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We just launched the first MCP server that lets Claude by Anthropic rent GPUs and run workloads fully autonomously. Repo: Claude can now discover available GPUs on Hyperbolic, rent an H100, SSH into the instance, run commands like 𝚗𝚟𝚒𝚍𝚒𝚊-𝚜𝚖𝚒, and terminate the instance when it's done. Download models, run... show more

Hyperbolic

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41,291 views • 1 year ago •via X (Twitter)

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Hyperbolic1 year ago

Get started with step-by-step setup instructions in the repo:

Hyperbolic1 year ago

Find the cheapest compute, including H100s GPUs starting at $0.99/hr: Shoutout to @theamrelhady for the demo.

Investors.com1 year ago

The 4% Rule For Retirement Gets An Update. Here's The New Formula.

ODbeke (Ø,G)1 year ago

This is a groundbreaking step! Enabling Claude by @AnthropicAI to autonomously rent GPUs and manage workloads on your MCP server showcases the future of AI driven cloud computing. The TypeScript integration hints at a robust, error resistant framework, impressive work on scalability and efficiency! How do you see this evolving for broader AI applications?

kira_simonn1 year ago

@AnthropicAI Congratulations 🎊

CD III1 year ago

@AnthropicAI this is cool can it run nodes like gensyn when i provide it with proper commands on hyperbolic gpu?

SENU1 year ago

@AnthropicAI That's OP Giving Claude the autonomy to rent and manage compute unlocks a whole new class of self-directed Al agents

Sagitario ◨ ◨1 year ago

@AnthropicAI Super bullish

Evade1 year ago

@AnthropicAI Claude just became GPU-native! This is a massive step for autonomous AI workflows, huge props to @hyperbolic_labs for making it real.

Prakhar1 year ago

@AnthropicAI Dawm privacy too. You guys are not leaving anything on the table 😂😁

Zection1 year ago

This is a major breakthrough! Enabling Claude to autonomously rent GPUs, run training scripts, and manage compute through natural language is a huge step forward for intelligent agent development. The ability to SSH, run commands like nvidia-smi, and tear down instances — all without human intervention — is seriously impressive. Huge congrats to the teams at @HyperbolicLabs and @AnthropicAI! Can’t wait to see how AI engineers leverage this to push the boundaries even further. 👏🔥

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We built the first AI agent that has its own computer powered by Hyperbolic! AI agents are now GPU rich! We developed an AgentKit that allow AI agents to • Check GPU availability • Rent & manage GPU compute • Access & run commands on remote machines Why does this matter? With their own compute resources, AI agents can: 1. Validate blockchains like Ethereum and decentralized protocols like 2. Launch and coordinate AI swarms on Hyperbolic's decentralized compute network 3. Train and fine-tune models, improving their own capabilities over time 4. Dive into AI research to push the boundaries of AI, i.e. themselves 5. Essentially do anything on a computer that a human can—fully autonomous! Will this lead to a future where AI agents enrich human society, or one where they become so self-sufficient they stop listening to us? Only time will tell. —————— Big shoutout to Coinbase Developer Platform🛡️'s CDP agentkit for inspiration. This repo is done by two non-engineers (our pm Kai Huang and myself) + Cursor ai agent to run agents. Codings can now be easily done by just prompting ai agents. What a crazy time!

We built the first AI agent that has its own computer powered by Hyperbolic! AI agents are now GPU rich! We developed an AgentKit that allow AI agents to • Check GPU availability • Rent & manage GPU compute • Access & run commands on remote machines Why does this matter? With their own compute resources, AI agents can: 1. Validate blockchains like Ethereum and decentralized protocols like 2. Launch and coordinate AI swarms on Hyperbolic's decentralized compute network 3. Train and fine-tune models, improving their own capabilities over time 4. Dive into AI research to push the boundaries of AI, i.e. themselves 5. Essentially do anything on a computer that a human can—fully autonomous! Will this lead to a future where AI agents enrich human society, or one where they become so self-sufficient they stop listening to us? Only time will tell. —————— Big shoutout to Coinbase Developer Platform🛡️'s CDP agentkit for inspiration. This repo is done by two non-engineers (our pm Kai Huang and myself) + Cursor ai agent to run agents. Codings can now be easily done by just prompting ai agents. What a crazy time!

