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Introducing RL Environment Creator Skill Now any one can create RL environments $ npx skills add adithya-s-k/RL_Envs_101 > You can create environments across multiple frameworks like OpenEnv, OpenReward, Verifiers, NemoGym ... > the repo has live working examples of environments that your coding agent can reference > The skill...

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Adithya S K

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46,556 görüntüleme • 1 ay önce •via X (Twitter)

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A Severance Vision Pro Environment was featured in a WWDC25 developer session Don't expect it to make it to the Environment tab; it's just being used as a example for environments that sites can now provide via the web.
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🚨 New: Integrating Harbor (Harbor Framework) for end-to-end Computer-Use evaluation(for Windows and Linux) at scale with Thinking Machines' Tinker, OSWorld, Daytona, and bare-metal servers. We just added support for Computer Use, Tinker, and OSWorld to Harbor - a framework for evaluating agents and generating RL training data by running large-scale rollouts across parallel sandboxed environments and collecting trajectories for SFT and RL. Repo and blogpost below 👇
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🚨 New: Integrating Harbor (Harbor Framework) for end-to-end Computer-Use evaluation(for Windows and Linux) at scale with Thinking Machines' Tinker, OSWorld, Daytona, and bare-metal servers. We just added support for Computer Use, Tinker, and OSWorld to Harbor - a framework for evaluating agents and generating RL training data by running large-scale rollouts across parallel sandboxed environments and collecting trajectories for SFT and RL. Repo and blogpost below 👇

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Hi everyone! My class “A-Z of NPR 3D Environment in Blender” is now up for pre-order on Coloso! (Coloso Global) I will guide you through the essential skills in Blender and show you how to create stylized environments! Link: #coloso #Blender
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Hi everyone! My class “A-Z of NPR 3D Environment in Blender” is now up for pre-order on Coloso! (Coloso Global) I will guide you through the essential skills in Blender and show you how to create stylized environments! Link: #coloso #Blender

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Did you know that GlobalEye can monitor air, land and sea at the same time? By combining multiple sensors into a single platform, it creates a real-time view of the operational environment — even in complex or jamming environments. GlobalEye creates time to act.
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Did you know that GlobalEye can monitor air, land and sea at the same time? By combining multiple sensors into a single platform, it creates a real-time view of the operational environment — even in complex or jamming environments. GlobalEye creates time to act.

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Today we announced Workshop – a solution for launching sandboxed development environments in Ubuntu with a single command. Spend less time on configuring your environment: with just a few lines of YAML, you’ve got a reproducible environment you can use across machines. Find out how it works at:
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Today we announced Workshop – a solution for launching sandboxed development environments in Ubuntu with a single command. Spend less time on configuring your environment: with just a few lines of YAML, you’ve got a reproducible environment you can use across machines. Find out how it works at:

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if you're making 2D pixel art games for #vibejam this is solid. generate a sprite, create an end frame, prompt the animation between them worth checking. you can use with game creator skill design your game with placeholder wireframes using your agent, replace with final sprites later
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if you're making 2D pixel art games for #vibejam this is solid. generate a sprite, create an end frame, prompt the animation between them worth checking. you can use with game creator skill design your game with placeholder wireframes using your agent, replace with final sprites later

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LLM Artifacts Connected to Andrej Karpathy's LLM Knowledge base idea, I've been building out a fun way to generate dynamic artifacts from these knowledge bases with the goal of discovering and revealing meaningful and deeper insights. LLM KBs are hard to consume for humans, as I think they are more built for agents. So the question is, what form would be useful for humans to take actions and make important decisions? That's what I am trying to figure out with these artifacts. The artifact example shows a pulse on HN discussions around AI-related stories. The insights can go deeper, of course, but this is already super fun and thought-provoking, like some of my favorite podcasts. The format and depth matter a lot. The aggregation skills of agents are outstanding if you tune the prompts and skill carefully. I built this artifact generator in a few minutes through an agent skill, but I feel like there are so many ways that LLM-generated information can be used and consumed. Like generating deeper insights and analysis, and things that are just not feasible for humans today. The generated artifact (including its data and design) serves as reusable templates or can be updated in real-time via auomations, which is something I am also working on. It is truly an insane way to monitor and track information. Better than a newsletter. Better than newspapers. There is something about this that gets me really excited about the future of AI agents for knowledge generation and discovery. Lots of hidden gems everywhere just waiting to be discovered and acted on if the information is presented correctly. This is not perfect. The format, style/prose can be improved, but this is easy to customize via skill. You can personalize it to your liking. I feel like these dynamic artifacts are going to emerge as a strong new medium to stay on the cutting edge of things, both for agents and humans. My target is research, of course. This was just a basic example. Besides animation, I am also targeting other components like voice, videos, images, slides, etc. This space is full of opportunities to explore. Skill for this coming soon.

