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OpenAI shows how gpt-oss can autonomously beat 2048 using reinforcement learning (RL). Training was done locally with Unsloth on NVIDIA DGX Spark. You can also do it free on Colab. 🦥 OpenAI DevDay notebook:

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Unsloth AI

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98,881 просмотров • 10 месяцев назад •via X (Twitter)

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We teamed up with NVIDIA and Matthew Berman to teach you how to do Reinforcement Learning! Learn about: - RL environments, reward functions & reward hacking - Training OpenAI gpt-oss to automatically solve 2048 - Local Windows training with NVIDIA_AI_PC RTX GPUs - How RLVR (verifiable rewards) works - How to interpret RL metrics like KL Divergence Full video tutorial:
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We teamed up with NVIDIA and Matthew Berman to teach you how to do Reinforcement Learning! Learn about: - RL environments, reward functions & reward hacking - Training OpenAI gpt-oss to automatically solve 2048 - Local Windows training with NVIDIA_AI_PC RTX GPUs - How RLVR (verifiable rewards) works - How to interpret RL metrics like KL Divergence Full video tutorial:

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"I don’t have a GPU" is no longer an excuse 🤯 You can now train LLMs directly in VS Code using a free Google Colab runtime. → Connect any fine-tuning notebook to Colab → Train locally or on a free cloud GPU → Works with Unsloth
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"I don’t have a GPU" is no longer an excuse 🤯 You can now train LLMs directly in VS Code using a free Google Colab runtime. → Connect any fine-tuning notebook to Colab → Train locally or on a free cloud GPU → Works with Unsloth

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86,321 просмотров • 6 месяцев назад

OpenAI has finally released GPT OSS 20B!! This is probably the most powerful model you can run locally on a laptop. → Only 3.6B active parameters → Adjustable "Reasoning Effort" → Works with 16GB of RAM! Quick steps to use it 100% free and offline:
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OpenAI has finally released GPT OSS 20B!! This is probably the most powerful model you can run locally on a laptop. → Only 3.6B active parameters → Adjustable "Reasoning Effort" → Works with 16GB of RAM! Quick steps to use it 100% free and offline:

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595,592 просмотров • 1 год назад

Unsloth AI and NVIDIA are Revolutionizing Local LLM Fine-Tuning: From RTX Desktops to DGX Spark Fine-tune popular AI models faster with Unsloth on NVIDIA RTX AI PCs such as GeForce RTX desktops and laptops to RTX PRO workstations and the new DGX Spark to build personalized assistants for coding, creative work, and complex agentic workflows. The landscape of modern AI is shifting. We are moving away from a total reliance on massive, generalized cloud models and entering the era of local, agentic AI. Whether it is tuning a chatbot to handle hyper-specific product support or building a personal assistant that manages intricate schedules, the potential for generative AI on local hardware is boundless. However, developers face a persistent bottleneck: How do you get a Small Language Model (SLM) to punch above its weight class and respond with high accuracy for specialized tasks? The answer is Fine-Tuning, and the tool of choice is Unsloth. Unsloth provides an easy and high-speed method to customize models. Optimized for efficient, low-memory training on NVIDIA GPUs, Unsloth scales effortlessly from GeForce RTX desktops and laptop all the way to the DGX Spark, the world’s smallest AI supercomputer...... Full analysis: NVIDIA NVIDIA AI NVIDIA AIDev NVIDIAnewsroom Unsloth AI Unsloth
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Unsloth AI and NVIDIA are Revolutionizing Local LLM Fine-Tuning: From RTX Desktops to DGX Spark Fine-tune popular AI models faster with Unsloth on NVIDIA RTX AI PCs such as GeForce RTX desktops and laptops to RTX PRO workstations and the new DGX Spark to build personalized assistants for coding, creative work, and complex agentic workflows. The landscape of modern AI is shifting. We are moving away from a total reliance on massive, generalized cloud models and entering the era of local, agentic AI. Whether it is tuning a chatbot to handle hyper-specific product support or building a personal assistant that manages intricate schedules, the potential for generative AI on local hardware is boundless. However, developers face a persistent bottleneck: How do you get a Small Language Model (SLM) to punch above its weight class and respond with high accuracy for specialized tasks? The answer is Fine-Tuning, and the tool of choice is Unsloth. Unsloth provides an easy and high-speed method to customize models. Optimized for efficient, low-memory training on NVIDIA GPUs, Unsloth scales effortlessly from GeForce RTX desktops and laptop all the way to the DGX Spark, the world’s smallest AI supercomputer...... Full analysis: NVIDIA NVIDIA AI NVIDIA AIDev NVIDIAnewsroom Unsloth AI Unsloth

