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。

An open source project turns any LLM into a 3D character that talks, moves, and reacts in the browser, no game engine, no local render setup. Characters have a memory system tracking emotional state and relationship history, so replies shift based on what's happened in the conversation so far,... not just the last message. Fully customizable: swap the 3D model, the personality prompt, the LLM, or the text-to-speech provider. Try it free with zero setup, a hosted version includes complimentary API access to get started. Self-hosting needs your own API keys but gives full control to modify it. From the team behind Digital Life Project (CVPR 2024), presented at SIGGRAPH Asia 2025. 100% Free. Open Source.show more

Simplifying AI

38,078 subscribers

59,324 次观看 • 2 天前 •via X (Twitter)

科学技术教育游戏

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

AI is smart enough now.. The problem is it keeps getting stuck. Ask it to host a website → it asks for API keys. Ask it to send an email → it needs a subscription. Ask it to scrape data → it wants an integration setup. At some point, YOU become the integration layer. I tested Zero and it changed that completely. I gave it one prompt, and it built a premium website, hosted it, and put it live automatically. Zero setup. Zero subscriptions. Zero API keys. All from a single prompt. Zero gives your AI access to 14,000+ real-world services on demand. It handles payments automatically. No billing. No signups. Nothing. Just prompt → outcome. First 10,000 users get $5 free to try it: Zero #ad

AI is smart enough now.. The problem is it keeps getting stuck. Ask it to host a website → it asks for API keys. Ask it to send an email → it needs a subscription. Ask it to scrape data → it wants an integration setup. At some point, YOU become the integration layer. I tested Zero and it changed that completely. I gave it one prompt, and it built a premium website, hosted it, and put it live automatically. Zero setup. Zero subscriptions. Zero API keys. All from a single prompt. Zero gives your AI access to 14,000+ real-world services on demand. It handles payments automatically. No billing. No signups. Nothing. Just prompt → outcome. First 10,000 users get $5 free to try it: Zero #ad

Rony

32,938 次观看 • 2 个月前

Kimi K3 is the most powerful open-source AI model ever, and you can use it 100% free right now. Go to Sign in. Switch the dropdown from K2.6 to K3. That's it. No credit card. No API setup. On my own tests, it beat GPT 5.6 and Opus 4.8. It builds games. 3D worlds. Full websites. Even videos. It goes fully open source in July 2026. Use it off-peak hours and you get even more free tokens. Most people will never even try it. The ones who do get frontier-level AI for $0.

Kimi K3 is the most powerful open-source AI model ever, and you can use it 100% free right now. Go to Sign in. Switch the dropdown from K2.6 to K3. That's it. No credit card. No API setup. On my own tests, it beat GPT 5.6 and Opus 4.8. It builds games. 3D worlds. Full websites. Even videos. It goes fully open source in July 2026. Use it off-peak hours and you get even more free tokens. Most people will never even try it. The ones who do get frontier-level AI for $0.

Julian Goldie SEO

145,482 次观看 • 1 个月前

We're thrilled to release & open-source Hunyuan3D World Model 1.0! This model enables you to generate immersive, explorable, and interactive 3D worlds from just a sentence or an image. It's the industry's first open-source 3D world generation model, compatible with CG pipelines for full editability & simulation. Set to transform game development, VR, digital content creation and so on. Get started now👇🏻 Project Page： Try it now： Github： Hugging Face：

We're thrilled to release & open-source Hunyuan3D World Model 1.0! This model enables you to generate immersive, explorable, and interactive 3D worlds from just a sentence or an image. It's the industry's first open-source 3D world generation model, compatible with CG pipelines for full editability & simulation. Set to transform game development, VR, digital content creation and so on. Get started now👇🏻 Project Page： Try it now： Github： Hugging Face：

Tencent Hy

1,230,802 次观看 • 1 年前

ComfyUI MCP server - A project from Pixelle AI Shoutout to Pixelle-MCP - an amazing open-source project that bridges ComfyUI with LLMs through the MCP protocol. Zero-code, talk to your LLM to iterate ComfyUI workflow! Highlights: - Full TISV (Text, Image, Sound/Speech, Video) support - Flexible deployment options - Easy setup with Docker or one-click scripts - Custom workflow tools in just a few steps 🧵👇

