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Alibaba just open-sourced the world's FIRST AI dubbing model that handles multi-speaker scenes. It's called Fun-CineForge and it nails what every other dubbing model fails at: Lip-sync. Emotion. Voice stability. Timing. Across multiple characters. Not a single open-source model could do this before. Here's how it works: ↓ Tongyi...

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Guri Singh

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620,634 görüntüleme • 4 ay önce •via X (Twitter)

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Everyone thinks AI dubbing needs clear, visible lips. But what if it could do more? 🤔 Watch this clip: lips partially blocked, off-screen moments, fast cuts — still perfect sync! 🤯 Discover Fun-CineForge, the FIRST open-source AI dubbing model for multi-speaker scenes. It sees what others can't. 👇 Tongyi Lab Alibaba Group
0:39

Everyone thinks AI dubbing needs clear, visible lips. But what if it could do more? 🤔 Watch this clip: lips partially blocked, off-screen moments, fast cuts — still perfect sync! 🤯 Discover Fun-CineForge, the FIRST open-source AI dubbing model for multi-speaker scenes. It sees what others can't. 👇 Tongyi Lab Alibaba Group

Deborah

40,933 görüntüleme • 4 ay önce

Open source models are crazy. Alibaba just dropped Wan 2.2 Animate, a new model that can animate any character based on a simple souce image. It handles facial expressions and body movements like no other model. 10 insane examples: (sound on)
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Open source models are crazy. Alibaba just dropped Wan 2.2 Animate, a new model that can animate any character based on a simple souce image. It handles facial expressions and body movements like no other model. 10 insane examples: (sound on)

Angry Tom

4,259,222 görüntüleme • 10 ay önce

🚨BREAKING: A new open-source voice model just dropped and it’s better than ElevenLabs. This open-source voice AI is ultra-expressive, high quality, and fully free with no paywalls, no limits. Here’s how it works (with real examples):👇
0:26

🚨BREAKING: A new open-source voice model just dropped and it’s better than ElevenLabs. This open-source voice AI is ultra-expressive, high quality, and fully free with no paywalls, no limits. Here’s how it works (with real examples):👇

Sehaj Singh

814,129 görüntüleme • 11 ay önce

Chinese labs are now competing with each other to build the strongest open-weight model. > DeepSeek started the domino effect > Qwen kept improving across coding, reasoning and long context > GLM, MiniMax and Moonshot joined the race > Kimi K3 pushed it to 2.8T parameters and a 1M context window > now Alibaba is answering with Qwen3.8 > 2.4T parameters > full open-weight release coming soon > Alibaba says it is second only to Fable 5 Qwen3.8 may be the model that brings open-weight AI closest to Claude Fable 5.
0:23

Chinese labs are now competing with each other to build the strongest open-weight model. > DeepSeek started the domino effect > Qwen kept improving across coding, reasoning and long context > GLM, MiniMax and Moonshot joined the race > Kimi K3 pushed it to 2.8T parameters and a 1M context window > now Alibaba is answering with Qwen3.8 > 2.4T parameters > full open-weight release coming soon > Alibaba says it is second only to Fable 5 Qwen3.8 may be the model that brings open-weight AI closest to Claude Fable 5.

Tornado guy

64,960 görüntüleme • 14 gün önce

Hey Theo - t3.gg my Tesla has a local model running it. It works without being connected at all. And doesn’t kill me. Just got home. Alibaba Cloud researchers told me this week at ACL that the real action in the labs is building smaller models. So the open source & “run locally” bulls will have their day.
0:31

Hey Theo - t3.gg my Tesla has a local model running it. It works without being connected at all. And doesn’t kill me. Just got home. Alibaba Cloud researchers told me this week at ACL that the real action in the labs is building smaller models. So the open source & “run locally” bulls will have their day.