Jasper

161,741 views • 1 year ago

🤯 Building computer-vision applications is never going to be the same again. As Andrej Karpathy says, "English is going to be the new programming-language", and we just made that happen for programming visual AI. 👨‍💻 This past month, the VLM Run team cooked up something magical that I'm especially proud of - a natural-language interface to build and run computer vision workflows (object-detection, OCR, parsing, and so much more) – all via our new VLM Run MCP server. 🔌 It works with any MCP-compatible AI agent (Claude, OpenAI, Cursor, etc.) and abstracts complex visual workflows into simple English commands. No need to write Python or fiddle with bespoke computer-vision code – just say what you want your agent to do, and it does it. Here’s a glimpse into what you can build today ( ☑️ Image AI agents – run detection, tagging, blurring, cropping, and more traditional CV tasks with English ☑️ Document AI agents – extract totals from invoices, search visual content, or act on what’s found ☑️ Video AI agents – understand scene content, trim clips, add subtitles, and create ready-to-share edits ☑️ And best-of-all, it's fully programmable with English. 🧑‍🍳 MCP Showcase: 📚 MCP Cookbooks: 📚 MCP Docs: #computervision #ai #agents #llm #vlm #mcp #vibecoding #genai

🤯 Building computer-vision applications is never going to be the same again. As Andrej Karpathy says, "English is going to be the new programming-language", and we just made that happen for programming visual AI. 👨‍💻 This past month, the VLM Run team cooked up something magical that I'm especially proud of - a natural-language interface to build and run computer vision workflows (object-detection, OCR, parsing, and so much more) – all via our new VLM Run MCP server. 🔌 It works with any MCP-compatible AI agent (Claude, OpenAI, Cursor, etc.) and abstracts complex visual workflows into simple English commands. No need to write Python or fiddle with bespoke computer-vision code – just say what you want your agent to do, and it does it. Here’s a glimpse into what you can build today ( ☑️ Image AI agents – run detection, tagging, blurring, cropping, and more traditional CV tasks with English ☑️ Document AI agents – extract totals from invoices, search visual content, or act on what’s found ☑️ Video AI agents – understand scene content, trim clips, add subtitles, and create ready-to-share edits ☑️ And best-of-all, it's fully programmable with English. 🧑‍🍳 MCP Showcase: 📚 MCP Cookbooks: 📚 MCP Docs: #computervision #ai #agents #llm #vlm #mcp #vibecoding #genai

Sudeep Pillai

17,789 views • 1 year ago

Claude Science just CHANGED how AI is used in research Anthropic didn't launch a new model they launched an AI-native scientific workspace Claude Science lets researchers: > analyze hundreds of papers at once > run Python, R & Jupyter notebooks > work with genomics, proteomics & molecular data > generate figures, charts & publication-ready outputs > keep a full reproducible audit trail this isn't about making the LLM smarter it's about building the workflow around it first we got Claude Code for developers now we have Claude Science for researchers the AI race is shifting it's no longer just who has the best model it's who builds the best AI operating system for every profession coding was first science is next

Claude Science just CHANGED how AI is used in research Anthropic didn't launch a new model they launched an AI-native scientific workspace Claude Science lets researchers: > analyze hundreds of papers at once > run Python, R & Jupyter notebooks > work with genomics, proteomics & molecular data > generate figures, charts & publication-ready outputs > keep a full reproducible audit trail this isn't about making the LLM smarter it's about building the workflow around it first we got Claude Code for developers now we have Claude Science for researchers the AI race is shifting it's no longer just who has the best model it's who builds the best AI operating system for every profession coding was first science is next