ComfyUI MCP server - A project from Pixelle AI Shoutout to Pixelle-MCP - an amazing open-source project that bridges ComfyUI with LLMs through the MCP protocol. Zero-code, talk to your LLM to iterate ComfyUI workflow! Highlights: - Full TISV (Text, Image, Sound/Speech, Video) support - Flexible deployment options - Easy setup with Docker or one-click scripts - Custom workflow tools in just a few steps 🧵👇

ComfyUI

27,949 次观看 • 1 年前

someone built a free open-source version of manus. no invite code needed. it's called OpenManus. built in 3 hours by researchers from metagpt. give it any task via terminal and it handles everything end to end: ✦ plans and reasons through the task ✦ browses the web autonomously ✦ uses tools and executes actions ✦ mcp support included ✦ works with any llm provider 100% free. open source.

someone built a free open-source version of manus. no invite code needed. it's called OpenManus. built in 3 hours by researchers from metagpt. give it any task via terminal and it handles everything end to end: ✦ plans and reasons through the task ✦ browses the web autonomously ✦ uses tools and executes actions ✦ mcp support included ✦ works with any llm provider 100% free. open source.

Oliver Prompts

57,549 次观看 • 1 个月前

AI is getting incredibly good. The problem is it still gets stuck whenever it needs to interact with the real world. Need to host a website? API keys. Need to send emails? Another service. Need to use external tools? More accounts and more setup. That's exactly why I wanted to try Zero. Zero gives Claude and ChatGPT access to **14,000+ real-world services**, so instead of stopping to ask for integrations, they can actually complete real tasks. I tested it by asking Cursor to build an AI healthcare startup. Within a single workflow it: → built and hosted a complete website → generated the assets it needed → emailed me the live URL → showed the total cost of the entire workflow No API keys. No juggling different services. No complicated setup. Just a prompt → a finished result. If you're building with Claude or ChatGPT, it's definitely worth trying. The first 10,000 users can claim $5 in free credits to get started: Try out now: #Ad

AI is getting incredibly good. The problem is it still gets stuck whenever it needs to interact with the real world. Need to host a website? API keys. Need to send emails? Another service. Need to use external tools? More accounts and more setup. That's exactly why I wanted to try Zero. Zero gives Claude and ChatGPT access to 14,000+ real-world services, so instead of stopping to ask for integrations, they can actually complete real tasks. I tested it by asking Cursor to build an AI healthcare startup. Within a single workflow it: → built and hosted a complete website → generated the assets it needed → emailed me the live URL → showed the total cost of the entire workflow No API keys. No juggling different services. No complicated setup. Just a prompt → a finished result. If you're building with Claude or ChatGPT, it's definitely worth trying. The first 10,000 users can claim $5 in free credits to get started: Try out now: #Ad

Abdullah AI

12,775 次观看 • 1 个月前

Introducing RAGApp 💫 A no-code interface to configure a RAG chatbot, as dead-simple as GPTs by OpenAI. It’s a docker container that’s easily deployable in any cloud infrastructure. Best of all, it’s fully open-source 🔥 1️⃣ Setup the LLM: Configure the model provider (OpenAI, Gemini) 2️⃣ Setup the data: Define the system prompt and upload your knowledge base. 3️⃣ Launch the chatbot both via the UI or API 4️⃣ If via the UI, stream intermediate events and also sources! This is fantastic work by Marcus Schiesser and is built upon the same DNA as our create-llama project. Check out RAGApp today:

Introducing RAGApp 💫 A no-code interface to configure a RAG chatbot, as dead-simple as GPTs by OpenAI. It’s a docker container that’s easily deployable in any cloud infrastructure. Best of all, it’s fully open-source 🔥 1️⃣ Setup the LLM: Configure the model provider (OpenAI, Gemini) 2️⃣ Setup the data: Define the system prompt and upload your knowledge base. 3️⃣ Launch the chatbot both via the UI or API 4️⃣ If via the UI, stream intermediate events and also sources! This is fantastic work by Marcus Schiesser and is built upon the same DNA as our create-llama project. Check out RAGApp today:

LlamaIndex 🦙

123,977 次观看 • 2 年前

I asked my AI to build and host a website for me. No hosting subscription. No domain setup. No manual deployment. Just a prompt. Here's the part that actually surprised me Claude found a live hosting service on its own, paid for it automatically, and handed me a working URL in minutes. That's Zero Zero It gives your AI access to 14,000 real-world services. Hosting, scrapers, image generators, email senders, all callable from a single prompt with zero setup. My AI can finally do real things in the real world. Get $5 free to start →

I asked my AI to build and host a website for me. No hosting subscription. No domain setup. No manual deployment. Just a prompt. Here's the part that actually surprised me Claude found a live hosting service on its own, paid for it automatically, and handed me a working URL in minutes. That's Zero Zero It gives your AI access to 14,000 real-world services. Hosting, scrapers, image generators, email senders, all callable from a single prompt with zero setup. My AI can finally do real things in the real world. Get $5 free to start →

ɱҽԃι✨

14,928 次观看 • 2 个月前

Anthropic won't like this open-source repo. It is going to cost LLM providers a lot of money. Every CI run of an AI app today sends real requests to providers like OpenAI or Anthropic. Like any other LLM call, this too gets billed at actual API rates. So for teams with high commit volumes, this accumulates into a meaningful chunk of API spend. One common hack devs use is that instead of invoking the LLM API, the test calls a fake local server that speaks the same API and returns a dummy response. The catch is that the dummy response is a copy of what the provider returned on the day it was saved, and providers keep adding fields and changing types. So the tests keep passing against a schema that's no longer valid, while the real integration breaks in production. A smart approach is now actually implemented in CopilotKit🪁's recently open-sourced aimock project. Every day, the repo's own CI sends a handful of requests to the real API and the same requests to the fake server, then compares both against the official client library's type definitions. Those are the only real API calls in the whole setup, and they run on the repo's own keys, not in anyone else's CI. A single team can push hundreds of commits a day, and thousands of teams are already doing that with coding agents. All of those runs stay offline, because one repo checks against the real API on everyone's behalf. When a check fails, a coding agent updates aimock's built-in response schema, the full test suite has to pass, and a patch version ships to npm. By simply upgrading the package, the corrected schema gets reflected in every project using it. The capability is not just limited to a single provider. The same server works for Claude, OpenAI, Gemini, Bedrock, Azure, Ollama, plus MCP tools, A2A agents, AG-UI event streams, vector DBs like Pinecone and Qdrant, and search, speech, image, and video endpoints. Here's the repo: (don't forget to star it ⭐) That said, mocking your API calls is one thing. AI engineers should also know how to test agents properly in the first place, which several teams still skip. I wrote a full walkthrough on that, covering build, testing, evals, tracing, and deployment. Read it below.

Anthropic won't like this open-source repo. It is going to cost LLM providers a lot of money. Every CI run of an AI app today sends real requests to providers like OpenAI or Anthropic. Like any other LLM call, this too gets billed at actual API rates. So for teams with high commit volumes, this accumulates into a meaningful chunk of API spend. One common hack devs use is that instead of invoking the LLM API, the test calls a fake local server that speaks the same API and returns a dummy response. The catch is that the dummy response is a copy of what the provider returned on the day it was saved, and providers keep adding fields and changing types. So the tests keep passing against a schema that's no longer valid, while the real integration breaks in production. A smart approach is now actually implemented in CopilotKit🪁's recently open-sourced aimock project. Every day, the repo's own CI sends a handful of requests to the real API and the same requests to the fake server, then compares both against the official client library's type definitions. Those are the only real API calls in the whole setup, and they run on the repo's own keys, not in anyone else's CI. A single team can push hundreds of commits a day, and thousands of teams are already doing that with coding agents. All of those runs stay offline, because one repo checks against the real API on everyone's behalf. When a check fails, a coding agent updates aimock's built-in response schema, the full test suite has to pass, and a patch version ships to npm. By simply upgrading the package, the corrected schema gets reflected in every project using it. The capability is not just limited to a single provider. The same server works for Claude, OpenAI, Gemini, Bedrock, Azure, Ollama, plus MCP tools, A2A agents, AG-UI event streams, vector DBs like Pinecone and Qdrant, and search, speech, image, and video endpoints. Here's the repo: (don't forget to star it ⭐) That said, mocking your API calls is one thing. AI engineers should also know how to test agents properly in the first place, which several teams still skip. I wrote a full walkthrough on that, covering build, testing, evals, tracing, and deployment. Read it below.