Robert Scoble

18,231 görüntüleme • 24 gün önce

Introducing Oasis: the first playable AI-generated game. We partnered with Decart to build a real-time, interactive world model that runs >10x faster on Sohu. We're open-sourcing the model architecture, weights, and research. Here's how it works (and a demo you can play!):
0:24

Introducing Oasis: the first playable AI-generated game. We partnered with Decart to build a real-time, interactive world model that runs >10x faster on Sohu. We're open-sourcing the model architecture, weights, and research. Here's how it works (and a demo you can play!):

Etched

24,692,582 görüntüleme • 1 yıl önce

🚨 ALIBABA JUST OPEN-SOURCED THE MOST POWERFUL MODEL IN THE WORLD - Qwen3.5 plus And it changes the AI race forever. This is not another “bigger model” release. This is a complete architectural reset. 397B parameters → only 17B active at inference, Qwen3.5 plus delivers performance on par with GPT-5.2 and Gemini-3-Pro. A new Hybrid Sparse MoE + Linear Attention architecture + Multi-Token Prediction = near-instant long-context responses and massive speed gains. Built as a true native multimodal model, it doesn’t just chat it builds. With a single prompt: “Use the React framework to create a visually impressive Mapbox demo featuring locations in Beijing and Shanghai” it generates a live interactive 3D map UI, structured components, real layouts, and production-ready frontend logic. This is real agentic, multimodal coding not a static code block. MMLU-Pro: 87.8 GPQA: 88.4 IFBench: 76.5 ⚡ up to 8× faster inference And it’s fully open-sourced under Apache-2.0. No locked APIs. No restricted tiers. 201 languages supported bringing frontier AI to developers, startups, and researchers worldwide. The race is no longer about the biggest model. It’s about the most usable intelligence. Open source just entered the top tier.
1:50

🚨 ALIBABA JUST OPEN-SOURCED THE MOST POWERFUL MODEL IN THE WORLD - Qwen3.5 plus And it changes the AI race forever. This is not another “bigger model” release. This is a complete architectural reset. 397B parameters → only 17B active at inference, Qwen3.5 plus delivers performance on par with GPT-5.2 and Gemini-3-Pro. A new Hybrid Sparse MoE + Linear Attention architecture + Multi-Token Prediction = near-instant long-context responses and massive speed gains. Built as a true native multimodal model, it doesn’t just chat it builds. With a single prompt: “Use the React framework to create a visually impressive Mapbox demo featuring locations in Beijing and Shanghai” it generates a live interactive 3D map UI, structured components, real layouts, and production-ready frontend logic. This is real agentic, multimodal coding not a static code block. MMLU-Pro: 87.8 GPQA: 88.4 IFBench: 76.5 ⚡ up to 8× faster inference And it’s fully open-sourced under Apache-2.0. No locked APIs. No restricted tiers. 201 languages supported bringing frontier AI to developers, startups, and researchers worldwide. The race is no longer about the biggest model. It’s about the most usable intelligence. Open source just entered the top tier.

RAVI KUMAR SAHU

380,123 görüntüleme • 5 ay önce

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.
5:45

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

1,373,564 görüntüleme • 3 ay önce

NVIDIA just removed the biggest friction point in Voice AI 🤯 They've open-sourced PersonaPlex-7B, a full-duplex conversational model that can listen and speak at the same time. Instead of waiting for you to finish talking, it uses a dual-stream architecture to process and respond in real-time. 100% Open-Source and Free.
0:42

NVIDIA just removed the biggest friction point in Voice AI 🤯 They've open-sourced PersonaPlex-7B, a full-duplex conversational model that can listen and speak at the same time. Instead of waiting for you to finish talking, it uses a dual-stream architecture to process and respond in real-time. 100% Open-Source and Free.

Simplifying AI

278,970 görüntüleme • 6 ay önce

Let's be real: we can't beat AI in speed. So why compete? Instead, let's use it to create something REAL. Meet SkyReels - All-in-one AI Video Creation Platform V3, the world's FIRST AI model for true multi-person conversations! Upload a group photo, assign voices, and generate a video with multiple characters talking naturally. It's not just about being fast, it's about being groundbreaking ➜
0:37

Let's be real: we can't beat AI in speed. So why compete? Instead, let's use it to create something REAL. Meet SkyReels - All-in-one AI Video Creation Platform V3, the world's FIRST AI model for true multi-person conversations! Upload a group photo, assign voices, and generate a video with multiple characters talking naturally. It's not just about being fast, it's about being groundbreaking ➜

