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Microsoft just killed voice subscriptions. 🤯 They quietly open-sourced VibeVoice, and it’s a total industry disruptor. Transcribe hour-long meetings or generate 90 minutes of natural, multi-speaker speech, all locally on your hardware for free. It handles 50+ languages and complex speaker tracking without the monthly fees. The era of... show more

Vaibhav Sisinty

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22,132 views • 5 months ago •via X (Twitter)

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🚨 JUST IN: MICROSOFT just open sourced a VOICE AI THAT TRANSCRIBES 60 MINUTES OF AUDIO in a single pass. 100% FREE. It knows who spoke. It knows when they spoke. It knows exactly what they said. All in one shot. No chunking. No context loss. It's called VibeVoice. Not a transcription tool. Not a basic speech to text wrapper. A frontier voice AI family with ASR, TTS, and real time streaming. All open source. All free. Here's what it actually does 👇 VibeVoice ASR - Speech Recognition: → Processes 60 minutes of continuous audio in a single pass → Never slices audio into chunks so global context is never lost → Identifies WHO spoke, WHEN they spoke and WHAT they said simultaneously → Supports customized hotwords for domain specific accuracy → Works in 50+ languages natively → Already adopted by Hugging Face Transformers library → Already being built on by the open source community BY PEOPLE WHO HAD NO IDEA THIS LEVEL OF ACCURACY WAS ALREADY FREE. VibeVoice TTS - Text to Speech: → Generates up to 90 minutes of speech in a single pass → Supports up to 4 distinct speakers in one conversation → Natural turn taking and speaker consistency throughout → Expressive speech that captures emotional nuances → Supports English, Chinese and multiple other languages VibeVoice Realtime - Streaming TTS: → Only 300 millisecond first audible latency → Streams text input in real time → 0.5B parameters so it actually deploys anywhere → Robust long form generation up to 10 minutes → Lightweight enough for production use today The core innovation nobody is talking about: Most voice AI models slice long audio into short chunks. Every time they slice, they lose context. Speaker tracking breaks. Semantic coherence breaks. Accuracy drops. VibeVoice uses continuous speech tokenizers running at an ultra low frame rate of 7.5 Hz. This preserves audio fidelity while dramatically boosting computational efficiency. The entire 60 minutes stays in context. Nothing gets lost. Nobody gets misidentified. The numbers: → VibeVoice ASR 7B - available now on Hugging Face → VibeVoice Realtime 0.5B - try it on Colab right now → 50+ supported languages → 11 distinct English voice styles → 9 multilingual speaker voices → Already integrated into Hugging Face Transformers → Finetuning code now available The wildest part? A voice powered input method called Vibing just built itself on top of VibeVoice ASR. Available on macOS and Windows right now. The open source community is already shipping products on top of this. 100% Open Source. Free to use. Free to fine tune. Free to build on. 🔖 Save this before your competitors find it first. 👇