Akshay 🚀

62,821 次观看 • 13 天前

Introducing OpenVenice — an open-source, customizable frontend for Venice. Your API key stays in your browser, talks directly to Venice. No server, no backend. - Chat, image gen, audio, music, video, embeddings — everything venice offers in one clean UI - Visual workflows — chain models together (vision → LLM → image gen -> video gen). Venice is multimodal so you can build some really powerful workflows - Full control over every model parameter - Runs locally, deploys anywhere — zero infrastructure I'm a $DIEM holder and heavy Venice user. The models are solid and website is great but I kept wanting more freedom with the UX — more control, custom tools, being able to give it access to my local computer, multimodal chaining -- something I could shape to how I actually work. Didn't exist, so I built it. Feel free to fork and make it yours. Open source, MIT licensed.

Introducing OpenVenice — an open-source, customizable frontend for Venice. Your API key stays in your browser, talks directly to Venice. No server, no backend. - Chat, image gen, audio, music, video, embeddings — everything venice offers in one clean UI - Visual workflows — chain models together (vision → LLM → image gen -> video gen). Venice is multimodal so you can build some really powerful workflows - Full control over every model parameter - Runs locally, deploys anywhere — zero infrastructure I'm a $DIEM holder and heavy Venice user. The models are solid and website is great but I kept wanting more freedom with the UX — more control, custom tools, being able to give it access to my local computer, multimodal chaining -- something I could shape to how I actually work. Didn't exist, so I built it. Feel free to fork and make it yours. Open source, MIT licensed.

nikshep

40,500 次观看 • 5 个月前

Viggle’s Mic 2.0 is here! With our upgraded model, take precise control over how a character talks and moves, in one shot. Turn images into videos simply with an audio or text prompt for speech. Or take it further—add a motion source to drive the character’s movements—action and voice, perfectly aligned. Try it free on our web, or on our iOS/Android apps.👇

Viggle’s Mic 2.0 is here! With our upgraded model, take precise control over how a character talks and moves, in one shot. Turn images into videos simply with an audio or text prompt for speech. Or take it further—add a motion source to drive the character’s movements—action and voice, perfectly aligned. Try it free on our web, or on our iOS/Android apps.👇

ViggleAI

36,121 次观看 • 1 年前

Someone paid $6,000 (!) to get OpenClaw setup. So I built a free, open-source alternative: > OpenClaw Operator It's an agent skill + AGENTS.md/CLAUDE.md file that gives Codex/Claude Code the playbooks + validation flow needed to configure your local OpenClaw install. You open your OpenClaw repo/workspace in your coding agent and say things like: - “set up a cron job” - “create a custom skill” - “fix my provider config” - “troubleshoot this install and validate it” Nothing magical. Uses context from the OpenClaw open-source repo + docs to provide an effective skill. Includes: - SKILL.md - AGENTS.md/CLAUDE.md - validation checklist - task playbooks Free and open source. Contributions welcome. Demo below. Repo in reply.

Someone paid $6,000 (!) to get OpenClaw setup. So I built a free, open-source alternative: > OpenClaw Operator It's an agent skill + AGENTS.md/CLAUDE.md file that gives Codex/Claude Code the playbooks + validation flow needed to configure your local OpenClaw install. You open your OpenClaw repo/workspace in your coding agent and say things like: - “set up a cron job” - “create a custom skill” - “fix my provider config” - “troubleshoot this install and validate it” Nothing magical. Uses context from the OpenClaw open-source repo + docs to provide an effective skill. Includes: - SKILL.md - AGENTS.md/CLAUDE.md - validation checklist - task playbooks Free and open source. Contributions welcome. Demo below. Repo in reply.