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nvidia allows you to use many llm models on their website. to use it programatically you can either create a phone verified nvidia nim account (heavily limited, often slow and NOT AVAILABLE IN TURKEY) or my wrapper app which bypasses this measures. > how it works? - it spawns and invisible safari webview of nvidia page - it solves the captcha using js (because page uses really soft version of hCaptcha) - because it's easy, it can create a pool of tokens - then spawns a local openai-anthropic compatible proxy server on port 2289 so you can use it with any tool, locally.
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nvidia allows you to use many llm models on their website. to use it programatically you can either create a phone verified nvidia nim account (heavily limited, often slow and NOT AVAILABLE IN TURKEY) or my wrapper app which bypasses this measures. > how it works? - it spawns and invisible safari webview of nvidia page - it solves the captcha using js (because page uses really soft version of hCaptcha) - because it's easy, it can create a pool of tokens - then spawns a local openai-anthropic compatible proxy server on port 2289 so you can use it with any tool, locally.

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54,548 просмотров • 4 месяцев назад

How GPT-5 thinks, with OpenAI VP of Research Jerry Tworek 00:00 - Intro 01:01 - What Reasoning Actually Means in AI 02:32 - Chain of Thought: Models Thinking in Words 05:25 - How Models Decide How Long to Think 07:24 - Evolution from o1 to o3 to GPT-5 11:00 - The Road to OpenAI: Growing up in Poland, Dropping out of School, Trading 20:32 - Working on Robotics and Rubik's Cube Solving 23:02 - A Day in the Life: Talking to Researchers 24:06 - How Research Priorities Are Determined 26:53 - OpenAI's Culture of Transparency 29:32 - Balancing Research with Shipping Fast 31:52 - Using OpenAI's Own Tools Daily 32:43 - Pre-Training Plus RL: The Modern AI Stack 35:10 - Reinforcement Learning 101: Training Dogs 40:17 - The Evolution of Deep Reinforcement Learning 42:09 - When GPT-4 Seemed Underwhelming at First 45:39 - How RLHF Made GPT-4 Actually Useful 48:02 - Unsupervised vs Supervised Learning 49:59 - GRPO and How DeepSeek Accelerated US Research 53:05 - What It Takes to Scale Reinforcement Learning 55:36 - Agentic AI and Long-Horizon Thinking 59:19 - Alignment as an RL Problem 1:01:11 - Winning ICPC World Finals Without Specific Training 1:05:53 - Applying RL Beyond Math and Coding 1:09:15 - The Path from Here to AGI 1:12:23 - Pure RL vs Language Models
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Matt Turck

451,229 просмотров • 10 месяцев назад

BOOOOM! You can now run OpenAI gpt-oss 20B natively in Colaboratory T4 for FREE! 🔥 Powered by Transformers ⚡ The setup takes a bit since everything is bleeding edge, but once done it should work as expected Link to our cookbook in comments 👇
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BOOOOM! You can now run OpenAI gpt-oss 20B natively in Colaboratory T4 for FREE! 🔥 Powered by Transformers ⚡ The setup takes a bit since everything is bleeding edge, but once done it should work as expected Link to our cookbook in comments 👇

