Sensitive content

This media may contain sensitive content.

ๆญฃๅœจๅŠ ่ฝฝ่ง†้ข‘...

่ง†้ข‘ๅŠ ่ฝฝๅคฑ่ดฅ

[Sneaky Chiku] teaser 2 Chiku model:๐Ÿ”žCryptia๐Ÿ”ž voice:Aini โ˜†๏ธ VA ๐ŸŽ™๏ธ Aak model@valorlynz voice:๐Ÿ”žRayTracingVA๐Ÿ•โšœ๏ธ | VA & EDITOR | COMMS OPEN!! SFX:OpenNSFW ๐ŸŸฃ Available Now -Introless, Full 3 minutes, HQ download and more animations on the wataa page in bio >:3-

50,858 ๆฌก่ง‚็œ‹ โ€ข 2 ไธชๆœˆๅ‰ โ€ขvia X (Twitter)

0 ๆก่ฏ„่ฎบ

ๆš‚ๆ— ่ฏ„่ฎบ

ๅŽŸๅง‹ๅธ–ๅญ็š„่ฏ„่ฎบๅฐ†ๆ˜พ็คบๅœจ่ฟ™้‡Œ

็›ธๅ…ณ่ง†้ข‘

Nvidia has just announced Alpamayo 2 Super, an open 34 billion parameter reasoning vision-language-action model designed to accelerate the development of autonomous vehicles. This new model combines the NVIDIA Cosmos 3 Super reasoning model with a 2 billion parameter diffusion-based action expert model, and is post trained with reinforcement learning. The model can return multiple outputs: future trajectory plans, reasoning traces, grounded answers to questions about the scenes, and auto label generation. The model weights are now available for anyone to download on Hugging Face, and the inference code has been posted to GitHub. Distilled models can be deployed commercially without any further permission from Nvidia, and model outputs carry no license conditions. Automakers can distill down a compact version of this model that can run on the Nvidia computer in the car. Major kudos to Nvidia and Jensen Huang for advancing the state of the industry by releasing this as an open model with permissive licensing. Jensen isn't just paying lip service to the idea of open models, Nvidia is actually contributing to the ecosystem โ€” and it's great for their business, because it helps sell more Thor computers that go in the car. Anyone can go download the model and play with it. If you do, let me know what you think. Personally I think it's so cool that we have open weights models that are this advanced, for anyone to download.

Whole Mars Catalog

45,595 ๆฌก่ง‚็œ‹ โ€ข 1 ไธชๆœˆๅ‰

๐—ฅ๐˜‚๐—ป ๐—š๐—ผ๐—ผ๐—ด๐—น๐—ฒ'๐˜€ ๐—š๐—ฒ๐—บ๐—บ๐—ฎ ๐Ÿฐ + ๐—ข๐—ฝ๐—ฒ๐—ป๐—–๐—น๐—ฎ๐˜„ ๐—ฎ๐˜€ ๐—ฎ ๐—ณ๐—ฟ๐—ฒ๐—ฒ ๐—ฝ๐—ฟ๐—ถ๐˜ƒ๐—ฎ๐˜๐—ฒ ๐—”๐—œ ๐—ฎ๐—ด๐—ฒ๐—ป๐˜ ๐—ผ๐—ป ๐˜†๐—ผ๐˜‚๐—ฟ ๐—ผ๐˜„๐—ป ๐—บ๐—ฎ๐—ฐ๐—ต๐—ถ๐—ป๐—ฒ ๐—ถ๐—ป ๐Ÿฏ ๐˜€๐˜๐—ฒ๐—ฝ๐˜€. No API bills. No usage limits. No subscription. Nothing leaves your computer. Here's the full setup: โ†’ Step 1: Go to Download and install. Update to version 0.2.2.0 or higher. โ†’ Step 2: Open terminal. Type: ollama pull gemma4. Downloads the model. Done. โ†’ Step 3: Install OpenClaw. Select Ollama as your provider. Point it at port 11434. Pick Gemma 4. That's it. Your AI agent is now running locally. Message it through Telegram, Slack, Discord, or WhatsApp like a coworker. Read files. Write code. Remember context across every conversation. All on your own hardware. Gemma 4 ranked number 3 on the global open model leaderboard on launch day. It beat models with 20 times more parameters. The 26B version activates only 4B parameters at a time so you get near large-model quality at small-model speed. Every AI subscription you're paying for right now could be replaced with this.