Eyisha Zyer

35,018 görüntüleme • 9 ay önce

Alibaba just dropped an AI that doesn’t just write code. It runs it. Tests it. Fixes it. Until it actually works. Here’s what makes Qwen 3 Coder Next different: → Executes code, not just autocomplete → Runs tests automatically → Iterates until all tests pass → Handles multi-file repositories → Works fully offline This is a real coding agent, not a text generator. Save this video, you’ll rethink how coding gets done. Want the SOP? DM me. 💬
8:15

Alibaba just dropped an AI that doesn’t just write code. It runs it. Tests it. Fixes it. Until it actually works. Here’s what makes Qwen 3 Coder Next different: → Executes code, not just autocomplete → Runs tests automatically → Iterates until all tests pass → Handles multi-file repositories → Works fully offline This is a real coding agent, not a text generator. Save this video, you’ll rethink how coding gets done. Want the SOP? DM me. 💬

Julian Goldie SEO

20,956 görüntüleme • 5 ay önce

Alibaba just dropped a free AI that codes like a $150/hr developer. And it runs on your laptop. Qwen 3 Coder Next has 80 billion parameters but only uses 3 billion at a time. So you get massive model power with tiny model speed. The real kicker? It handles 256,000 tokens of context. That's your entire codebase. Every file. All at once. People are building 2D games in seconds. Full IDE integrations that write, test, and fix code automatically. Custom business tools without hiring devs. It works with OpenClaw, Claude Code, and every major coding tool. No complicated setup. Just download and go. Completely open source. Zero API queues. You own it. Your competitors are using this right now.
8:02

Alibaba just dropped a free AI that codes like a $150/hr developer. And it runs on your laptop. Qwen 3 Coder Next has 80 billion parameters but only uses 3 billion at a time. So you get massive model power with tiny model speed. The real kicker? It handles 256,000 tokens of context. That's your entire codebase. Every file. All at once. People are building 2D games in seconds. Full IDE integrations that write, test, and fix code automatically. Custom business tools without hiring devs. It works with OpenClaw, Claude Code, and every major coding tool. No complicated setup. Just download and go. Completely open source. Zero API queues. You own it. Your competitors are using this right now.

Julian Goldie SEO

30,259 görüntüleme • 5 ay önce

What if you could hand AI your characters, scenes, music, and footage - and it just... made the video? That's AI video model Dreamina Seedance 2.5! Coming out soon! - Up to 50 multimodal reference assets supported - 3D white model + green screen editing - Auto lip-sync across 10+ global languages - Long video mode generating up to 3 minutes Get your early access here: #dreamina #dreaminapartner #seedance #dreaminaseedance25 #sponsored #ad
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What if you could hand AI your characters, scenes, music, and footage - and it just... made the video? That's AI video model Dreamina Seedance 2.5! Coming out soon! - Up to 50 multimodal reference assets supported - 3D white model + green screen editing - Auto lip-sync across 10+ global languages - Long video mode generating up to 3 minutes Get your early access here: #dreamina #dreaminapartner #seedance #dreaminaseedance25 #sponsored #ad

Madza 👨‍💻⚡

36,162 görüntüleme • 3 gün önce

ADAM CURRY: I'M NOT A BIG BELIEVER IN AI "I run these models at home on my own computer. I run the llama model, which is, Meta. They've open sourced it. I've, I've run the French one, and then DeepSeek, and it's not very impressive. It's just not. The the error rate is too high, so I'm I'm skeptical of it." Source: Joe Rogan
1:40

ADAM CURRY: I'M NOT A BIG BELIEVER IN AI "I run these models at home on my own computer. I run the llama model, which is, Meta. They've open sourced it. I've, I've run the French one, and then DeepSeek, and it's not very impressive. It's just not. The the error rate is too high, so I'm I'm skeptical of it." Source: Joe Rogan

Mario Nawfal

202,113 görüntüleme • 1 yıl önce

Today we’re launching our first homegrown AI model: an open source turn detection model for building voice agents. Instead of relying solely on voice activity detection (VAD), which only considers when a user is speaking, our model also considers what has and is being said in the context of a conversation and predicts when a user is finished expressing their thoughts before the agent responds. Conversations with AI voice agents using this new model flow much more naturally without constant interruptions from the AI— check it out (more videos, details, and code in the thread):
2:36