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Databricks is excited to partner with OpenAI on GPT-5.5, their latest frontier model. GPT-5.5 will be available in Unity AI Gateway on launch. You can use it with coding tools such as Codex, or to power your enterprise agents. GPT-5.5 is state-of-the-art on many benchmarks including OfficeQA Pro, our benchmark for evaluating grounded reasoning on enterprise tasks. We are partnering with OpenAI to co-launch on Databricks. Hear more from our co-founder Patrick Wendell and OpenAI CRO Denise Holland Dresser on GPT-5.5 in Databricks.
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Databricks is excited to partner with OpenAI on GPT-5.5, their latest frontier model. GPT-5.5 will be available in Unity AI Gateway on launch. You can use it with coding tools such as Codex, or to power your enterprise agents. GPT-5.5 is state-of-the-art on many benchmarks including OfficeQA Pro, our benchmark for evaluating grounded reasoning on enterprise tasks. We are partnering with OpenAI to co-launch on Databricks. Hear more from our co-founder Patrick Wendell and OpenAI CRO Denise Holland Dresser on GPT-5.5 in Databricks.

Databricks

12,707 просмотров • 4 месяцев назад

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.OpenAI GPT-5.5 is now available on Databricks, with Codex coding workflows and model inference fully governed through Unity AI Gateway. With GPT-5.5 on Databricks, you can: - Power coding workflows with Codex or other coding agents - Build custom agents grounded in enterprise data - Ask business questions in natural language from enterprise data with Genie - Automate document intelligence pipelines with Lakeflow Spark Declarative Pipelines Hear more from our co-founder, Patrick Wendell, and OpenAI CRO Denise Holland Dresser about how Databricks and OpenAI are bringing frontier AI to the enterprise. Get started today:

Databricks

63,207 просмотров • 3 месяцев назад

notes on my reinforcement learning for rocket league side quest so far: i’m in awe that — we live in a time where i can train a reinforcement learning model that is learning to play rocket league and at the same time, test community made rocket league models. where, both processes can run in parallel & locally on my hardware. in the game window — i’m playing against a reinforcement learning ppo model that’s running locally. and in the vscode window — i’m training my own reinforcement learning model (just a dummy example script for now). also, the rocket league botting ecosystem has incredible tooling where you can test out different reinforcement learning ideas against other algorithms + it has great documentation for linux and windows. it’s honestly a beautiful hidden gem of a rabbit hole :)
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notes on my reinforcement learning for rocket league side quest so far: i’m in awe that — we live in a time where i can train a reinforcement learning model that is learning to play rocket league and at the same time, test community made rocket league models. where, both processes can run in parallel & locally on my hardware. in the game window — i’m playing against a reinforcement learning ppo model that’s running locally. and in the vscode window — i’m training my own reinforcement learning model (just a dummy example script for now). also, the rocket league botting ecosystem has incredible tooling where you can test out different reinforcement learning ideas against other algorithms + it has great documentation for linux and windows. it’s honestly a beautiful hidden gem of a rabbit hole :)

naklecha

46,795 просмотров • 1 год назад

Spent the last few days vibe coding on my NVIDIA DGX Spark. Here's what I learned. Qwen 3.5 122B took one minute and nine seconds to respond "Hi how are you doing". Unusable for vibe coding. Gemma 4 was fast but built a dot instead of a first person shooter game. GPT-OSS 120B was the sweet spot. Fast, capable, and actually produced working HTML. Open source models running locally are not replacing Claude Opus 4.6 or Codex with GPT 5.4. Not even close. But they're getting better every month. The new DGX Spark Bench is live on Real-world benchmarks for local models on local hardware. This is just the start. Full video below.
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Spent the last few days vibe coding on my NVIDIA DGX Spark. Here's what I learned. Qwen 3.5 122B took one minute and nine seconds to respond "Hi how are you doing". Unusable for vibe coding. Gemma 4 was fast but built a dot instead of a first person shooter game. GPT-OSS 120B was the sweet spot. Fast, capable, and actually produced working HTML. Open source models running locally are not replacing Claude Opus 4.6 or Codex with GPT 5.4. Not even close. But they're getting better every month. The new DGX Spark Bench is live on Real-world benchmarks for local models on local hardware. This is just the start. Full video below.

