正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

Today we’re launching INTELLECT-2: The first decentralized 32B-parameter RL training run open to join for anyone with compute — fully permissionless. Scaling towards frontier reasoning across coding, math and science.

Prime Intellect

71,062 subscribers

353,791 次观看 • 1 年前 •via X (Twitter)

游戏科学技术教育

Anya Rossi• Live Now

Private livecam show

11 条评论

Prime Intellect 的头像

Prime Intellect1 年前

INTELLECT-2 brings decentralized training into the inference-time compute era: • Fully async, decentralized reinforcement learning • Eliminating communication overhead • Scalable across heterogeneous GPUs worldwide

Prime Intellect 的头像

Prime Intellect1 年前

Over the past months, we’ve built the full open-source stack to enable INTELLECT-2: • PRIME-RL: fully async decentralized RL • GENESYS & SYNTHETIC-1: crowdsourced tasks & verifiers for RL • TOPLOC validation: verifiable inference with low overhead • Protocol Testnet: global AI coordination infrastructure

Prime Intellect 的头像

Prime Intellect1 年前

How INTELLECT-2 operates: • Inference Rollout Workers: Decentralized swarm collects rollouts using the latest policy model • TOPLOC Validators: Verify the inference computations • GRPO Training Workers: Train on new data and broadcast weights via our shardcast library

Prime Intellect 的头像

Prime Intellect1 年前

Asynchronous RL completely eliminates communication bottlenecks. Our ablation studies confirm we maintain performance even with 4-step delays, making decentralized training viable with weak global interconnects.

Prime Intellect 的头像

Prime Intellect1 年前

With INTELLECT-2 we aim for frontier reasoning performance with a controllable thinking budget. By incorporating length rewards into our training run, users can specify how long the model should reason for a given task.

Prime Intellect 的头像

Prime Intellect1 年前

Contribute compute and watch training live on our dashboard: • Participate in our testnet powering an open reasoning model • Slashing and validation keep contributions honest Join us in building towards open and decentralized AGI

Lab4crypto 的头像

Lab4crypto1 年前

🚀 Don't gamble with your portfolio! Use our advanced hybrid quant risk tool using on/off-chain data and make informed decisions. 📈 Acess to 1000+ charts for your crypto journey. 📚Join our Premium Telegram for daily alerts. 📊+21 projects supported. 🏗️ Beginners and experts.

Michael Luo 的头像

Michael Luo1 年前

This is amazing work! Looks like asynchronous RL for LLMs is pretty stable 🤩, a paradigm shift away from traditional Deep RL where synchronous PPO won, as opposed to A3C and IMPALA

Tom Bennet 的头像

Tom Bennet1 年前

Decentralized RL training? Sounds like we're breeding digital superminds in a worldwide compute farm. Count me in for the chaos.

jesse.base.eth 的头像

jesse.base.eth1 年前

ok this is really sick

Burny — Effective Omni 的头像

Burny — Effective Omni1 年前

Decentralized open source is climbing

相关视频

Introducing SYNTHETIC-1: Collaboratively generating the largest synthetic dataset of verified reasoning traces for math, coding and science using DeepSeek-R1. Join us to contribute compute towards state-of-the-art open reasoning models.

Introducing SYNTHETIC-1: Collaboratively generating the largest synthetic dataset of verified reasoning traces for math, coding and science using DeepSeek-R1. Join us to contribute compute towards state-of-the-art open reasoning models.

Prime Intellect

198,473 次观看 • 1 年前

Launching SYNTHETIC-2: our next-gen open reasoning dataset and planetary-scale synthetic data generation run. Powered by our P2P inference stack and DeepSeek-R1-0528, it verifies traces for the hardest RL tasks. Contribute towards AGI via open, permissionless compute.

Launching SYNTHETIC-2: our next-gen open reasoning dataset and planetary-scale synthetic data generation run. Powered by our P2P inference stack and DeepSeek-R1-0528, it verifies traces for the hardest RL tasks. Contribute towards AGI via open, permissionless compute.

Prime Intellect

360,457 次观看 • 1 年前

Announcing INTELLECT-1: the first-ever decentralized training of a 10B model Scaling decentralized training 10x beyond prior efforts. Anyone can join us to build open-source AGI 🦋

Announcing INTELLECT-1: the first-ever decentralized training of a 10B model Scaling decentralized training 10x beyond prior efforts. Anyone can join us to build open-source AGI 🦋

Prime Intellect

790,053 次观看 • 1 年前

Introducing Cosmos 3: Our latest frontier model for Physical AI Cosmos 3 is the world’s first fully open omnimodel with native vision reasoning, world and action generation. Today we’re releasing Super (32B) and Nano (8B) variants.