Today we’re launching our first homegrown AI model: an open source turn detection model for building voice agents. Instead of relying solely on voice activity detection (VAD), which only considers when a user is speaking, our model also considers what has and is being said in the context of a conversation and predicts when a user is finished expressing their thoughts before the agent responds. Conversations with AI voice agents using this new model flow much more naturally without constant interruptions from the AI— check it out (more videos, details, and code in the thread):

LiveKit

126,898 görüntüleme • 1 yıl önce

FULL INTERVIEW: Engineers Edward Coristine (Edward Coristine) and Tai Groot (Tai Groot 🐧) just released an ML model called Rampart for the National Design Studio. It's a local-first, open-source AI privacy model that runs entirely in the browser. They joined TBPN to explain the model and why the National Design Studio launched it. 0:25 – National Design Studio launches Rampart 1:40 – Why Rampart is open source 2:40 – How NDS trained the model 3:55 – Use cases for the model 5:25 – How NDS thinks about side quests 6:25 – Team size, workflow, and why they work seven days a week 8:00 – Recruiting top talent to the National Design Studio
9:26

FULL INTERVIEW: Engineers Edward Coristine (Edward Coristine) and Tai Groot (Tai Groot 🐧) just released an ML model called Rampart for the National Design Studio. It's a local-first, open-source AI privacy model that runs entirely in the browser. They joined TBPN to explain the model and why the National Design Studio launched it. 0:25 – National Design Studio launches Rampart 1:40 – Why Rampart is open source 2:40 – How NDS trained the model 3:55 – Use cases for the model 5:25 – How NDS thinks about side quests 6:25 – Team size, workflow, and why they work seven days a week 8:00 – Recruiting top talent to the National Design Studio

TBPN

116,392 görüntüleme • 1 ay önce

🚨 Forget LIDAR. The Robbyant team just dropped a streaming 3D model that reconstructs scenes live, at ~20 FPS, over long sequences. One single camera. Runs in real time. Open-source. Entirely end-to-end. NO iterative optimization tricks and no post-processing cleanup steps! It outperforms both existing streaming approaches and several offline methods. 100% Free and open-source. Repo, paper and model weights in 🧵↓
3:30

🚨 Forget LIDAR. The Robbyant team just dropped a streaming 3D model that reconstructs scenes live, at ~20 FPS, over long sequences. One single camera. Runs in real time. Open-source. Entirely end-to-end. NO iterative optimization tricks and no post-processing cleanup steps! It outperforms both existing streaming approaches and several offline methods. 100% Free and open-source. Repo, paper and model weights in 🧵↓

Charly Wargnier

35,993 görüntüleme • 1 ay önce

MICROSOFT DROPPED A 4B PARAMETER MODEL THAT TURNS ONE IMAGE INTO A 3D ASSET IN 3 SECONDS and it's open source TRELLIS.2 fully textured, physically accurate 3D models with PBR textures out of the box not a rough mesh..not a placeholder roughness, metallic, opacity the kind of detail that makes things look real under any lighting and it handles the weird stuff too..open surfaces, hollow interiors, geometry that breaks every other tool the model doesn't know the word "limitation" apparently demo is live on hugging face right now
0:43

MICROSOFT DROPPED A 4B PARAMETER MODEL THAT TURNS ONE IMAGE INTO A 3D ASSET IN 3 SECONDS and it's open source TRELLIS.2 fully textured, physically accurate 3D models with PBR textures out of the box not a rough mesh..not a placeholder roughness, metallic, opacity the kind of detail that makes things look real under any lighting and it handles the weird stuff too..open surfaces, hollow interiors, geometry that breaks every other tool the model doesn't know the word "limitation" apparently demo is live on hugging face right now