BridgeMind

57,304 просмотров • 4 месяцев назад

At OpenAI DevDay, we introduced the Realtime API with a demo of an interactive solar system you can navigate with your voice. A lot of you have asked how it was built, so we've open-sourced it—with a twist: this version uses our new WebRTC integration. Have fun exploring! 🌍
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At OpenAI DevDay, we introduced the Realtime API with a demo of an interactive solar system you can navigate with your voice. A lot of you have asked how it was built, so we've open-sourced it—with a twist: this version uses our new WebRTC integration. Have fun exploring! 🌍

Katia Gil Guzman

316,627 просмотров • 1 год назад

OpenAI just released access to Computer Use Agent via an API. It combines GPT-4o vision with advanced reasoning for an AI Agent to simulate controlling computer interfaces and performing tasks just like humans. You can try it for free using this Agent Playground.
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OpenAI just released access to Computer Use Agent via an API. It combines GPT-4o vision with advanced reasoning for an AI Agent to simulate controlling computer interfaces and performing tasks just like humans. You can try it for free using this Agent Playground.

Shubham Saboo

64,206 просмотров • 1 год назад

A voice agent powered by gpt-oss. Running locally on my macBook. Demo recorded in a Waymo with WiFi turned off. I'm still on my space game voice AI kick, obviously. Code link below. For conversational voice AI, you want to set the gpt-oss reasoning behavior to "low". (The default is "medium".) Notes on how to do that and a jinja template you can use are in the repo. The LLM in the demo video is the big, 120B version of gpt-oss. You can use the smaller, 20B model for this, of course. But OpenAI really did a cool thing here designing the 120B model to run in "just" 80GB of VRAM. And the llama.cpp mlx inference is fast: ~250ms TTFT. Running a big model on-device feels like a time warp into the future of AI.
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A voice agent powered by gpt-oss. Running locally on my macBook. Demo recorded in a Waymo with WiFi turned off. I'm still on my space game voice AI kick, obviously. Code link below. For conversational voice AI, you want to set the gpt-oss reasoning behavior to "low". (The default is "medium".) Notes on how to do that and a jinja template you can use are in the repo. The LLM in the demo video is the big, 120B version of gpt-oss. You can use the smaller, 20B model for this, of course. But OpenAI really did a cool thing here designing the 120B model to run in "just" 80GB of VRAM. And the llama.cpp mlx inference is fast: ~250ms TTFT. Running a big model on-device feels like a time warp into the future of AI.

kwindla

202,211 просмотров • 1 год назад

We’re excited to partner with OpenAI to launch their new open source models natively on Databricks! gpt-oss sets a new standard of quality for open language models, supporting advanced reasoning with the transparency, flexibility and control enterprises need. Running on Databricks, the gpt-oss models connect securely to your data and scale with built-in governance, and expand what you can build and do with GenAI. Try both the 20B and 120B today in the Mosaic AI Playground.
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We’re excited to partner with OpenAI to launch their new open source models natively on Databricks! gpt-oss sets a new standard of quality for open language models, supporting advanced reasoning with the transparency, flexibility and control enterprises need. Running on Databricks, the gpt-oss models connect securely to your data and scale with built-in governance, and expand what you can build and do with GenAI. Try both the 20B and 120B today in the Mosaic AI Playground.

Databricks

10,132 просмотров • 1 год назад

OpenAI just announced "GPT-4o". It can reason with voice, vision, and text. The model is 2x faster, 50% cheaper, and has 5x higher rate limit than GPT-4 Turbo. It will be available for free users and via the API. The voice model can even pick up on emotion and generate emotive voice.
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OpenAI just announced "GPT-4o". It can reason with voice, vision, and text. The model is 2x faster, 50% cheaper, and has 5x higher rate limit than GPT-4 Turbo. It will be available for free users and via the API. The voice model can even pick up on emotion and generate emotive voice.