Dan McAteer

17,809 次观看 • 5 个月前

Your AI agent is useless once it needs to interact with the real world. Need email sending? Website hosting? Data scraping? That usually means: → API keys → subscriptions → integrations → hours of setup I gave my AI agent access to Zero, and it built + hosted personalized landing pages automatically without me configuring anything. Zero gives AI agents access to 14,000+ real-world services with no API keys or subscriptions. The coolest part? Everything runs on pay-per-use microtransactions, so you only pay for what you use. If you're building agents, this is worth trying. Get $5 free credit at 👉

Your AI agent is useless once it needs to interact with the real world. Need email sending? Website hosting? Data scraping? That usually means: → API keys → subscriptions → integrations → hours of setup I gave my AI agent access to Zero, and it built + hosted personalized landing pages automatically without me configuring anything. Zero gives AI agents access to 14,000+ real-world services with no API keys or subscriptions. The coolest part? Everything runs on pay-per-use microtransactions, so you only pay for what you use. If you're building agents, this is worth trying. Get $5 free credit at 👉

Toha Khan

86,826 次观看 • 2 个月前

GeoLibre v1.10.0 is here! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. This release brings photorealistic city-scale 3D to the map, adds OGC API vector tiles, and makes vector tiles and live editing easier to work with. What's new in v1.10.0 - Google Photorealistic 3D Tiles: drape entire cities in photorealistic 3D right in the map, streamed and rendered through - ArcGIS I3S scene layers: stream Integrated Mesh and 3D Object scene layers and render them in 3D on the shared instance. - OGC API vector tiles: add standards-based OGC API - Tiles vector tile services as a remote source, right alongside XYZ and ArcGIS vector tiles. - Local HDF5 and NetCDF-4 loading: open scientific HDF5 and NetCDF-4 files straight from disk, no cloud references required. - GeoEditor from the current view: pull the vector features currently visible in the map into the GeoEditor and start editing what you are looking at, without re-importing the source data. Try it out - Launch GeoLibre Web: - GitHub: - Documentation: - Release notes: #GIS #Geospatial #OpenSource #RemoteSensing #DataVisualization #MapLibre

GeoLibre v1.10.0 is here! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. This release brings photorealistic city-scale 3D to the map, adds OGC API vector tiles, and makes vector tiles and live editing easier to work with. What's new in v1.10.0 - Google Photorealistic 3D Tiles: drape entire cities in photorealistic 3D right in the map, streamed and rendered through - ArcGIS I3S scene layers: stream Integrated Mesh and 3D Object scene layers and render them in 3D on the shared instance. - OGC API vector tiles: add standards-based OGC API - Tiles vector tile services as a remote source, right alongside XYZ and ArcGIS vector tiles. - Local HDF5 and NetCDF-4 loading: open scientific HDF5 and NetCDF-4 files straight from disk, no cloud references required. - GeoEditor from the current view: pull the vector features currently visible in the map into the GeoEditor and start editing what you are looking at, without re-importing the source data. Try it out - Launch GeoLibre Web: - GitHub: - Documentation: - Release notes: #GIS #Geospatial #OpenSource #RemoteSensing #DataVisualization #MapLibre

Qiusheng Wu

24,578 次观看 • 1 个月前

I just found a way to use Claude Code completely free. Claude Code is Anthropic’s terminal coding agent that usually needs a paid API key to run. But a viral GitHub project called Free Claude Code, now sitting at 37k stars, lets you skip the billing entirely. It works as a tiny proxy that sits between Claude Code and free model providers like NVIDIA NIM, OpenRouter, DeepSeek, and Gemini. Every request Claude Code would send to Anthropic gets quietly rerouted to a free model on the other side. The interface stays the same. What’s actually thinking behind it changes. Setup takes a couple of quick commands and a free API key from NVIDIA NIM or OpenRouter. Paste it into the local dashboard, pick a model, and you’re building. The catch is you’re not really using Claude anymore. But when the code ships, does the model badge matter? -- I have shared the Github Link in my free Whatsapp Community ↓