🚨 JUST IN: MICROSOFT just open sourced a VOICE AI THAT TRANSCRIBES 60 MINUTES OF AUDIO in a single pass. 100% FREE. It knows who spoke. It knows when they spoke. It knows exactly what they said. All in one shot. No chunking. No context loss. It's called VibeVoice. Not a transcription tool. Not a basic speech to text wrapper. A frontier voice AI family with ASR, TTS, and real time streaming. All open source. All free. Here's what it actually does 👇 VibeVoice ASR - Speech Recognition: → Processes 60 minutes of continuous audio in a single pass → Never slices audio into chunks so global context is never lost → Identifies WHO spoke, WHEN they spoke and WHAT they said simultaneously → Supports customized hotwords for domain specific accuracy → Works in 50+ languages natively → Already adopted by Hugging Face Transformers library → Already being built on by the open source community BY PEOPLE WHO HAD NO IDEA THIS LEVEL OF ACCURACY WAS ALREADY FREE. VibeVoice TTS - Text to Speech: → Generates up to 90 minutes of speech in a single pass → Supports up to 4 distinct speakers in one conversation → Natural turn taking and speaker consistency throughout → Expressive speech that captures emotional nuances → Supports English, Chinese and multiple other languages VibeVoice Realtime - Streaming TTS: → Only 300 millisecond first audible latency → Streams text input in real time → 0.5B parameters so it actually deploys anywhere → Robust long form generation up to 10 minutes → Lightweight enough for production use today The core innovation nobody is talking about: Most voice AI models slice long audio into short chunks. Every time they slice, they lose context. Speaker tracking breaks. Semantic coherence breaks. Accuracy drops. VibeVoice uses continuous speech tokenizers running at an ultra low frame rate of 7.5 Hz. This preserves audio fidelity while dramatically boosting computational efficiency. The entire 60 minutes stays in context. Nothing gets lost. Nobody gets misidentified. The numbers: → VibeVoice ASR 7B - available now on Hugging Face → VibeVoice Realtime 0.5B - try it on Colab right now → 50+ supported languages → 11 distinct English voice styles → 9 multilingual speaker voices → Already integrated into Hugging Face Transformers → Finetuning code now available The wildest part? A voice powered input method called Vibing just built itself on top of VibeVoice ASR. Available on macOS and Windows right now. The open source community is already shipping products on top of this. 100% Open Source. Free to use. Free to fine tune. Free to build on. 🔖 Save this before your competitors find it first. 👇

Kanika

221,715 views • 5 months ago

MICROSOFT OPEN SOURCED A 7B PARAMETER MODEL THAT TRANSCRIBES 60 MINUTES OF AUDIO IN A SINGLE PASS and it's completely free VIBEVOICE ASR no chunking, no context loss, full speaker diarization baked in not just speech to text..not a basic wrapper who spoke, when they spoke, exactly what they said..all in one shot and it handles the hard stuff too..50+ languages, custom hotwords, long form audio that breaks every other tool the model doesn't know what "context window" means apparently Available on macOS and Windows right now. Free to use. Free to fine tune. Free to build on.

MICROSOFT OPEN SOURCED A 7B PARAMETER MODEL THAT TRANSCRIBES 60 MINUTES OF AUDIO IN A SINGLE PASS and it's completely free VIBEVOICE ASR no chunking, no context loss, full speaker diarization baked in not just speech to text..not a basic wrapper who spoke, when they spoke, exactly what they said..all in one shot and it handles the hard stuff too..50+ languages, custom hotwords, long form audio that breaks every other tool the model doesn't know what "context window" means apparently Available on macOS and Windows right now. Free to use. Free to fine tune. Free to build on.

Rahul

1,375,300 views • 5 months ago

microsoft just released a tool that transcribes a full hour of audio at once, tracking who spoke and when. it's called vibevoice the 7b model processes the full recording in one shot instead of chunking it, so speaker identity and context never break across segments → full speaker diarization built in, not bolted on → structured timestamps for every speaker turn → supports 50+ languages runs locally, no api costs.

microsoft just released a tool that transcribes a full hour of audio at once, tracking who spoke and when. it's called vibevoice the 7b model processes the full recording in one shot instead of chunking it, so speaker identity and context never break across segments → full speaker diarization built in, not bolted on → structured timestamps for every speaker turn → supports 50+ languages runs locally, no api costs.