Lior Alexander

485,112 просмотров • 2 лет назад

WOW! OPENAI DID IT! They released their first TWO open weights models! This is HUGE news for the entire AI industry. It means you can RIGHT NOW run cutting edge AI models locally on your computer Here's all the benefits and how to set up the models locally yourself:
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WOW! OPENAI DID IT! They released their first TWO open weights models! This is HUGE news for the entire AI industry. It means you can RIGHT NOW run cutting edge AI models locally on your computer Here's all the benefits and how to set up the models locally yourself:

Alex Finn

71,875 просмотров • 1 год назад

A big milestone for AI on Windows: gpt‑oss‑20b is now available in Windows AI Foundry and Azure AI Foundry! You can now run this open-source, frontier-class model locally on a high-performance Windows PC. It’s fast, capable, and built for real-world use. Brought to life through collaboration across Windows, Azure, and OpenAI teams. We can’t wait to see what you create. 🚀
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A big milestone for AI on Windows: gpt‑oss‑20b is now available in Windows AI Foundry and Azure AI Foundry! You can now run this open-source, frontier-class model locally on a high-performance Windows PC. It’s fast, capable, and built for real-world use. Brought to life through collaboration across Windows, Azure, and OpenAI teams. We can’t wait to see what you create. 🚀

Pavan Davuluri

80,597 просмотров • 1 год назад

OpenAI engineer: "At OpenAI, 85% of our engineers are running hundreds of agents with Codex. The way you do it is graph engineering." In 30-minutes lecture, he explains how a single engineer can now do the work of an entire team, how far this has already gone inside OpenAI, and where it goes next. This is something you can't skip if you don't want to be left behind. Watch it, then read the full guide on graph engineering below.
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OpenAI engineer: "At OpenAI, 85% of our engineers are running hundreds of agents with Codex. The way you do it is graph engineering." In 30-minutes lecture, he explains how a single engineer can now do the work of an entire team, how far this has already gone inside OpenAI, and where it goes next. This is something you can't skip if you don't want to be left behind. Watch it, then read the full guide on graph engineering below.

Movez

203,004 просмотров • 13 дней назад

OpenAI Dev Day Just kicked off and it was the biggest day for AI since the launch of GPT-4 in April. Here's a 3 minute video with everything you need to know and a full summary: 1. GPT-4 Turbo is released. It is much better than GPT-4, can accept up to 128k characters and is 3x cheaper. The knowledge cut off is now April 2023 2. Text to Speech is also being released. They offer 6 hyper-realistic voice models that are the best I've heard from any other AI t-t-s software on the market. 3. Copyright Shield. OpenAI will actually defend your legal costs if you get sued for copyright infringement using their API! 4. GPTs. Maybe the most exciting IMHO, you can now create custom "GPTs" by training your own model of GPT and selling it on their store. This will create a massive shakeup of the current AI software landscape and is the first step towards autonomous agents.
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OpenAI Dev Day Just kicked off and it was the biggest day for AI since the launch of GPT-4 in April. Here's a 3 minute video with everything you need to know and a full summary: 1. GPT-4 Turbo is released. It is much better than GPT-4, can accept up to 128k characters and is 3x cheaper. The knowledge cut off is now April 2023 2. Text to Speech is also being released. They offer 6 hyper-realistic voice models that are the best I've heard from any other AI t-t-s software on the market. 3. Copyright Shield. OpenAI will actually defend your legal costs if you get sued for copyright infringement using their API! 4. GPTs. Maybe the most exciting IMHO, you can now create custom "GPTs" by training your own model of GPT and selling it on their store. This will create a massive shakeup of the current AI software landscape and is the first step towards autonomous agents.

Mark Gadala-Maria

79,177 просмотров • 2 лет назад