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Whoever nails real-time voice stands to win the interface layer to AI. Not screens. Not chat bubbles. One of the startups doing great work in this area is Cartesia (disclosure: I'm an indie investor in the company). Their Sonic-3 low latency models are already laughing, emoting, and switching languages live.

dharmesh

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52,097 次观看 • 10 个月前 •via X (Twitter)

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There is a subtle architecture shift happening in voice AI. The voice stack is becoming part of the agent's execution loop. Cartesia is combining the listening and speaking paths around that loop. Sonic-3.6 turns text into speech (90ms latency) and Ink-2 turns speech into text (100ms transcript latency), faster than anything else streaming. now holds the #1 spot for both speaking and listening models. Becasue, voice agents are one of those systems where 100ms in the wrong place is very noticeable. Cartesia is attacking both sides of that loop at once. super interesting work by Karan Goel and team.

There is a subtle architecture shift happening in voice AI. The voice stack is becoming part of the agent's execution loop. Cartesia is combining the listening and speaking paths around that loop. Sonic-3.6 turns text into speech (90ms latency) and Ink-2 turns speech into text (100ms transcript latency), faster than anything else streaming. now holds the #1 spot for both speaking and listening models. Becasue, voice agents are one of those systems where 100ms in the wrong place is very noticeable. Cartesia is attacking both sides of that loop at once. super interesting work by Karan Goel and team.

Rohan Paul

308,266 次观看 • 4 天前

In Signal Dialogues #04, we explore what it takes to build the foundational layer of voice AI from the ground up. Karan Goel, Co-founder and CEO of Cartesia, sits down with Aakrit Vaish to unpack the bet behind one of the most ambitious infrastructure plays in AI. Karan and his co-founders came out of Stanford's AI Lab, where Albert Gu (now Cartesia's Chief Scientist) co-authored Mamba and pioneered State Space Models, the architecture they believe will define the next generation of real-time, interactive AI. Backed by Kleiner Perkins, Index Ventures, Lightspeed and NVIDIA with over $120M raised, Cartesia is building voice models engineered for real-time latency and efficiency at scale. If you're a founder, researcher or builder thinking about voice, infrastructure or the next architectural shift in AI, this one's for you. Timestamps: 00:00 - Introduction 02:46 - What Cartesia Does: Interactive AI Models 03:24 - Founding Story: From Stanford PhDs to Cartesia 04:03 - The Unique Insight: Efficiency and Beyond Transformers 09:07 - Voice Company, Neolab, or Big Lab? 14:57 - State Space Models and Algorithmic Innovation 26:04 - The Four Big Bets in Interactive AI 30:24 - Products, Customers, and Going Full-Stack 41:44 - The BPO Disruption: India's Call Center Future 54:17 - Competition, Moats, and the Long Game Karan Goel Aakrit Vaish Cartesia

In Signal Dialogues #04, we explore what it takes to build the foundational layer of voice AI from the ground up. Karan Goel, Co-founder and CEO of Cartesia, sits down with Aakrit Vaish to unpack the bet behind one of the most ambitious infrastructure plays in AI. Karan and his co-founders came out of Stanford's AI Lab, where Albert Gu (now Cartesia's Chief Scientist) co-authored Mamba and pioneered State Space Models, the architecture they believe will define the next generation of real-time, interactive AI. Backed by Kleiner Perkins, Index Ventures, Lightspeed and NVIDIA with over $120M raised, Cartesia is building voice models engineered for real-time latency and efficiency at scale. If you're a founder, researcher or builder thinking about voice, infrastructure or the next architectural shift in AI, this one's for you. Timestamps: 00:00 - Introduction 02:46 - What Cartesia Does: Interactive AI Models 03:24 - Founding Story: From Stanford PhDs to Cartesia 04:03 - The Unique Insight: Efficiency and Beyond Transformers 09:07 - Voice Company, Neolab, or Big Lab? 14:57 - State Space Models and Algorithmic Innovation 26:04 - The Four Big Bets in Interactive AI 30:24 - Products, Customers, and Going Full-Stack 41:44 - The BPO Disruption: India's Call Center Future 54:17 - Competition, Moats, and the Long Game Karan Goel Aakrit Vaish Cartesia

Activate

12,489 次观看 • 3 个月前

From IIT Delhi to Stanford PhD to raising $27M before having a product. That's Karan Goel story. No revenue. No product. Just strong research, strong demos, and strong conviction. What does Cartesia do? In simple language: It helps businesses automate conversations. If you’re a small business owner and miss a customer’s call, you may lose revenue. Cartesia makes it possible for AI to answer that call, qualify the lead, and respond naturally — in real time, and in local languages. A few things that stood out to me from my conversation with Karan: → Cartesia is building some of the fastest voice AI models in the world → They’re obsessed with latency because even small delays break conversations → They’re betting big on India as a voice-first market → Karan believes India should aim to export AI to the world, not just consume it Karan Goel Cartesia 🎧 Link in comments.