Oliver Prompts

53,501 views • 2 months ago

🚨 THIS IS INSANE A developer has released a free AI voice studio capable of cloning almost any voice in just a few seconds. It's called Voicebox. And it has already surpassed 50,500 stars on GitHub. Here's how it works: 1.- Upload a short audio sample and clone a voice in seconds. 2.- Generate speech in 23 different languages using multiple TTS engines. 3.- Run everything locally for greater privacy, and you can integrate it into your own applications. It also includes voice dictation, support for AI agents, and MCP integration. All in a single open-source tool. Save this tool. I've left the link in the next comment 👇

🚨 THIS IS INSANE A developer has released a free AI voice studio capable of cloning almost any voice in just a few seconds. It's called Voicebox. And it has already surpassed 50,500 stars on GitHub. Here's how it works: 1.- Upload a short audio sample and clone a voice in seconds. 2.- Generate speech in 23 different languages using multiple TTS engines. 3.- Run everything locally for greater privacy, and you can integrate it into your own applications. It also includes voice dictation, support for AI agents, and MCP integration. All in a single open-source tool. Save this tool. I've left the link in the next comment 👇

Nova

26,530 views • 1 month ago

🚨BREAKING: Frontdesk just quietly released a free AI workforce that automatically calls, texts, emails, and remembers ALL your customers. The workers reply 24/7 across all channels. They intelligently reach out at the right time. And since they remember every customer, they all share a custom CRM built just for them. Thousands of people are cancelling their GoHighLevel and Hubspot subscriptions and letting these AI workers run on autopilot. Try it here:

🚨BREAKING: Frontdesk just quietly released a free AI workforce that automatically calls, texts, emails, and remembers ALL your customers. The workers reply 24/7 across all channels. They intelligently reach out at the right time. And since they remember every customer, they all share a custom CRM built just for them. Thousands of people are cancelling their GoHighLevel and Hubspot subscriptions and letting these AI workers run on autopilot. Try it here:

Hasan Toor

75,368 views • 6 months ago

btw this robot runs on a fully open source AI framework called Xiaozhi it turns a $8 ESP32 chip into a fully autonomous voice assistant NO expensive cloud servers or high latency wake-word detection and audio streaming happen locally on the chip: > requires only an ESP32-S3, a microphone, and a basic speaker > supports real-time conversational voice interaction > completely open-source and customizable for any DIY robotics project anyone can now build a personal AI companion for the price of a cup of coffee. (github link in the replies)

btw this robot runs on a fully open source AI framework called Xiaozhi it turns a $8 ESP32 chip into a fully autonomous voice assistant NO expensive cloud servers or high latency wake-word detection and audio streaming happen locally on the chip: > requires only an ESP32-S3, a microphone, and a basic speaker > supports real-time conversational voice interaction > completely open-source and customizable for any DIY robotics project anyone can now build a personal AI companion for the price of a cup of coffee. (github link in the replies)

ard

42,210 views • 1 month ago

Text-to-speech is moving way too fast. Just a few days ago, I tweeted about PersonaPlex-7B, NVIDIA's new open source TTS ( And today, Qwen just open-sourced Qwen3-TTS 🤯 It’s a revolutionary text-to-speech model built for control. Not just about generating speech, but about shaping how it sounds directly from language. You can guide the pace, the tone, and the expressiveness straight from text, without touching audio graphs or hand-tuning parameters. That’s the real shift! What makes Qwen3-TTS stand out is how practical it already is: → voice cloning from just a few seconds of audio → voice creation without any reference sample → support for 10 languages out of the box → end-to-end latency down to ~97ms → works in both streaming and non-streaming setups The models come in two sizes (0.6B and 1.7B), so you can trade off quality and hardware cost depending on your setup. You can work with curated voices, designed voices, or cloned ones, and it integrates cleanly with vLLM for production use. It also ships as a simple Python package you can pip install. If you’re building real-time voice systems, this removes a lot of friction! 100% free and open source. I put the repo in the 🧵↓