I just found a way to use Claude Code completely free. Claude Code is Anthropic’s terminal coding agent that usually needs a paid API key to run. But a viral GitHub project called Free Claude Code, now sitting at 37k stars, lets you skip the billing entirely. It works as a tiny proxy that sits between Claude Code and free model providers like NVIDIA NIM, OpenRouter, DeepSeek, and Gemini. Every request Claude Code would send to Anthropic gets quietly rerouted to a free model on the other side. The interface stays the same. What’s actually thinking behind it changes. Setup takes a couple of quick commands and a free API key from NVIDIA NIM or OpenRouter. Paste it into the local dashboard, pick a model, and you’re building. The catch is you’re not really using Claude anymore. But when the code ships, does the model badge matter? -- I have shared the Github Link in my free Whatsapp Community ↓

Vaibhav Sisinty

36,892 次观看 • 2 个月前

Running OpenClaw yourself is a pain. You need your own server, your own API keys, handle the deployment, and if something breaks you figure it out alone. Most people just don't bother. MiniMax launched MaxClaw to solve exactly that. It's OpenClaw, fully hosted in the cloud. No server. No API setup. Nothing to configure. I deployed mine in under 2 minutes. Told it to connect to Telegram, it walked me through the whole thing and I built a full website directly from the chat. Watch 👇

Running OpenClaw yourself is a pain. You need your own server, your own API keys, handle the deployment, and if something breaks you figure it out alone. Most people just don't bother. MiniMax launched MaxClaw to solve exactly that. It's OpenClaw, fully hosted in the cloud. No server. No API setup. Nothing to configure. I deployed mine in under 2 minutes. Told it to connect to Telegram, it walked me through the whole thing and I built a full website directly from the chat. Watch 👇

AshutoshShrivastava

17,696 次观看 • 6 个月前

Mureka vs. Suno Suno might be a popular choice, but gives you way more control and creative flexibility. With Mureka, you can: • Use audio as a prompt, not just text • Keep the vocals consistent throughout your track • Train your own custom model • Access an open API to build or connect it with other tools

Mureka vs. Suno Suno might be a popular choice, but gives you way more control and creative flexibility. With Mureka, you can: • Use audio as a prompt, not just text • Keep the vocals consistent throughout your track • Train your own custom model • Access an open API to build or connect it with other tools

Nelly;

29,435 次观看 • 1 年前

Finally, a proper chat UI for Hermes Agent (open-source)! Hermes ships an official dashboard, but it's primarily built for management, and its chat is just a terminal piped into a browser tab. Hermes Web UI is an open-source chat-first alternative. It's self-hosted and points at your existing ~/.hermes state, so there's nothing new to configure. - It's a native web chat, not a terminal in a tab - Sessions group by date with a context ring - Kanban renders the agent's task board - Spaces manages your workspaces - Skills panel lists the full catalog - Tasks panel shows cron jobs - Insights show usage and activity - Memory shows MEMORY and SOUL files - Logs tails the agent, gateway, and error logs The whole setup runs 100% locally, binds to localhost by default, and you reach it over an SSH tunnel or Tailscale from your phone. I have shared the Hermes Web UI GitHub repo in the replies. Do note that it's a community project, not official, so expect occasional rough edges (concurrent profile runs are blocked for now). To dive deeper into Hermes Agent, my co-founder wrote a full masterclass about it, covering the learning loop, the memory tiers, self-evolving skills, GEPA, and running multiple isolated agents. Read it below.

