Inference is Turing Post’s way of asking the big questions about AI — and refusing easy answers. Each episode starts with a simple prompt: “When will we…?” – and follows it wherever it leads.
Host Ksenia Se sits down with the people shaping the future firsthand: researchers, founders, engineers, and entrepreneurs. The conversations are candid, sharp, and sometimes surprising – less about polished visions, more about the real work happening behind the scenes.
It’s called Inference for a reason: opinions are great, but we want to connect the dots – between research breakthroughs, business moves, technical hurdles, and shifting ambitions.
If you’re tired of vague futurism and ready for real conversations about what’s coming (and what’s not), this is your feed. Join us – and draw your own inference.
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Inference is Turing Post’s way of asking the big questions about AI — and refusing easy answers. Each episode starts with a simple prompt: “When will we…?” – and follows it wherever it leads.
Host Ksenia Se sits down with the people shaping the future firsthand: researchers, founders, engineers, and entrepreneurs. The conversations are candid, sharp, and sometimes surprising – less about polished visions, more about the real work happening behind the scenes.
It’s called Inference for a reason: opinions are great, but we want to connect the dots – between research breakthroughs, business moves, technical hurdles, and shifting ambitions.
If you’re tired of vague futurism and ready for real conversations about what’s coming (and what’s not), this is your feed. Join us – and draw your own inference.
When Will We Speak Without Language Barrier? A conversation with Mati Staniszewski, CEO @ ElevenLabs
Inference by Turing Post
22 minutes
8 months ago
When Will We Speak Without Language Barrier? A conversation with Mati Staniszewski, CEO @ ElevenLabs
In this episode of Inference, I sit down with Mati Staniszewski, co-founder and CEO of ElevenLabs, to explore the future of AI voice, real-time multilingual translation, and emotionally rich speech synthesis. We dive into what still makes dubbing hard, how Lex Fridman's podcast was localized, and what it takes to preserve tone, timing, and emotion across languages. Mati shares why speaker detection in noisy rooms is tricky, how fast their models really are (70ms TTS!), and the deeper strategy behind partnering with creators and enterprises to show – not just tell – what the tech can do.
What needs to happen for natural, free-flowing multilingual conversations to become reality? Mati says: give it two or three years. Watch to learn more!
Guest:
Mati Staniszewski, co-founder and CEO at ElevenLabs
Website: https://elevenlabs.io/
Additional Reading:
https://www.turingpost.com/p/mati
Chapters
0:00 Real-time voice translation
0:11 Language barriers and AI
0:29 Why ElevenLabs started
0:36 Dubbing in Poland
0:45 Preserving emotion in translation
1:06 Tech challenges in real-time translation
1:17 Ideal device setup
2:32 Speaker diarization and emotional nuance
3:04 Speech-to-text to LLM to TTS pipeline
5:51 Concrete examples: healthcare & customer support
7:05 Real-time AI dubbing use cases
8:02 Lex Fridman podcast dubbing challenge
13:01 Audio model performance & latency
14:44 Conversational AI & multimodal future
16:57 Product vs research focus at ElevenLabs
20:42 Why ElevenLabs didn't open source (yet)
21:28 Strategy: creators, enterprises & brand building
Turing Post is a newsletter about AI's past, present, and future. Publisher Ksenia Semenova explores how intelligent systems are built—and how they’re changing how we think, work, and live.
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Inference by Turing Post
Inference is Turing Post’s way of asking the big questions about AI — and refusing easy answers. Each episode starts with a simple prompt: “When will we…?” – and follows it wherever it leads.
Host Ksenia Se sits down with the people shaping the future firsthand: researchers, founders, engineers, and entrepreneurs. The conversations are candid, sharp, and sometimes surprising – less about polished visions, more about the real work happening behind the scenes.
It’s called Inference for a reason: opinions are great, but we want to connect the dots – between research breakthroughs, business moves, technical hurdles, and shifting ambitions.
If you’re tired of vague futurism and ready for real conversations about what’s coming (and what’s not), this is your feed. Join us – and draw your own inference.