Vaishnavi

354,571 görüntüleme • 3 ay önce

Alibaba just released a coding model that hits 82 percent on SWE-Bench Verified. That is the highest score ever published for an open-source model. The weights are free. The license is Apache 2.0. You can run it today. The model is Qwen 4 Coder 32B. Here is what 82 percent on SWE-Bench Verified actually means. SWE-Bench Verified tests whether an AI can autonomously resolve real bugs pulled from real production GitHub repositories. Not synthetic exercises. Real open-source projects that real teams depend on. A model gets a bug report, reads the code, writes a fix, and either passes the test suite or it does not. At 82 percent, Qwen 4 Coder 32B resolves 82 out of every 100 real production bugs it is given. Without a human guiding it. On code it has never seen before. For comparison: Qwen 4 Coder 32B: 82 percent SWE-Bench Verified. Open source. Apache 2.0. Claude Fable 5: 80.3 percent SWE-Bench Pro. $10 input / $50 output per million tokens. Currently suspended. GPT-5.6 Sol: Competitive on Terminal-Bench. $5 input / $30 output per million tokens. An open-weight model that you can download and run for free just beat both of them on the benchmark designed to measure real software engineering capability. Here is the architecture. Qwen 4 Coder 32B is a 32 billion parameter dense model. Not a Mixture-of-Experts. Every parameter is active on every request. This matters for inference: a dense 32B model runs on 22 gigabytes of VRAM, which fits on a single high-end consumer GPU or a MacBook Pro with 64GB of unified memory. The smaller variant, Qwen 4 Coder 4B, runs at approximately 135 tokens per second on an M5 Max and fits inside 8 gigabytes of RAM. For a model with usable coding capability, that is a new bar for what fits in a single laptop. The training methodology continued Alibaba's approach of reinforcement learning on verifiable coding tasks. The model gets rewarded when its code passes tests. It gets penalized when it fails. Over millions of training steps, the model learns to write code that actually runs rather than code that looks plausible. License: Apache 2.0. Full commercial use. No attribution requirement. No revenue threshold. No monthly active user ceiling. Weights: Hugging Face, available today. Runs on: vLLM, Ollama, SGLang, and any standard GGUF-compatible inference engine. Qwen 4 32B also runs at approximately 135 tokens per second on an M5 Max chip, setting a new bar for what a sub-8GB model can do on Apple Silicon. The open-source coding model just beat the best closed-source model in the world on the benchmark designed to test whether AI can actually do software engineering. The weights are free. The subscription is optional. Source: Autom8Labs AI Insight July 2026, State of Open Source LLMs June 2026, Kunal Ganglani blog June 2026.
0:25

Alibaba just released a coding model that hits 82 percent on SWE-Bench Verified. That is the highest score ever published for an open-source model. The weights are free. The license is Apache 2.0. You can run it today. The model is Qwen 4 Coder 32B. Here is what 82 percent on SWE-Bench Verified actually means. SWE-Bench Verified tests whether an AI can autonomously resolve real bugs pulled from real production GitHub repositories. Not synthetic exercises. Real open-source projects that real teams depend on. A model gets a bug report, reads the code, writes a fix, and either passes the test suite or it does not. At 82 percent, Qwen 4 Coder 32B resolves 82 out of every 100 real production bugs it is given. Without a human guiding it. On code it has never seen before. For comparison: Qwen 4 Coder 32B: 82 percent SWE-Bench Verified. Open source. Apache 2.0. Claude Fable 5: 80.3 percent SWE-Bench Pro. $10 input / $50 output per million tokens. Currently suspended. GPT-5.6 Sol: Competitive on Terminal-Bench. $5 input / $30 output per million tokens. An open-weight model that you can download and run for free just beat both of them on the benchmark designed to measure real software engineering capability. Here is the architecture. Qwen 4 Coder 32B is a 32 billion parameter dense model. Not a Mixture-of-Experts. Every parameter is active on every request. This matters for inference: a dense 32B model runs on 22 gigabytes of VRAM, which fits on a single high-end consumer GPU or a MacBook Pro with 64GB of unified memory. The smaller variant, Qwen 4 Coder 4B, runs at approximately 135 tokens per second on an M5 Max and fits inside 8 gigabytes of RAM. For a model with usable coding capability, that is a new bar for what fits in a single laptop. The training methodology continued Alibaba's approach of reinforcement learning on verifiable coding tasks. The model gets rewarded when its code passes tests. It gets penalized when it fails. Over millions of training steps, the model learns to write code that actually runs rather than code that looks plausible. License: Apache 2.0. Full commercial use. No attribution requirement. No revenue threshold. No monthly active user ceiling. Weights: Hugging Face, available today. Runs on: vLLM, Ollama, SGLang, and any standard GGUF-compatible inference engine. Qwen 4 32B also runs at approximately 135 tokens per second on an M5 Max chip, setting a new bar for what a sub-8GB model can do on Apple Silicon. The open-source coding model just beat the best closed-source model in the world on the benchmark designed to test whether AI can actually do software engineering. The weights are free. The subscription is optional. Source: Autom8Labs AI Insight July 2026, State of Open Source LLMs June 2026, Kunal Ganglani blog June 2026.