Text-to-speech is moving way too fast. Just a few days ago, I tweeted about PersonaPlex-7B, NVIDIA's new open source TTS ( And today, Qwen just open-sourced Qwen3-TTS 🤯 It’s a revolutionary text-to-speech model built for control. Not just about generating speech, but about shaping how it sounds directly from language. You can guide the pace, the tone, and the expressiveness straight from text, without touching audio graphs or hand-tuning parameters. That’s the real shift! What makes Qwen3-TTS stand out is how practical it already is: → voice cloning from just a few seconds of audio → voice creation without any reference sample → support for 10 languages out of the box → end-to-end latency down to ~97ms → works in both streaming and non-streaming setups The models come in two sizes (0.6B and 1.7B), so you can trade off quality and hardware cost depending on your setup. You can work with curated voices, designed voices, or cloned ones, and it integrates cleanly with vLLM for production use. It also ships as a simple Python package you can pip install. If you’re building real-time voice systems, this removes a lot of friction! 100% free and open source. I put the repo in the 🧵↓

Charly Wargnier

59,144 views • 8 months ago

VoiceBox just did what everyone thought was impossible. It might have killed ElevenLabs overnight. No subscription. No cloud. No credits. Runs locally on your machine. Clones a voice from 3 seconds of audio. Powered by Qwen 3 TTS. Apache 2.0 license. Commercial use allowed. And your voice data never leaves your computer. For years, if you wanted high quality voice cloning, ElevenLabs was the default. Now there’s a free open-source alternative that sounds shockingly close. Plus it has a built-in multi-track editor, recording, transcription with Whisper, and a local API. This isn’t just another TTS tool. It’s a full voice production studio on your desktop. Open source AI is catching up fast. And this changes the game for creators and businesses. Would you trust the cloud with your voice… or keep it local? 👇

VoiceBox just did what everyone thought was impossible. It might have killed ElevenLabs overnight. No subscription. No cloud. No credits. Runs locally on your machine. Clones a voice from 3 seconds of audio. Powered by Qwen 3 TTS. Apache 2.0 license. Commercial use allowed. And your voice data never leaves your computer. For years, if you wanted high quality voice cloning, ElevenLabs was the default. Now there’s a free open-source alternative that sounds shockingly close. Plus it has a built-in multi-track editor, recording, transcription with Whisper, and a local API. This isn’t just another TTS tool. It’s a full voice production studio on your desktop. Open source AI is catching up fast. And this changes the game for creators and businesses. Would you trust the cloud with your voice… or keep it local? 👇

Julian Goldie SEO

59,167 views • 7 months ago

How did a tiny, scrappy team build one of the most powerful AI voice models? In a deep dive with Sesame CTO Ankit Kumar and a16z's Anjney Midha, we explore how Sesame is pushing the boundaries of AI conversation, why it open-sourced its speech generation model, and the power of small teams to outdo much larger AI labs on product focus. A part of their secret: a relentless focus on real-time, natural conversations over raw intelligence, and a deep commitment to voice, personality, and user experience. By opening up its speech generation model, Sesame is paving the way for even more breakthroughs in AI-native conversation 👇

How did a tiny, scrappy team build one of the most powerful AI voice models? In a deep dive with Sesame CTO Ankit Kumar and a16z's Anjney Midha, we explore how Sesame is pushing the boundaries of AI conversation, why it open-sourced its speech generation model, and the power of small teams to outdo much larger AI labs on product focus. A part of their secret: a relentless focus on real-time, natural conversations over raw intelligence, and a deep commitment to voice, personality, and user experience. By opening up its speech generation model, Sesame is paving the way for even more breakthroughs in AI-native conversation 👇

a16z

29,930 views • 1 year ago

Claude tokens can be saved by using this simple hack. Every reply, Claude rereads your entire chat from the top before responding. Silently burning your limit before a single word comes back. Someone on Reddit figured out a one-line fix that cuts usage by 75%. Same answers. Same AI. Just stops letting it talk more than it needs to. Exact prompt is pinned in the first comment. Free. I share updates like these in my free AI community on WhatsApp. Join here 👇

Claude tokens can be saved by using this simple hack. Every reply, Claude rereads your entire chat from the top before responding. Silently burning your limit before a single word comes back. Someone on Reddit figured out a one-line fix that cuts usage by 75%. Same answers. Same AI. Just stops letting it talk more than it needs to. Exact prompt is pinned in the first comment. Free. I share updates like these in my free AI community on WhatsApp. Join here 👇