Introducing Cosmos 3: Our latest frontier model for Physical AI Cosmos 3 is the world’s first fully open omnimodel with native vision reasoning, world and action generation. Today we’re releasing Super (32B) and Nano (8B) variants.

NVIDIA AI

423,606 次观看 • 1 个月前

Introducing INTELLECT-3: Scaling RL to a 100B+ MoE model on our end-to-end stack Achieving state-of-the-art performance for its size across math, code and reasoning Built using the same tools we put in your hands, from environments & evals, RL frameworks, sandboxes & more

Introducing INTELLECT-3: Scaling RL to a 100B+ MoE model on our end-to-end stack Achieving state-of-the-art performance for its size across math, code and reasoning Built using the same tools we put in your hands, from environments & evals, RL frameworks, sandboxes & more

Prime Intellect

1,142,730 次观看 • 7 个月前

$A crypto project actually trained a 72B parameter AI model from scratch using decentralized GPU compute. Not fine-tuned, not a wrapper: trained from zero. The model benchmarks competitively against Meta's LLaMA 3 on reasoning tasks, and the entire training run cost a fraction of what centralized labs spend. If decentralized compute can produce frontier-class models, the moat around OpenAI and Anthropic is thinner than people think.$

A crypto project actually trained a 72B parameter AI model from scratch using decentralized GPU compute. Not fine-tuned, not a wrapper: trained from zero. The model benchmarks competitively against Meta's LLaMA 3 on reasoning tasks, and the entire training run cost a fraction of what centralized labs spend. If decentralized compute can produce frontier-class models, the moat around OpenAI and Anthropic is thinner than people think.

VirtualBacon

40,543 次观看 • 3 个月前

1/3 The wait is finally over! Secure. Permissionless. Compute. Deploy enterprise-grade AI applications, run private LLMs, and access dedicated compute with one click. Open-source, decentralized, and completely under your control. Welcome to CLI! ☁️🌐 App: >_ $CMD

1/3 The wait is finally over! Secure. Permissionless. Compute. Deploy enterprise-grade AI applications, run private LLMs, and access dedicated compute with one click. Open-source, decentralized, and completely under your control. Welcome to CLI! ☁️🌐 App: >_ $CMD

CLI

33,613 次观看 • 1 年前

After coding is solved, the next frontier is computer use. Today, we are launching Use Computer, the infra for evaluating and training models to use all kinds of computers 👇

After coding is solved, the next frontier is computer use. Today, we are launching Use Computer, the infra for evaluating and training models to use all kinds of computers 👇

Marco Mascorro

44,641 次观看 • 1 个月前

We’re thrilled to announce that Gata Decentralized GPU Cloud is now LIVE! Start today → Built to accelerate the decentralization of the open AI economy, Gata enables anyone, anywhere to access decentralized GPU infrastructure, to build, train, and deploy AI models with full transparency and efficiency. GPU credits are now available for purchase directly with $GATA, creating a seamless bridge between compute and the decentralized economy.

We’re thrilled to announce that Gata Decentralized GPU Cloud is now LIVE! Start today → Built to accelerate the decentralization of the open AI economy, Gata enables anyone, anywhere to access decentralized GPU infrastructure, to build, train, and deploy AI models with full transparency and efficiency. GPU credits are now available for purchase directly with $GATA, creating a seamless bridge between compute and the decentralized economy.

Gata

48,232 次观看 • 8 个月前

We’re excited to share that 🥇Llama Nemotron Super 49B v1.5 -- our latest open reasoning model -- is now #1 on the Artificial Analysis Intelligence Index - a leaderboard that spans advanced math, science, and agentic tasks, in the 70B open model category. Llama Nemotron Super 49B v1.5 is trained with high-quality reasoning synthetic data generated from models like Qwen3-235B and DeepSeek R1. It delivers state-of-the-art accuracy and throughput, running on a single H100. Key features: 🎯 Leading accuracy on multi-step reasoning, math, coding, and function-calling 🏗️ Post-trained using RPO, DPO, and RLVR across 26M+ synthetic examples 📊 Fully transparent training data and techniques If you're building AI agents and want a high accuracy, fully-open, and transparent reasoning model that you can deploy anywhere, try Super v1.5 on or download from Hugging Face 🤗 ➡️ Leaderboard:

We’re excited to share that 🥇Llama Nemotron Super 49B v1.5 -- our latest open reasoning model -- is now #1 on the Artificial Analysis Intelligence Index - a leaderboard that spans advanced math, science, and agentic tasks, in the 70B open model category. Llama Nemotron Super 49B v1.5 is trained with high-quality reasoning synthetic data generated from models like Qwen3-235B and DeepSeek R1. It delivers state-of-the-art accuracy and throughput, running on a single H100. Key features: 🎯 Leading accuracy on multi-step reasoning, math, coding, and function-calling 🏗️ Post-trained using RPO, DPO, and RLVR across 26M+ synthetic examples 📊 Fully transparent training data and techniques If you're building AI agents and want a high accuracy, fully-open, and transparent reasoning model that you can deploy anywhere, try Super v1.5 on or download from Hugging Face 🤗 ➡️ Leaderboard:

NVIDIA AI Developer

100,506 次观看 • 11 个月前

Today we’re releasing K2 Think V2, our most capable open-source reasoning model to date. This is a fully sovereign model: trained end-to-end on IFM-curated and synthesized data, with complete transparency from pre-training through final reasoning alignment.