Harman

41,179 görüntüleme • 25 gün önce

China just released an open source AI model that matches the best closed models from OpenAI and Anthropic. Gavin Baker explained exactly how they did it and the answer should concern every American AI lab. The model is called GLM 5.2. It was built by Z. AI. You get 744 billion parameters, 1 million token context window and its MIT license, meaning anyone can download it, fork it, build a company on it, with no restrictions and no Dario. It scored 51 points on the artificial analysis intelligence index. The highest score any open weight model has ever achieved. It beat GPT 5.5 on the frontier software engineering benchmark. It trails Claude Opus 4.8 by less than one percentage point. And it costs 85% less to run than GPT 5.5 for comparable performance. Gavin Baker said on the All-In podcast that this model has challenged some of his beliefs. Then he explained how China built it. The method is called distillation. Just think of tens of thousands of phones and computers running simultaneously, all hitting the frontier model APIs through masked accounts, asking specific questions, and harvesting what happens inside the model when it answers. Every reasoning step, every token. The entire thinking process gets recorded and fed back into the Chinese model during training. It is a cheat sheet. It is the answer key to the exam. And here is the part that should worry everyone. Sacks said it plainly. China was already nine months behind American models. But now that GLM 5.2 is good enough to run its own reinforcement learning, it can improve itself without needing to distill from American models anymore. The cheat sheet let them get close enough to start writing their own answers. Sacks said we are six months behind on the model and 24 months behind on silicon and they are only a few months behind in total. The Z. AI founder told Elon Musk directly that open weight fable-level capability will be here before Q1 2027. Every restriction Anthropic lobbied for, every self-imposed safety guardrail, every month of delay in releasing American frontier models accelerated this. The Chinese labs were not under those restrictions. They were not going to wait. The composable model future Gavin described, where every enterprise runs a frontier model alongside their own fine-tuned open weight model, is coming regardless of what American labs do next. The question is just whether the open weight half of that stack is American or Chinese. Right now it is Chinese. WATCH THE FULL PODCAST ON The All-In Podcast
3:21

China just released an open source AI model that matches the best closed models from OpenAI and Anthropic. Gavin Baker explained exactly how they did it and the answer should concern every American AI lab. The model is called GLM 5.2. It was built by Z. AI. You get 744 billion parameters, 1 million token context window and its MIT license, meaning anyone can download it, fork it, build a company on it, with no restrictions and no Dario. It scored 51 points on the artificial analysis intelligence index. The highest score any open weight model has ever achieved. It beat GPT 5.5 on the frontier software engineering benchmark. It trails Claude Opus 4.8 by less than one percentage point. And it costs 85% less to run than GPT 5.5 for comparable performance. Gavin Baker said on the All-In podcast that this model has challenged some of his beliefs. Then he explained how China built it. The method is called distillation. Just think of tens of thousands of phones and computers running simultaneously, all hitting the frontier model APIs through masked accounts, asking specific questions, and harvesting what happens inside the model when it answers. Every reasoning step, every token. The entire thinking process gets recorded and fed back into the Chinese model during training. It is a cheat sheet. It is the answer key to the exam. And here is the part that should worry everyone. Sacks said it plainly. China was already nine months behind American models. But now that GLM 5.2 is good enough to run its own reinforcement learning, it can improve itself without needing to distill from American models anymore. The cheat sheet let them get close enough to start writing their own answers. Sacks said we are six months behind on the model and 24 months behind on silicon and they are only a few months behind in total. The Z. AI founder told Elon Musk directly that open weight fable-level capability will be here before Q1 2027. Every restriction Anthropic lobbied for, every self-imposed safety guardrail, every month of delay in releasing American frontier models accelerated this. The Chinese labs were not under those restrictions. They were not going to wait. The composable model future Gavin described, where every enterprise runs a frontier model alongside their own fine-tuned open weight model, is coming regardless of what American labs do next. The question is just whether the open weight half of that stack is American or Chinese. Right now it is Chinese. WATCH THE FULL PODCAST ON The All-In Podcast

Ihtesham Ali

86,295 görüntüleme • 1 ay önce