Vaibhav Sisinty

22,408 views • 5 months ago

after three months of building, i'm officially sharing my app sono 🥳 sono is my 100% offline transcription and summarization app! you can use it to: - transcribe voice notes, real-time audio, videos in 99 languages - share transcripts as txt, pdf, docx, or srt file - get ai summary and chat i built this app because i didn't want my recordings in the cloud + didn't want to pay recurring subscriptions sono is just $4.99 one-time while most ai notetakers charge $100+ annually would mean a lot if u try it out!

after three months of building, i'm officially sharing my app sono 🥳 sono is my 100% offline transcription and summarization app! you can use it to: - transcribe voice notes, real-time audio, videos in 99 languages - share transcripts as txt, pdf, docx, or srt file - get ai summary and chat i built this app because i didn't want my recordings in the cloud + didn't want to pay recurring subscriptions sono is just $4.99 one-time while most ai notetakers charge $100+ annually would mean a lot if u try it out!

jenna ☁️

132,573 views • 6 months ago

Tired of AI app builders that lock you into subscriptions and limit your model choices? 🤔 Meet : The free, local, open-source vibe coding tool that actually sets you free. 💻 Runs on your computer (Mac/Windows) 🗝️Model freedom: Use any AI model (Gemini 2.5 Flash or Pro? Free OpenRouter ones? it’s your choice!) 🦋Zero lock-in: Integrates smoothly with editors like Cursor, VS Code, etc. ♾️Truly free: Build unlimited apps without restrictions It’s not just theory. 1000+ builders are already using it, 12+ releases shipped. Dyad is dropping updates weekly based on amazing community feedback. Stop renting your tools. Start owning them. 👉 Download Dyad free: (P.S. 👀Check out the momentum on Product Hunt too →) #opensource #developers #programmers #dsa #100daysofcode #letsconnect

Tired of AI app builders that lock you into subscriptions and limit your model choices? 🤔 Meet : The free, local, open-source vibe coding tool that actually sets you free. 💻 Runs on your computer (Mac/Windows) 🗝️Model freedom: Use any AI model (Gemini 2.5 Flash or Pro? Free OpenRouter ones? it’s your choice!) 🦋Zero lock-in: Integrates smoothly with editors like Cursor, VS Code, etc. ♾️Truly free: Build unlimited apps without restrictions It’s not just theory. 1000+ builders are already using it, 12+ releases shipped. Dyad is dropping updates weekly based on amazing community feedback. Stop renting your tools. Start owning them. 👉 Download Dyad free: (P.S. 👀Check out the momentum on Product Hunt too →) #opensource #developers #programmers #dsa #100daysofcode #letsconnect

Shruti Codes

18,154 views • 1 year ago

You can now generate real-time speech that sounds conversational. Microsoft just open-sourced VibeVoice, a real-time text-to-speech system with ~300 ms first audio latency and streaming input. It handles long conversations without falling apart. 𝗧𝗵𝗶𝘀 𝗺𝗼𝗱𝗲𝗹 𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗲𝘀 𝗹𝗼𝗻𝗴, 𝗺𝘂𝗹𝘁𝗶-𝘀𝗽𝗲𝗮𝗸𝗲𝗿 𝘀𝗽𝗲𝗲𝗰𝗵. It produces up to 90 minutes of audio. It supports up to four distinct speakers. Turn-taking stays consistent over long sessions. 𝗜𝘁 𝘄𝗼𝗿𝗸𝘀 𝗯𝘆 𝗿𝗲𝗱𝘂𝗰𝗶𝗻𝗴 𝘁𝗶𝗺𝗲 𝗿𝗲𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻. Audio compresses into semantic and acoustic tokens. They run at 7.5 Hz instead of frame-level audio. A language model predicts structure. A diffusion head restores acoustic detail. 𝗜𝘁 𝗮𝗹𝗹𝗼𝘄𝘀 𝗹𝗼𝘄-𝗹𝗮𝘁𝗲𝗻𝗰𝘆 𝘀𝘁𝗿𝗲𝗮𝗺𝗶𝗻𝗴 𝗮𝘂𝗱𝗶𝗼. The real-time variant streams text incrementally. First speech arrives in ~300 ms. A WebSocket demo shows live generation. The code is MIT-licensed and research-only. The repo already passed 20k GitHub stars.