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that’s it. you only have to read this one article to: > learn claude skill foundations > learn claude skill architecture > learn claude skill testing > learn claude skill production which will let you create claude skills that: 1: automate your workflow’s 2: make you more productive 3: outperform your competitors welcome to the land of automation my claude cowork and claude code friends!
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that’s it. you only have to read this one article to: > learn claude skill foundations > learn claude skill architecture > learn claude skill testing > learn claude skill production which will let you create claude skills that: 1: automate your workflow’s 2: make you more productive 3: outperform your competitors welcome to the land of automation my claude cowork and claude code friends!

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Excited to announce AI Research Skills - an open-source library of 82 specialized skills for AI coding tools. One command gives your agent expert knowledge in: → Model training & fine-tuning (TRL, Unsloth ...) → Distributed systems (DeepSpeed, FSDP ...) → Inference optimization (vLLM, TensorRT ...) → Agent building ? (Langchain, AutoGPT ...) Works with Claude Code, Cursor, Gemini CLI, Windsurf, and Codex with one click interactive installation @ npx orchestra-research/ai-research-skills If you found the ML paper writing skill useful, check out the comprehensive collection

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🚨Current scalable RL algos train a policy w/o value func, which is limiting with learning in open-ended, non-stationary, dynamic environments. But, how to scale value-based RL with more data/compute is unclear... Not anymore: presenting scaling laws for value-based RL 🧵⬇️

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Out of sheer frustration ... I decided to vibe code my own tile map editor to see if it can help with making my agent skills be able to build better levels. It also proves that the agent skill is sufficiently good enough to know how to read the tilemaps - just bad at level design. So maybe I just need to build a level design skill.
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Out of sheer frustration ... I decided to vibe code my own tile map editor to see if it can help with making my agent skills be able to build better levels. It also proves that the agent skill is sufficiently good enough to know how to read the tilemaps - just bad at level design. So maybe I just need to build a level design skill.

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🔥🆙!! The 6AM group brought the HEAT on squats. Create an environment that PEOPLE want to be a part of.
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🔥🆙!! The 6AM group brought the HEAT on squats. Create an environment that PEOPLE want to be a part of.

Jake Riedel

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RL is painfully slow 😭 — bottlenecked by super-long CoT rollout. 🔭 Sparse attention should help, but naive sparse rollout hits a brutal efficiency–stability tradeoff: A tedious trial-and-error sparsity sweep for each dense policy is required before an actual RL run. 🐤Sparrow chirps no more pain! Introduce Sparrow: Sparse Rollout for stable and efficient long-context RL. Sparrow finds that: 💡As long as we keep the tail distribution mismatch throughout the sparse rollout above a critical threshold, the RL training will be stable. 💡Even cooler! Through comprehensive control studies of Qwen3-1.7B, 4B, 8B thinking models RL with 40K rollout max length, the critical threshold stays constant across model sizes. 💡Sparrow then finds the optimal dynamic sparse schedule to reach the threshold with minimal cost. 💡Sparrow's findings are empirically validated to generalize in Qwen3-14B, and hold on both Math and Coding RL. 🐤Sparrow empirically helps achieve 2.2× / 2.4× / 2.0× rollout speedup on Qwen3 1.7B / 4B / 8B thinking models, while keeping training stability over extended RL steps. We release the 🐤bird in the following formats. [1/n] Paper: Code: Blog:
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RL is painfully slow 😭 — bottlenecked by super-long CoT rollout. 🔭 Sparse attention should help, but naive sparse rollout hits a brutal efficiency–stability tradeoff: A tedious trial-and-error sparsity sweep for each dense policy is required before an actual RL run. 🐤Sparrow chirps no more pain! Introduce Sparrow: Sparse Rollout for stable and efficient long-context RL. Sparrow finds that: 💡As long as we keep the tail distribution mismatch throughout the sparse rollout above a critical threshold, the RL training will be stable. 💡Even cooler! Through comprehensive control studies of Qwen3-1.7B, 4B, 8B thinking models RL with 40K rollout max length, the critical threshold stays constant across model sizes. 💡Sparrow then finds the optimal dynamic sparse schedule to reach the threshold with minimal cost. 💡Sparrow's findings are empirically validated to generalize in Qwen3-14B, and hold on both Math and Coding RL. 🐤Sparrow empirically helps achieve 2.2× / 2.4× / 2.0× rollout speedup on Qwen3 1.7B / 4B / 8B thinking models, while keeping training stability over extended RL steps. We release the 🐤bird in the following formats. [1/n] Paper: Code: Blog:

Infini-AI-Lab

76,895 görüntüleme • 17 gün önce

The concept of creating an exact digital replica of the physical world has always fascinated me: environments that look and behave exactly like our everyday reality, precisely captured in the digital domain. This is the essence of 𝐖𝐨𝐫𝐥𝐝 𝐌𝐨𝐝𝐞𝐥𝐬, simulated realities indistinguishable from our own. Generating these models is the core mission behind what we are building at SpAItial AI. True World Models must capture both photorealistic appearance and underlying physics, spatially-consistent across the environment. For static scenes, current models already deliver impressive results, unlocking downstream applications from gaming to 3D design. However, the true frontier lies in modeling dynamics, which will enable the training of AI agents whose learned behaviors can bridge the sim-to-real gap, thus unlocking countless real-world applications.
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The concept of creating an exact digital replica of the physical world has always fascinated me: environments that look and behave exactly like our everyday reality, precisely captured in the digital domain. This is the essence of 𝐖𝐨𝐫𝐥𝐝 𝐌𝐨𝐝𝐞𝐥𝐬, simulated realities indistinguishable from our own. Generating these models is the core mission behind what we are building at SpAItial AI. True World Models must capture both photorealistic appearance and underlying physics, spatially-consistent across the environment. For static scenes, current models already deliver impressive results, unlocking downstream applications from gaming to 3D design. However, the true frontier lies in modeling dynamics, which will enable the training of AI agents whose learned behaviors can bridge the sim-to-real gap, thus unlocking countless real-world applications.

Matthias Niessner

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We are entering an extremely exciting era for open-weight models. Kimi K2.6 now feels like a top agentic model. I took it for a spin via Fireworks AI fast inference APIs. Kimi K2.6 has impressive agentic capabilities, design skills, and the ability to synthesize large amounts of information. I built a little Skill that produces survey papers on any AI research topic you want. (see example in the clip) You can use the skill to tell your agent to generate a survey on whatever topic and watch it go to work. The artifact was fully generated by Kimi.ai's Kimi K2.6. It's cheap and fast. Next step for me is to explore ways to continue integrating the capabilities of these models on use cases like automating my LLM knowledge bases and augmenting my agent memory capabilities. Stay tuned for more.
0:19

We are entering an extremely exciting era for open-weight models. Kimi K2.6 now feels like a top agentic model. I took it for a spin via Fireworks AI fast inference APIs. Kimi K2.6 has impressive agentic capabilities, design skills, and the ability to synthesize large amounts of information. I built a little Skill that produces survey papers on any AI research topic you want. (see example in the clip) You can use the skill to tell your agent to generate a survey on whatever topic and watch it go to work. The artifact was fully generated by Kimi.ai's Kimi K2.6. It's cheap and fast. Next step for me is to explore ways to continue integrating the capabilities of these models on use cases like automating my LLM knowledge bases and augmenting my agent memory capabilities. Stay tuned for more.

elvis

47,678 görüntüleme • 2 ay önce

Ukrainian children know what to do in the case of air alerts. In a normal world, this isn't a skill that children need. When you live next to an insane neighbor, such a habit can save you. Children deserve more reliable protection to sleep in peace:
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Ukrainian children know what to do in the case of air alerts. In a normal world, this isn't a skill that children need. When you live next to an insane neighbor, such a habit can save you. Children deserve more reliable protection to sleep in peace:

UNITED24

10,096 görüntüleme • 1 yıl önce

Over the past months, Cohort I of our RL Residency has been shipping. Highlights - continual learning - automating AI research (from GPU programming to RL itself) - embodied environments - multi-agent systems - materials science discovery
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Over the past months, Cohort I of our RL Residency has been shipping. Highlights - continual learning - automating AI research (from GPU programming to RL itself) - embodied environments - multi-agent systems - materials science discovery

Prime Intellect

59,409 görüntüleme • 1 ay önce