ash retweeted
Day 25/
We are doubling all usage limits for all Pro 100/200/500 tiers and Business Premium, effective today.
We heard your kind feedback and won’t be reducing usage limits for Pro 200, so your Work and Codex usage will stay the same. We’re also going to continue offering extended limits for dots for now, and usage of your dot will still continue to be separate from your default usage.
And we'll of course also keep shipping better models and other efficiency improvements that increase your effective usage over time.
LFM3 is live in LM Studio!
Fits in about 1 GB of memory.
Model page: lmstudio.ai/models/lfm3
Introducing 𝙻𝙵𝙼𝟹: our new generation of Liquid Foundation Models. With a new tri-hybrid architecture and new multimodal encoders, the LFM3 family is the ideal model suite for specialized intelligence.
> 6 model instances, across text, audio, vision, and omni modalities, generative and decision models.
> 𝙻𝙵𝙼𝟹-𝟷.𝟽𝙱: text, 256k context window.
> 𝙻𝙵𝙼𝟹-𝚅𝙻-𝟸𝙱: vision-language model with video-input support for spatial understanding
> 𝙻𝙵𝙼𝟹-𝙰𝚞𝚍𝚒𝚘-𝟸𝙱: tool calls, voice chat, reasoning in 18 languages.
> 𝙻𝙵𝙼𝟹-𝙾𝚖𝚗𝚒-𝟸𝙱: an omni model combines vision, audio, and language.
> 𝚍𝟷-𝟸𝙱 and 𝚍𝟷-𝙾𝚖𝚗𝚒-𝟸𝙱: decision models with typed outputs and calibrated probabilities in a single pass. Omni adds audio input.
> fine-tune on 1 GPU.
> a new tri-hybrid architecture
> architecture optimized for 14 processor classes across GPUs, CPUs, and NPUs.
> 𝙻𝙵𝙼𝟹-𝚅𝙻-𝟸𝙱 is a beast. It performs competitively with Gemma 4 12B (6x larger), and Gemini 3.5 Flash Lite, and GPT-5.6 Luna, with 1.9B parameters.
> 𝙻𝙵𝙼𝟹-𝟷.𝟽𝙱 is #1 on the Pareto frontier of device intelligence 𝚙𝚒𝚙𝚎𝚝𝚝𝚎.𝚕𝚒𝚚𝚞𝚒𝚍.𝚊𝚒
Every modality for specialized intelligence. Pick the one that fits your use case, customize it, and run it on-device.
1/ 🧵
ash retweeted
🚀 Introducing Hy-Nomas: An Open Source Free-Form Interactive Video World Model
Key Features:
* Free-form interaction with text prompts and camera trajectories
* Long-horizon generation with world memory
* Lightweight LoRA adaptation for specialized domains such as robotics
* Optimized for Inference on Consumer GPUs
Test it and drop feedback anytime!
🔗 Website: hy-nomas.hy.tencent.com/
💻 GitHub:github.com/Tencent-Hunyuan/H…
🤗 Hugging Face: huggingface.co/tencent/Hy-No…
🎥 Demo: hy-nomas.hy.tencent.com/demo
#Hy#WorldModels #VideoGeneration #GenerativeAI
ash retweeted
We just launched OpenUSD support on the @huggingface Hub 🎉
Yesterday, @nvidiaomniverse put 2,500+ SimReady assets on the Hub. Forklifts, robot arms, engines, hospital equipment, all OpenUSD. You can also search the whole library in plain English
huggingface.co/spaces/nvidia…
huggingface.co/datasets/nvid…
Astraに手元のSO-101を操作させて「消しゴム拾って」って頼んでみた
消しゴム近くまではサッと動くのに、
グリッパーの位置と角度合わせで
ちょっと動いて止まるを繰り返してるの可愛い
16倍速(待ち時間もそのまま)
ash retweeted
【話題】中国、ロボットの学習データを世界に無償公開
・大会の準備・本番で集めた2500時間超の動作や失敗例
・工場や物流、飲食店など12分野、1万超の細かなタスクを収録
・世界の企業や研究機関によるAI開発への活用を想定
arduinoの概念変わったわ
The wait is over! Meet Arduino VENTUNO Q, where AI takes action.
💬 Run local LLMs like Qwen 3, Gemma 4, and Qwen 3 VLM directly on the board
🧠 NPU + CPU + GPU +MCU: @Qualcomm Dragonwing IQ-8275 with up to 40 dense TOPS of AI performance and STM32H5 microcontroller for real-time control
🗄️ 16 GB RAM + 64 GB eMMC + expandable storage
🪁 Linux-powered, pre-loaded with Ubuntu OS + Zephyr RTOS
🛠️ Build AI faster using Arduino App Lab, @huggingface, @EdgeImpulse, and Qualcomm AI Hub
💨 Move seamlessly from prototype to production through Works with Arduino Certification Program
The first batch won’t last. Pre-order your VENTUNO Q with a free power supply and USB-C cable included! Get ready to enter a new era of Physical AI: arduino.cc/product-ventuno-q
ash retweeted
Introducing GEN-1.5, a one-shot learner.
It can learn new tasks in a few seconds. Show it what to do, and it generalizes.
This capability emerged from pretraining on physical data at scale, as a step towards our mission of building general intelligence for the physical world.
GPT-5.6 Sol sets a new state of the art in cybersecurity on “The Last Ones” cyber range.
We’re already seeing that capability translate into defensive outcomes: helping teams find, validate, and fix vulnerabilities in real-world code.
Put it to work with Codex Security: openai.com/daybreak/codex-se…