You can now generate real-time speech that sounds conversational. Microsoft just open-sourced VibeVoice, a real-time text-to-speech system with ~300 ms first audio latency and streaming input. It handles long conversations without falling apart. 𝗧𝗵𝗶𝘀 𝗺𝗼𝗱𝗲𝗹 𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗲𝘀 𝗹𝗼𝗻𝗴, 𝗺𝘂𝗹𝘁𝗶-𝘀𝗽𝗲𝗮𝗸𝗲𝗿 𝘀𝗽𝗲𝗲𝗰𝗵. It produces up to 90 minutes of audio. It supports up to four distinct speakers. Turn-taking stays consistent over long sessions. 𝗜𝘁 𝘄𝗼𝗿𝗸𝘀 𝗯𝘆 𝗿𝗲𝗱𝘂𝗰𝗶𝗻𝗴 𝘁𝗶𝗺𝗲 𝗿𝗲𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻. Audio compresses into semantic and acoustic tokens. They run at 7.5 Hz instead of frame-level audio. A language model predicts structure. A diffusion head restores acoustic detail. 𝗜𝘁 𝗮𝗹𝗹𝗼𝘄𝘀 𝗹𝗼𝘄-𝗹𝗮𝘁𝗲𝗻𝗰𝘆 𝘀𝘁𝗿𝗲𝗮𝗺𝗶𝗻𝗴 𝗮𝘂𝗱𝗶𝗼. The real-time variant streams text incrementally. First speech arrives in ~300 ms. A WebSocket demo shows live generation. The code is MIT-licensed and research-only. The repo already passed 20k GitHub stars.

Lior Alexander

61,122 views • 8 months ago

I thought I needed a powerful GPU to run serious AI locally. I was completely wrong. Late 2025, Ollama quietly launched something that changed everything. They built a cloud inference layer running on NVIDIA's Blackwell architecture, the most powerful GPU hardware available today. No GPU on your desk required. No expensive API subscription. No complex setup. Just one command and you're running Kimi K2.5, a 1 trillion parameter open-source model, completely free. I connected it to OpenClaw, which links my phone's messaging apps to the AI agent running at home. I sent a message from WhatsApp. My machine picked it up, ran the task, and sent me back the result. It felt like magic. It's just good engineering. Save this post, you'll want this when you're building your first workflow. Want the SOP? DM me.

I thought I needed a powerful GPU to run serious AI locally. I was completely wrong. Late 2025, Ollama quietly launched something that changed everything. They built a cloud inference layer running on NVIDIA's Blackwell architecture, the most powerful GPU hardware available today. No GPU on your desk required. No expensive API subscription. No complex setup. Just one command and you're running Kimi K2.5, a 1 trillion parameter open-source model, completely free. I connected it to OpenClaw, which links my phone's messaging apps to the AI agent running at home. I sent a message from WhatsApp. My machine picked it up, ran the task, and sent me back the result. It felt like magic. It's just good engineering. Save this post, you'll want this when you're building your first workflow. Want the SOP? DM me.