Avi Chawla

77,966 次观看 • 3 个月前

HERMES JUST GOT A CHATGPT INTERFACE AND IT IS COMPLETELY FREE. No terminal. No command line. No technical setup that takes half a day to figure out. Here is what just became possible. You can now run Hermes, DeepSeek, Ollama, and OpenClaw from a single clean chat interface. Switch between them in one click. Upload files directly. Attach knowledge bases and notes. Preview code without touching the terminal once. Use it on mobile. Make voice and video calls. All of it. Free. Open source. The setup took one conversation with Hermes itself. Pasted the GitHub link in. Hermes installed Open Web UI in Docker on its own. Connected the API server and gateway automatically. A clean ChatGPT-level interface running entirely on local hardware was live in minutes. No subscription. No data leaving your machine. No API bill at the end of the month. The people who set this up this weekend will have a local AI stack that rivals what most companies are paying $2,000 a month for in cloud infrastructure. The people who wait will keep paying for tools that send their data somewhere they cannot see. Both tools are free. Both are open source. The only thing between you and this setup is the next 30 minutes. Follow CyrilXBT for the exact config, setup steps, and local AI workflows I use to run a full stack without spending a dollar on cloud inference.

HERMES JUST GOT A CHATGPT INTERFACE AND IT IS COMPLETELY FREE. No terminal. No command line. No technical setup that takes half a day to figure out. Here is what just became possible. You can now run Hermes, DeepSeek, Ollama, and OpenClaw from a single clean chat interface. Switch between them in one click. Upload files directly. Attach knowledge bases and notes. Preview code without touching the terminal once. Use it on mobile. Make voice and video calls. All of it. Free. Open source. The setup took one conversation with Hermes itself. Pasted the GitHub link in. Hermes installed Open Web UI in Docker on its own. Connected the API server and gateway automatically. A clean ChatGPT-level interface running entirely on local hardware was live in minutes. No subscription. No data leaving your machine. No API bill at the end of the month. The people who set this up this weekend will have a local AI stack that rivals what most companies are paying $2,000 a month for in cloud infrastructure. The people who wait will keep paying for tools that send their data somewhere they cannot see. Both tools are free. Both are open source. The only thing between you and this setup is the next 30 minutes. Follow CyrilXBT for the exact config, setup steps, and local AI workflows I use to run a full stack without spending a dollar on cloud inference.

CyrilXBT

37,120 次观看 • 4 个月前

2D is what the camera sees.👀 3D is what the world is. 🌍 Today, we’re proudly open-sourcing QuerySplat — an open-source feed-forward 3D model that turns a few unposed images into a navigable 3D scene in seconds (run on 4090🪶). Your input: a few unposed images Our output: a sharp, navigable 3D scene — generated in seconds! 🚀 🧠 organize scenes with 3D queries, not pixel-bound Gaussians 📷 no camera poses or manual calibration required ⚡ reconstruct new scenes in a single forward pass ✨ preserve sharp geometry and high-frequency appearance 🏆 achieve state-of-the-art results on DL3DV-Evaluation 🔓 code and model weights are now open-source From pixels to scenes, we are making 3D generation scalable. Try our free iOS app — it’s a lot of fun! 😆 🔗 Try it on the Web: 🔗 Paper: 🔗 Code & weights: 🔗 Project page: 🔗 #AIGC #3DGS #AI #Computervision #3D #artist #3dartist #3d

2D is what the camera sees.👀 3D is what the world is. 🌍 Today, we’re proudly open-sourcing QuerySplat — an open-source feed-forward 3D model that turns a few unposed images into a navigable 3D scene in seconds (run on 4090🪶). Your input: a few unposed images Our output: a sharp, navigable 3D scene — generated in seconds! 🚀 🧠 organize scenes with 3D queries, not pixel-bound Gaussians 📷 no camera poses or manual calibration required ⚡ reconstruct new scenes in a single forward pass ✨ preserve sharp geometry and high-frequency appearance 🏆 achieve state-of-the-art results on DL3DV-Evaluation 🔓 code and model weights are now open-source From pixels to scenes, we are making 3D generation scalable. Try our free iOS app — it’s a lot of fun! 😆 🔗 Try it on the Web: 🔗 Paper: 🔗 Code & weights: 🔗 Project page: 🔗 #AIGC #3DGS #AI #Computervision #3D #artist #3dartist #3d

InSpatio｜影溯

29,524 次观看 • 27 天前