaling SSMs: What’s possible and what’s missing
15:31 – Hardware, GPUs & why SSMs work well on existing infra
18:46 – Landing on audio: Cartesia’s first core modality
22:38 – Navigating the model vs. market debate in AI startups
26:36 – How Cartesia built Sonic, their ultra-low latency TTS model
28:17 – Why latency is the #1 challenge in voice AI
30:46 – Tricks vs. model-first thinking: Baking it into the model
34:01 – How Cartesia balances fast execution with deep research
36:26 – Building with part-time academic co-founders
38:13 – Yes, every employee gets a personal Yoshi
40:02 – Where voice AI is being adopted first (telephony + beyond)
42:24 – Multilingual modeling & the long tail of language
45:02 – Voice as a new computing interface
46:26 – Why voice notes are the future (and Barr’s hot take)
49:56 – How Cartesia evaluates its models
52:44 – How Karan has grown as a founder and leader
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