Julian Goldie SEO

11,967 views • 6 months ago

🇺🇸 ALL IN PODCAST: ONLY GROK AND GEMINI MATTER IN AI RIGHT NOW On the latest All In, Chamath crowned Grok and Gemini as his phone's only AI anchors: "I try to limit the number of apps on the phone, but I have Gemini and Grok as the 2 anchor apps because I'm so reliant on both of them, and I just keep going back and forth between them now." But the real tea was Jason calling the AI war "the greatest battle we've seen since Netscape versus Microsoft." He predicts that Google is planning to "suck the oxygen out of the room" by making everything free and strangling competitors. "People used to pay 50 bucks for a Netscape browser. Microsoft came in and made it free. The same thing's going to happen to ChatGPT. Right now, 80% of the revenue comes from $20 subscriptions." The AI throne isn't decided by benchmarks anymore. Grok wins again. Source: All In Podcast, @jason, Chamath Palihapitiya

🇺🇸 ALL IN PODCAST: ONLY GROK AND GEMINI MATTER IN AI RIGHT NOW On the latest All In, Chamath crowned Grok and Gemini as his phone's only AI anchors: "I try to limit the number of apps on the phone, but I have Gemini and Grok as the 2 anchor apps because I'm so reliant on both of them, and I just keep going back and forth between them now." But the real tea was Jason calling the AI war "the greatest battle we've seen since Netscape versus Microsoft." He predicts that Google is planning to "suck the oxygen out of the room" by making everything free and strangling competitors. "People used to pay 50 bucks for a Netscape browser. Microsoft came in and made it free. The same thing's going to happen to ChatGPT. Right now, 80% of the revenue comes from $20 subscriptions." The AI throne isn't decided by benchmarks anymore. Grok wins again. Source: All In Podcast, @jason, Chamath Palihapitiya

Mario Nawfal

108,531 views • 9 months ago

Jensen Huang open-sourced NVIDIA's flagship AI model, its weights, its data, AND how they created it. "We open sourced the models," Huang says. "We open sourced the weights." "We open sourced the data." "We open sourced how we created it." Four layers of openness in one model release. "Open source is fundamentally necessary for many industries to join the AI revolution." "NVIDIA has the scale and the motivation to build and continue to build these AI models for as long as we shall live." The chip seller benefits when every model is open. NVIDIA is the chip seller. P.S. I made a playbook breaking down 100+ most powerful decision making mental models used by history's greatest thinkers. 5,000+ downloads. 113 five-star reviews. Grab a free copy here: If you're new here, follow GeniusThinking for content on the greatest minds in economics, psychology, and history. — Jensen Huang ( NVIDIA ), NVIDIA CEO, on Lex Fridman's ( Lex Fridman ) podcast

Jensen Huang open-sourced NVIDIA's flagship AI model, its weights, its data, AND how they created it. "We open sourced the models," Huang says. "We open sourced the weights." "We open sourced the data." "We open sourced how we created it." Four layers of openness in one model release. "Open source is fundamentally necessary for many industries to join the AI revolution." "NVIDIA has the scale and the motivation to build and continue to build these AI models for as long as we shall live." The chip seller benefits when every model is open. NVIDIA is the chip seller. P.S. I made a playbook breaking down 100+ most powerful decision making mental models used by history's greatest thinkers. 5,000+ downloads. 113 five-star reviews. Grab a free copy here: If you're new here, follow GeniusThinking for content on the greatest minds in economics, psychology, and history. — Jensen Huang ( NVIDIA ), NVIDIA CEO, on Lex Fridman's ( Lex Fridman ) podcast

GeniusThinking

14,769 views • 3 months ago

This robot assistant from the NVIDIA CES Keynote on Monday is going viral. Nader Khalil🍊 explains all the hottest emerging AI trends in one demo: AI applications in 2026 will be multi-model, multi-modal, hybrid cloud/local, use open source models as well as proprietary models, control robots and embedded devices in the physical world, and have voice interfaces. (And the demo had a cute robot *and* a cute dog. Gold.) The demo was built with Pipecat AI. NVIDIA posted a really nice technical walk-through and complete code. The Reachy Mini robot from Hugging Face is open source hardware. (You can order it now, I have one!). You can run the assistant locally on your own hardware, in the cloud, or both.