Julian Goldie SEO

36,898 ๆฌก่ง‚็œ‹ โ€ข 5 ไธชๆœˆๅ‰

Introducing PhoneLLM, an open model for voice agents. GPT 5.6 Terra performance on typical voice agent tasks at 1/3 the latency and 1/18 the cost. For voice agents, we need models that are both very low latency and very good at tool calling and instruction following. There's a trade-off here, and we often have to compromise on either latency or capability when building voice agents. With PhoneLLM (and the training and data stack that made this model possible) we're fixing this problem. For the last couple of years, most of the effort in frontier model development has gone towards leveraging test-time compute. Which is awesome! Models of all shapes and sizes are available that perform really, really well ... if you have "thinking" turned on for your model. But if you need your agent to respond at voice conversation speed, you can't use thinking models. PhoneLLM is a full-weights fine-tune of NVIDIA Nemotron Nano 30B. We trained on a wide range of real-world telephone and customer support use cases. The training focused on taking the excellent Nano 30B base capabilities and teaching the model to do typical voice agent tasks with thinking disabled. The results are really good: accurate tool calling and concise, on-topic responses in long conversations. And fast: TTFAT measured server-side is <100ms if you run PhoneLLM on a lightly loaded B200. :-) But seriously, when we characterize model latency, we do it with full, end-to-end, batched request simulations using real Pipecat voice agent pipelines. You can serve more than 80 concurrent agents on a single B200 with P95 end-to-end TTFAT <600ms. Including network overhead. That's an LLM cost-per-minute around $0.0025. (1/4 of a cent.) At a latency lower than any third-party API offers today. More details about this model, including weights on Hugging Face, how to spin it up with one click on Modal, and a starter project repo you can clone, are in the thread ...

kwindla

328,479 ๆฌก่ง‚็œ‹ โ€ข 16 ๅคฉๅ‰

HERMES AGENT BECOMES 10X MORE USEFUL WHEN YOU CONFIGURE THESE 5 THINGS. EACH ONE TAKES 5 MINUTES. MOST USERS NEVER TOUCH THEM. 1. THE RIGHT MODELS one model for everything = wrong model for most things. GPT-5.6 Sol: strongest reasoning. daily driver. access through your ChatGPT subscription (Plus or higher). Max plan unlocks higher reasoning effort. Grok 4.5: live X search. fastest responses. access through your X Premium+ subscription. "find me 3 high-engagement Hermes posts from the last 5 days." Grok pulls directly from X. no scraping. real-time. Kimi K3: design powerhouse. comparable quality to Claude Fable 5 at roughly 30% of the price. takes longer to generate. the quality justifies the wait. connect via Desktop app / Dashboard: Models โ†’ add provider. GPT-5.6: ChatGPT subscription โ†’ OAuth. Grok 4.5: X subscription โ†’ OAuth. Kimi K3: OpenRouter or Nous Portal. switch between them mid-session: /model [name] 2. PARALLEL TOOL CALLS Hermes used to call tools one at a time. Gmail, then calendar, then web search. sequential. now: multiple tool calls run simultaneously. "check my emails, check my calendar, tell me the weather in Dubai, and find the latest Hermes updates." four tools at once. results merge when all finish. what used to take 3 minutes takes 30 seconds. automatic after update. no config needed. hermes update 3. FASTER AND CHEAPER WEB SEARCH two improvements. one automatic, one you configure. AUTOMATIC (update only): v0.19.0 processes web pages differently. clean content straight to the agent without redundant processing steps. 60x faster. 49x cheaper. no config needed. CONFIGURE (Firecrawl): Firecrawl is the default scraping backend. strips HTML, ads, navigation, scripts. returns only the text your agent needs. 500 free credits per month on free tier. get your key from firecrawl .dev. add to .env: FIRECRAWL_API_KEY=your_key Nous Portal subscribers: Firecrawl is included through Tool Gateway. no separate key needed. SAVE MORE (auxiliary model): web summarization defaults to your main model. route it to a cheap model: auxiliary: web_extract: model: google/gemini-3-flash-preview cheap model reads the page. premium model reasons about the content. 4. MORNING BRIEF WITH EMAIL + CALENDAR connect Gmail and Google Calendar via MCP: 1. go to mcp .zapier.com 2. add Gmail: enable read and draft only. never enable send. one automated email from the wrong context can cost a relationship. 3. add Google Calendar: read access. 4. click connect โ†’ sign in โ†’ regenerate token 5. paste the token into Hermes chat tell your agent: "create a