Today we’re releasing K2 Think V2, our most capable open-source reasoning model to date. This is a fully sovereign model: trained end-to-end on IFM-curated and synthesized data, with complete transparency from pre-training through final reasoning alignment.

MBZUAI

287,725 次观看 • 5 个月前

Demis Hassabis on the final frontier for AI in science 🧬 : it’s not just about solving the math, it’s about having the creativity to ask the question in the first place. While coding and math are verifiable and easier to automate, natural science requires a "missing ingredient" that we haven't fully cracked yet. "Coming up with the question in the first place or coming up with the theory or the hypothesis. I think that's much, much harder and I think that's the highest level of scientific creativity.”

Demis Hassabis on the final frontier for AI in science 🧬 : it’s not just about solving the math, it’s about having the creativity to ask the question in the first place. While coding and math are verifiable and easier to automate, natural science requires a "missing ingredient" that we haven't fully cracked yet. "Coming up with the question in the first place or coming up with the theory or the hypothesis. I think that's much, much harder and I think that's the highest level of scientific creativity.”

Chris

12,885 次观看 • 5 个月前

🚀 Big news! We’re launching Shinkai Desktop (Mac, Windows and Linux) today — the most user friendly App to run AI locally (free + open source!) and a Testnet with CoinList of the Shinkai Decentralized Network (Knowledge + Agents (very soon™️)). More 👇

🚀 Big news! We’re launching Shinkai Desktop (Mac, Windows and Linux) today — the most user friendly App to run AI locally (free + open source!) and a Testnet with CoinList of the Shinkai Decentralized Network (Knowledge + Agents (very soon™️)). More 👇

Shinkai: Local AI Agents

180,403 次观看 • 2 年前

🆕Scaling Test Time Compute to Multi-Agent Civilizations, with Noam Brown We're excited to publish our full conversation with Noam Brown on the frontiers of the new reasoning paradigm at OpenAI! - first principles for starting the "Multi-Agents" team - what's not captured by the "System 1/System 2" analogy for inference time compute - how Ilya Sutskever convinced him that reasoning was closer than he thought - Deep Research is existence proof that RL generalizes beyond verifiable rewards - the relationship between AI for imperfect information games (like Poker, Stratego, Diplomacy) and reasoning Enjoy! on youtube, or wherever fine podcasts are sold.

🆕Scaling Test Time Compute to Multi-Agent Civilizations, with Noam Brown We're excited to publish our full conversation with Noam Brown on the frontiers of the new reasoning paradigm at OpenAI! - first principles for starting the "Multi-Agents" team - what's not captured by the "System 1/System 2" analogy for inference time compute - how Ilya Sutskever convinced him that reasoning was closer than he thought - Deep Research is existence proof that RL generalizes beyond verifiable rewards - the relationship between AI for imperfect information games (like Poker, Stratego, Diplomacy) and reasoning Enjoy! on youtube, or wherever fine podcasts are sold.

Latent.Space

105,923 次观看 • 1 年前

Reasoning is central to purposeful action. Today we introduce MolmoAct — a fully open Action Reasoning Model (ARM) for robotics. Grounded in large-scale pre-training with action reasoning data, every predicted action is interpretable and user-steerable via visual trace. We are open-sourcing everything!

Reasoning is central to purposeful action. Today we introduce MolmoAct — a fully open Action Reasoning Model (ARM) for robotics. Grounded in large-scale pre-training with action reasoning data, every predicted action is interpretable and user-steerable via visual trace. We are open-sourcing everything!