This robot assistant from the NVIDIA CES Keynote on Monday is going viral. Nader Khalil🍊 explains all the hottest emerging AI trends in one demo: AI applications in 2026 will be multi-model, multi-modal, hybrid cloud/local, use open source models as well as proprietary models, control robots and embedded devices in the physical world, and have voice interfaces. (And the demo had a cute robot and a cute dog. Gold.) The demo was built with Pipecat AI. NVIDIA posted a really nice technical walk-through and complete code. The Reachy Mini robot from Hugging Face is open source hardware. (You can order it now, I have one!). You can run the assistant locally on your own hardware, in the cloud, or both.

kwindla

49,032 views • 8 months ago

Today, we’re launching Gemini 3.5 Transcribe, our new speech-to-text model with sub-second streaming and intelligent post-processing for agent interfaces. 2.6% WER on non-streaming and 4.0% on streaming. Supports 85+ languages, cleans up conversational disfluencies ("um", "ah", and mid-sentence self-corrections), handles alphanumeric tokens (postal codes or IDs), 70% reduction time for the final transcription compared to Chirp 3. - `gemini-3.5-transcribe-live`: Sub-second, bidirectional streaming via the Gemini Live API - `gemini-3.5-transcribe`: Recorded processing via the Interactions API with word-level timestamps and speaker attribution (up to 3 speakers). Having access to Transcribe has made me use voice input way more than I ever did before. The native post-processing is incredible. It knows you mean `.json` and not a person named "Jason". I sometimes speak 5 minutes into and it perfectly refactors my instruction to my context. Available today in public preview in Gemini API, Google AI Studio and already in the Google Gemini and Google Antigravity. Try here:

Today, we’re launching Gemini 3.5 Transcribe, our new speech-to-text model with sub-second streaming and intelligent post-processing for agent interfaces. 2.6% WER on non-streaming and 4.0% on streaming. Supports 85+ languages, cleans up conversational disfluencies ("um", "ah", and mid-sentence self-corrections), handles alphanumeric tokens (postal codes or IDs), 70% reduction time for the final transcription compared to Chirp 3. - `gemini-3.5-transcribe-live`: Sub-second, bidirectional streaming via the Gemini Live API - `gemini-3.5-transcribe`: Recorded processing via the Interactions API with word-level timestamps and speaker attribution (up to 3 speakers). Having access to Transcribe has made me use voice input way more than I ever did before. The native post-processing is incredible. It knows you mean `.json` and not a person named "Jason". I sometimes speak 5 minutes into and it perfectly refactors my instruction to my context. Available today in public preview in Gemini API, Google AI Studio and already in the Google Gemini and Google Antigravity. Try here:

Philipp Schmid

15,084 views • 1 month ago

The best way to take advantage of ChatGPT Voice. I am completely and utterly voice-pilled. Voice interaction with AI is going to change the way humans interact with computers. Here's what you can do: 1. Create a remote connection to an always-on desktop PC through the ChatGPT Desktop app (I have a Linux box in my basement) 2. Customize the ChatGPT iOS widget and add a remote voice connection 3. Tap the widget. It will open a voice chat in ChatGPT Work/Codex, on your desktop, with access to your files and all your apps. It's like an always on Jarvis that has its own computer. Amazing stuff. Try it out!

The best way to take advantage of ChatGPT Voice. I am completely and utterly voice-pilled. Voice interaction with AI is going to change the way humans interact with computers. Here's what you can do: 1. Create a remote connection to an always-on desktop PC through the ChatGPT Desktop app (I have a Linux box in my basement) 2. Customize the ChatGPT iOS widget and add a remote voice connection 3. Tap the widget. It will open a voice chat in ChatGPT Work/Codex, on your desktop, with access to your files and all your apps. It's like an always on Jarvis that has its own computer. Amazing stuff. Try it out!

Dan McAteer

46,322 views • 1 month ago