From IIT Delhi to Stanford PhD to raising $27M before having a product. That's Karan Goel story. No revenue. No product. Just strong research, strong demos, and strong conviction. What does Cartesia do? In simple language: It helps businesses automate conversations. If you’re a small business owner and miss a customer’s call, you may lose revenue. Cartesia makes it possible for AI to answer that call, qualify the lead, and respond naturally — in real time, and in local languages. A few things that stood out to me from my conversation with Karan: → Cartesia is building some of the fastest voice AI models in the world → They’re obsessed with latency because even small delays break conversations → They’re betting big on India as a voice-first market → Karan believes India should aim to export AI to the world, not just consume it Karan Goel Cartesia 🎧 Link in comments.

Shiva Singh Sangwan

23,831 次观看 • 5 个月前

This is the DeepSeek moment for Voice AI. Chatterbox Turbo is an MIT-licensed voice model that beats ElevenLabs Turbo & Cartesia Sonic 3! - <150ms time-to-first-sound - Voice cloning from just 5-second audio - Paralinguistic tags for real human expression 100% open-source.

This is the DeepSeek moment for Voice AI. Chatterbox Turbo is an MIT-licensed voice model that beats ElevenLabs Turbo & Cartesia Sonic 3! - <150ms time-to-first-sound - Voice cloning from just 5-second audio - Paralinguistic tags for real human expression 100% open-source.

Akshay 🚀

468,852 次观看 • 8 个月前

Did Google just mass-murdered every voice AI startup irrelevant? Google just shipped Gemini 3.1 Flash Live. Real-time voice AND vision. Sub-second latency. 90+ languages. And the one thing no voice AI has cracked until now: it filters background noise in real-world environments. Not demo environments. Real ones. Traffic outside. TV left on. Drill running next door. That's the wall every voice AI startup has been quietly hitting for three years. The demos worked. The deployments didn't. Because the real world is loud and messy and the models couldn't tell your voice from the noise around it. Google just called that problem solved. And it's not sitting in a research paper. It's already running in production apps. Stitch is using it to let designers talk to their canvas in real-time. Ato is using it to give elderly people a companion who actually listens. Wit's End built an RPG game master with it that delivers theatrical dialogue indistinguishable from a human voice actor. Three live products. Three different industries. All shipping now. Every voice AI startup just woke up to a new baseline. The question isn't whether to build with this. The question is how fast.

Did Google just mass-murdered every voice AI startup irrelevant? Google just shipped Gemini 3.1 Flash Live. Real-time voice AND vision. Sub-second latency. 90+ languages. And the one thing no voice AI has cracked until now: it filters background noise in real-world environments. Not demo environments. Real ones. Traffic outside. TV left on. Drill running next door. That's the wall every voice AI startup has been quietly hitting for three years. The demos worked. The deployments didn't. Because the real world is loud and messy and the models couldn't tell your voice from the noise around it. Google just called that problem solved. And it's not sitting in a research paper. It's already running in production apps. Stitch is using it to let designers talk to their canvas in real-time. Ato is using it to give elderly people a companion who actually listens. Wit's End built an RPG game master with it that delivers theatrical dialogue indistinguishable from a human voice actor. Three live products. Three different industries. All shipping now. Every voice AI startup just woke up to a new baseline. The question isn't whether to build with this. The question is how fast.

Vaibhav Sisinty

59,350 次观看 • 5 个月前

We've raised a $64M Series A led by Kleiner Perkins to build the platform for real-time voice AI. We'll use this funding to expand our team, and to build the next generation of models, infrastructure, and products for voice, starting with Sonic 2.0, available today. Link below to try it free 👇

We've raised a $64M Series A led by Kleiner Perkins to build the platform for real-time voice AI. We'll use this funding to expand our team, and to build the next generation of models, infrastructure, and products for voice, starting with Sonic 2.0, available today. Link below to try it free 👇

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At RAISE Summit in Paris, one theme stood out: every layer of the AI stack is up for grabs. Startups are challenging incumbents in chips, cloud infrastructure, data centers, and foundation models alike.