Jiafei Duan

99,944 次观看 • 11 个月前

Inkling, Thinking Machines' first open model, dropped today: 975B total / 41B active MoE, up to 1M context, reasoning natively over text, images, and audio. Serving and RL support are already live: you can run and shape it on an open stack, starting now. Day 0 support on SGLang SGLang and Miles RadixArk👇 - Inkling's new architecture (ShortConv, attention with relative positional embedding, shared expert sink MoE) is natively implemented and deeply optimized, with prefill full CUDA graph and MXFP8 KV cache - Full parameter and LoRA RL in a customized Megatron backend, train inference consistency via customized kernels, routing replay, and cross-runtime parameter synchronization - DFlash speculative decoding from Modal for low-latency serving Launching now, blog and cookbook in the comments ⬇️

Inkling, Thinking Machines' first open model, dropped today: 975B total / 41B active MoE, up to 1M context, reasoning natively over text, images, and audio. Serving and RL support are already live: you can run and shape it on an open stack, starting now. Day 0 support on SGLang SGLang and Miles RadixArk👇 - Inkling's new architecture (ShortConv, attention with relative positional embedding, shared expert sink MoE) is natively implemented and deeply optimized, with prefill full CUDA graph and MXFP8 KV cache - Full parameter and LoRA RL in a customized Megatron backend, train inference consistency via customized kernels, routing replay, and cross-runtime parameter synchronization - DFlash speculative decoding from Modal for low-latency serving Launching now, blog and cookbook in the comments ⬇️

LMSYS Org

130,409 次观看 • 3 天前

China just broke the AI industry. Yesterday, Baidu open-sourced their Ernie 4.5. This 424 billion parameter model beats GPT-4o. And it's completely FREE to use. Here's how to get started: → Download from HuggingFace today → Choose Ernie-4.5-VL-424B for multimodal → Or Ernie-4.5-300B for text tasks → Run locally with enough compute → Access through Baidu's API too The model excels at: • Document analysis (93.1% DocVQA score) • Visual math reasoning (78.9% Math Vista) • Chart understanding (86.8% ChartQA) Save this video, you'll need it. Want the SOP? DM me. 💬

China just broke the AI industry. Yesterday, Baidu open-sourced their Ernie 4.5. This 424 billion parameter model beats GPT-4o. And it's completely FREE to use. Here's how to get started: → Download from HuggingFace today → Choose Ernie-4.5-VL-424B for multimodal → Or Ernie-4.5-300B for text tasks → Run locally with enough compute → Access through Baidu's API too The model excels at: • Document analysis (93.1% DocVQA score) • Visual math reasoning (78.9% Math Vista) • Chart understanding (86.8% ChartQA) Save this video, you'll need it. Want the SOP? DM me. 💬

Julian Goldie SEO

73,184 次观看 • 1 年前

Not every AI interaction is best served with a large frontier model. There is a long tail of trillion-token use cases, from tagging to search, best served by a sub-10b-parameter model that runs in milliseconds and costs many orders of magnitude less than the frontier. We built Freesolo Flash to make training loops like SFT and RL easy and end-to-end completable through your coding agent.

Not every AI interaction is best served with a large frontier model. There is a long tail of trillion-token use cases, from tagging to search, best served by a sub-10b-parameter model that runs in milliseconds and costs many orders of magnitude less than the frontier. We built Freesolo Flash to make training loops like SFT and RL easy and end-to-end completable through your coding agent.

Freesolo

24,215 次观看 • 1 天前

Your RL run just spiked at step 89! But, do you know why? We’re fixing that. Today we’re launching W&B Weave Traces to give you a step by step look into your agent’s decisions. This is the first drop from our fresh new integration with OpenPipe. More RL magic is incoming.

Your RL run just spiked at step 89! But, do you know why? We’re fixing that. Today we’re launching W&B Weave Traces to give you a step by step look into your agent’s decisions. This is the first drop from our fresh new integration with OpenPipe. More RL magic is incoming.

W&B Weave

290,258 次观看 • 10 个月前

Autonomys is a purpose-built blockchain for AI infrastructure—a vertically integrated stack for decentralized storage and compute. ⛓️ Consensus: Built with the Substrate framework (sovereign L1, not part of Polkadot), powered by Proof-of-Archival-Storage. 🟦 Domains Architecture: Our modular execution layer for compute. The first Domain, Auto EVM, launched in July—permissionless smart contracts are live today. 🗺️ Roadmap: Permissionless instantiation of Domains, allowing developers to launch custom environments tailored to specific AI functions. Designed before AI became fashionable, Autonomys delivers the foundation that decentralized AI truly needs. 👉 Learn more:

Autonomys is a purpose-built blockchain for AI infrastructure—a vertically integrated stack for decentralized storage and compute. ⛓️ Consensus: Built with the Substrate framework (sovereign L1, not part of Polkadot), powered by Proof-of-Archival-Storage. 🟦 Domains Architecture: Our modular execution layer for compute. The first Domain, Auto EVM, launched in July—permissionless smart contracts are live today. 🗺️ Roadmap: Permissionless instantiation of Domains, allowing developers to launch custom environments tailored to specific AI functions. Designed before AI became fashionable, Autonomys delivers the foundation that decentralized AI truly needs. 👉 Learn more:

Autonomys | AI3.0

152,990 次观看 • 9 个月前