YanXbt

29,620 ๆฌก่ง‚็œ‹ โ€ข 1 ไธชๆœˆๅ‰

๐—–๐—ต๐—ถ๐—ป๐—ฎ ๐—ถ๐˜€ ๐—ณ๐—ถ๐—ป๐—ถ๐˜€๐—ต๐—ถ๐—ป๐—ด ๐˜๐—ต๐—ฒ ๐—ต๐˜‚๐—บ๐—ฎ๐—ป๐—ผ๐—ถ๐—ฑ ๐—ฟ๐—ผ๐—ฏ๐—ผ๐˜ ๐—ฟ๐—ฎ๐—ฐ๐—ฒ ๐—ฏ๐—ฒ๐—ณ๐—ผ๐—ฟ๐—ฒ ๐—บ๐—ผ๐˜€๐˜ ๐—ผ๐—ณ ๐˜๐—ต๐—ฒ ๐—ช๐—ฒ๐˜€๐˜ ๐—ฟ๐—ฒ๐—ฎ๐—น๐—ถ๐˜‡๐—ฒ๐˜€ ๐—ถ๐˜ ๐—ต๐—ฎ๐˜€ ๐˜€๐˜๐—ฎ๐—ฟ๐˜๐—ฒ๐—ฑ. AGIBOT held its Partner Conference in Shanghai last week. The real headline wasn't the new hardware. It was their CTO standing on stage, telling investors that humanoid R&D season is over. 2026, he said, is "Deployment Year One." Not research. Not demos. Deployment into real factories, real warehouses, real stores. The manufacturing ramp is getting faster. 1,000 humanoid robots in the first 2 years. Another 4,000 in the next 12 months. Another 5,000 in just 3 months after that. AGIBOT is now shipping more humanoids per quarter than most US robotics companies have built in their entire existence. Then came the announcements the industry will spend the rest of the year reacting to. AIMA. The first full-stack open architecture for embodied AI. A unified robot operating system called Link-U, three dev platforms for motion, interaction, and task creation, plus an open agent framework. Any developer can build on top of it. This is the Android play for humanoids. GO-2. A vision-language-action foundation model with Action Chain-of-Thought reasoning. Planning and execution collapsed into one model. GE-2. A world model for simulation, strategy testing, and sim-to-real transfer. AGIBOT WORLD 2026. An open-source, production-grade real-world dataset pulled from actual industrial, logistics, hotel, and commercial sites. Seven standardized "productivity packages" covering logistics sorting, retail service, security patrol, commercial cleaning, and more. Plug, deploy, bill. A 5-year, $280 million commitment to seed a global developer and partner ecosystem. Now look at the competition. Boston Dynamics has been building humanoids since 1992. Tesla's Optimus is still climbing its own hype curve. Apptronik and Agility are well-funded but pre-scale on real deployments. AGIBOT has pulled all of this off in three years, with no acquisitions, no legacy platform, and no IPO distractions. While the West is still asking when humanoids will scale, China is already shipping them by the thousand.

Shruti

214,939 ๆฌก่ง‚็œ‹ โ€ข 4 ไธชๆœˆๅ‰