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TIME

7,735,854 次观看 • 2 个月前

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Daniel

151,698 次观看 • 9 个月前

This is the DeepSeek moment for Voice AI. Today we’re releasing Chatterbox Turbo — our state-of-the-art MIT licensed voice model that beats ElevenLabs Turbo and Cartesia Sonic 3! We’re finally removing the trade-offs that have held voice AI back. Fast models sound robotic. Great models are slow. And none are built for trust. We fixed all three. Chatterbox Turbo is transparent, auditable, and built for a world that needs proof.

This is the DeepSeek moment for Voice AI. Today we’re releasing Chatterbox Turbo — our state-of-the-art MIT licensed voice model that beats ElevenLabs Turbo and Cartesia Sonic 3! We’re finally removing the trade-offs that have held voice AI back. Fast models sound robotic. Great models are slow. And none are built for trust. We fixed all three. Chatterbox Turbo is transparent, auditable, and built for a world that needs proof.

Dev Shah

469,897 次观看 • 9 个月前

A very happy 80th Independence Day to India, from team Cartesia! 🇮🇳 Coming closer to home with Sonic 3.6, we're making every one of India's languages more natural, expressive, and accurate: - Hindi that flows the way you speak it - Hinglish that switches without missing a beat - Naturalness gains across all 9 existing Indic languages - Plus two new languages: Urdu and Odia Every voice in this video generated by Sonic.

A very happy 80th Independence Day to India, from team Cartesia! 🇮🇳 Coming closer to home with Sonic 3.6, we're making every one of India's languages more natural, expressive, and accurate: - Hindi that flows the way you speak it - Hinglish that switches without missing a beat - Naturalness gains across all 9 existing Indic languages - Plus two new languages: Urdu and Odia Every voice in this video generated by Sonic.

Cartesia

110,964 次观看 • 28 天前

Introducing Lightning V3 - it beats every model we tested against. ElevenLabs, Cartesia, OpenAI. Lightning sets a new SOTA with V3 in conversational text-to-speech. → Highest MOS score for conversational TTS at 3.9 → ~76% win rate vs gpt-4o-mini-tts on naturalness → 15 languages with mid-sentence code-switching → Built from scratch for voice agents, not read-aloud Every TTS model sounds clean in a demo. You type a sentence and you get beautiful audio. Voice agents don't work that way. They stream. They're generating audio in real-time chunks with half the context missing. That's where everything breaks. A great reading voice and a great conversational voice are fundamentally different things. A conversational voice has to sound like it's thinking - with the pauses, the rhythm shifts, the reactions. It has to handle the way real people actually talk, including switching languages mid-sentence. That's what V3 does. V3.1 also ships voice cloning. 5 to 15 seconds of audio, no fine-tuning, production-grade clone across 15 languages. Blog link in the comments.

Introducing Lightning V3 - it beats every model we tested against. ElevenLabs, Cartesia, OpenAI. Lightning sets a new SOTA with V3 in conversational text-to-speech. → Highest MOS score for conversational TTS at 3.9 → ~76% win rate vs gpt-4o-mini-tts on naturalness → 15 languages with mid-sentence code-switching → Built from scratch for voice agents, not read-aloud Every TTS model sounds clean in a demo. You type a sentence and you get beautiful audio. Voice agents don't work that way. They stream. They're generating audio in real-time chunks with half the context missing. That's where everything breaks. A great reading voice and a great conversational voice are fundamentally different things. A conversational voice has to sound like it's thinking - with the pauses, the rhythm shifts, the reactions. It has to handle the way real people actually talk, including switching languages mid-sentence. That's what V3 does. V3.1 also ships voice cloning. 5 to 15 seconds of audio, no fine-tuning, production-grade clone across 15 languages. Blog link in the comments.

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71,298 次观看 • 5 个月前

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29,048,294 次观看 • 3 个月前

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Klaas

21,569 次观看 • 1 年前

🚨 BREAKING: Big day for voice AI. Cartesia just dropped Sonic 3.5 and Sarvam announced their $300M Series B - so I decided to put both to the test myself. Same scripts, side by side. The results are kind of insane. Sonic came out a leap ahead on emotion, alphanumerics, and switching across Indian languages mid-sentence. Karan Goel grew up in Delhi, went to IIT Delhi, and constantly talks about how much he cares about building for India. Hard to argue he doesn't mean it 👇

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707,593 次观看 • 2 个月前

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Andrew Ng

87,810 次观看 • 1 年前

One of my top priorities as Chairman is to restore the U.S. Securities and Exchange Commission’s public company disclosure regime to one rooted in materiality. As a disclosure agency and not a merit regulator, the SEC should not use its rules to indirectly regulate matters that should be left to the States.

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Paul Atkins

44,472 次观看 • 1 个月前