絞り込み結果
23 件並び順
34:30ENNetic's Agents Answer the Phone When the Heat Breaksホスト Sarah Guo, Elad GilFounder Melisa Tokmak tells Elad Gil how a two-year-old platform became the AI operations layer for HVAC, roofing, pet care, and other essential services.
1:23:53ENCreators Cheer Filler-Word Removal and Boo Generative Videoホスト Nathan LabenzDescript CEO Laura Burkhauser maps the same customers' three-speed reaction to AI: deterministic buttons they love, an agentic co-editor they want but scold, and generative video they actively hate.
1:37:50ENGranola Added More Customers Than Almost Anyone by Being Surprisingly Unambitiousホスト Nathan LabenzCo-founder Sam Stephenson tells Nathan Labenz how a calm notes app for frazzled meeting days, one Slack-sharing loop, and a refusal to promise the burning-fire work built a $1.5 billion company.
41:38ENElevenLabs Hit $300 Million ARR by Building Voice Before Anyone Believed It Was the Interfaceホスト Sarah Guo, Elad GilIn Poland, watching a foreign film is a special kind of pain: one narrator, every character, a flat delivery from start to finish.
44:47ENThe Last Mile Is Where Contact-Center AI Gets RealCresta CEO Ping Wu and Sequoia's Doug Leone on why 17 to 20 million agents, legacy systems, and last-mile integration will decide who wins customer experience.
59:38ENElevenLabs Was Supposed to Be RoadkillCo-founder Mati Staniszewski on dirty audio data, prosumer virality, and why voice should become the default interface for technology.
38:43ENTwo in Five Doctors Want Out. An On-Call Cardiologist Built the Note That Lets Them Stayホスト Sarah Guo, Elad GilAbridge CEO Shiv Rao on treating the doctor-patient conversation as healthcare's source of truth, and why the company ran straight at the hardest health systems.
1:05:11ENThe Fake Five-Second Hold: Voice AI Is Already Negotiating With Truckersホスト Nathan Labenza16z partners Olivia Moore and Anish Acharya walk Nathan Labenz through what is working in voice AI — call centers, coaches, companions — and what still is not.
30:09ENBilt Saved 65 Support Seats. Decagon's Founder Says Most Agent Ideas Still Won't Sellホスト Sarah Guo, Elad GilJesse Zhang on why customer support is the golden agent use case, why instruction following beats o1-style reasoning, and the two filters that kill most agent startups.
56:10ENDeepL Beat Google at Translation by Refusing to Be a General Modelホスト Jacob EffronOnly 18 percent of the world speaks English—and a Cologne startup turned that fact into a $2 billion language-AI company.
32:07ENA 10-Person Team, One Click, and Two Years of Fake DeadlinesNotebookLM’s product and design leads explain how a source-grounded research tool became a viral two-host podcast generator—and what they refuse to add next.
34:09ENFive Independent Teams Found the Same 10-to-1 Mix That Beats Transformersホスト Sarah Guo, Elad GilThe authors of S4 and Mamba argue that mostly state-space layers plus a dash of attention is the architecture that actually works—and they are shipping it first as real-time speech.
1:45:11ENAI already beats doctors at empathy. Catastrophe is still not the defaultホスト Nathan LabenzNathan Labenz tells Sarah Hastings Woodhouse why he is an adoption accelerationist and a hyperscaling pauser, and lists eight reasons he will not join the hardcore doomers.
1:22:43ENFive billion minutes of calls: why Dialpad trained its own business LLMホスト Nathan LabenzDan O’Connell on real-time speech, verticalizing the stack, and why he and Nathan Labenz disagree about when AI employees show up.
1:17:20ENHume wants well-being in the objective function, measured 53 emotions at a timeホスト Nathan LabenzAlan Cowen tells Nathan Labenz how Hume AI reads face, voice, and language, sells custom models at $1.66 an hour, and wants long-horizon well-being to override every other AI goal.
1:20:55ENA Custom Voice Used to Cost $10,000. Ten Minutes of Audio Now Clones It.ホスト Nathan LabenzPlay.ht CEO Mahmoud Felfel tells Nathan Labenz how text-to-speech jumped from robotic cloud APIs to director-level voice generation — and why the company is racing to put brakes on abuse.
1:28:46ENThe Speech Company That Gets Paid to Label Its Own Training Dataゲスト Dan Kokotov · ホスト Lex FridmanRev VP of engineering Dan Kokotov tells Lex Fridman why a $1.25-a-minute human transcript, a 14% machine word-error rate, and a two-sided freelancer market are the same flywheel.
1:45:58ENNine of ten colleagues said far-field speech was impossibleゲスト Rohit Prasad · ホスト Lex FridmanRohit Prasad, Amazon’s vice president and head scientist for Alexa, talks with Lex Fridman about conversational AI, the Alexa Prize, trust, and why a 20-minute chat is still years away.
1:09:31ENThe Staircase to an AI Tutor: Connor Wick on Speak, Moats, and Voice-First Learningホスト Jacob EffronHow Speak's CEO is building a fluency product one model-capability step at a time, from specialized speech models to evals, pricing, and the future of education.
1:09:00ENThe Meeting Is the Moat: Fireflies.ai’s Path to 16 Million Usersホスト Jacob EffronKrish Ramani explains how Fireflies.ai turned AI note-taking into a meeting chief of staff, why he avoids fine-tuning, and how a startup competes with Microsoft, Zoom, and Google.
45:46ENGiving AI a Nervous System: Voice, Touch, and the Post-Keyboard Interfaceホスト Jacob EffronLiveKit's Russ explains how voice AI, multimodal chat, cloud browsers, and on-device models are reshaping how humans work with machines.
51:45ENCameras Optional: HeyGen's Joshua Xu on Avatars, Orchestration and Building Ahead of the Modelsホスト Jacob EffronHeyGen co-founder and CEO Joshua Xu explains how AI avatars are replacing the camera for business video, and how the company handles quality, trust and safety, and capital.
1:04:27ENPeter Deng on Why AI Pricing, Evals and Voice Are Still Misunderstoodホスト Jacob EffronA product leader's guide to pricing AI around work, making evals the spec, and why voice and proactive agents are underrated