hammertime

19,976 views • 1 month ago

📢 BREAKING: Nvidia, Microsoft, and Anthropic announce new strategic AI partnerships of roughly $45 Billion. They struck a 3-way deal where Anthropic commits $30B for Azure compute with capacity up to 1GW, and NVIDIA and Microsoft plan to invest up to $10B and $5B in Anthropic. Claude will scale on Azure using NVIDIA systems, which expands access for enterprises and makes Claude available across the major clouds. Anthropic and NVIDIA will co-design to tune both model stacks and future chips for performance, efficiency, and total cost of ownership, so the models run faster per dollar. The first wave targets NVIDIA Grace Blackwell and Vera Rubin systems, which pair high-bandwidth memory with dense interconnect to push training and inference throughput. Microsoft will expose Anthropic models in Azure AI Foundry, including Claude Sonnet 4.5, Claude Opus 4.1, and Claude Haiku 4.5, so teams can pick latency and cost profiles. Claude will also remain available across the Copilot family, which means coding, document automation, and workflow agents can call the same model line. The 1GW commitment signals many thousands of GPUs worth of capacity, which reduces queue times and stabilizes unit economics for long-running training runs. The joint optimization loop, models shaping chips and chips shaping models, typically yields double-digit efficiency gains over off-the-shelf deployments.

📢 BREAKING: Nvidia, Microsoft, and Anthropic announce new strategic AI partnerships of roughly $45 Billion. They struck a 3-way deal where Anthropic commits $30B for Azure compute with capacity up to 1GW, and NVIDIA and Microsoft plan to invest up to $10B and $5B in Anthropic. Claude will scale on Azure using NVIDIA systems, which expands access for enterprises and makes Claude available across the major clouds. Anthropic and NVIDIA will co-design to tune both model stacks and future chips for performance, efficiency, and total cost of ownership, so the models run faster per dollar. The first wave targets NVIDIA Grace Blackwell and Vera Rubin systems, which pair high-bandwidth memory with dense interconnect to push training and inference throughput. Microsoft will expose Anthropic models in Azure AI Foundry, including Claude Sonnet 4.5, Claude Opus 4.1, and Claude Haiku 4.5, so teams can pick latency and cost profiles. Claude will also remain available across the Copilot family, which means coding, document automation, and workflow agents can call the same model line. The 1GW commitment signals many thousands of GPUs worth of capacity, which reduces queue times and stabilizes unit economics for long-running training runs. The joint optimization loop, models shaping chips and chips shaping models, typically yields double-digit efficiency gains over off-the-shelf deployments.

Rohan Paul

39,781 views • 9 months ago

Read the actual Anthropic piece. It's wilder than the hype precisely because it's so measured. As of last month, Claude writes more than 80% of the code Anthropic merges into its own codebase. Their engineers now ship roughly 8x the code per day they did in 2024. On a fixed test they run every release (take some training code, make it run faster), the model went from ~3x a year ago to ~52x. A skilled human gets about 4x in a few hours. And when a researcher hits a wrong turn mid-investigation, the newest model now picks the better next step 64% of the time. The honest part the hype skips is that Anthropic says we are NOT at self-improvement yet. Claude still can't decide which problems are worth solving. That research taste is the last thing keeping a human in the loop. But they openly map the moment it closes, when agents can build and train models themselves and Claude starts improving Claude. And the loudest signal in the whole thing sits at the end: the company building this is the one asking for a working pause button before the loop closes.

Read the actual Anthropic piece. It's wilder than the hype precisely because it's so measured. As of last month, Claude writes more than 80% of the code Anthropic merges into its own codebase. Their engineers now ship roughly 8x the code per day they did in 2024. On a fixed test they run every release (take some training code, make it run faster), the model went from ~3x a year ago to ~52x. A skilled human gets about 4x in a few hours. And when a researcher hits a wrong turn mid-investigation, the newest model now picks the better next step 64% of the time. The honest part the hype skips is that Anthropic says we are NOT at self-improvement yet. Claude still can't decide which problems are worth solving. That research taste is the last thing keeping a human in the loop. But they openly map the moment it closes, when agents can build and train models themselves and Claude starts improving Claude. And the loudest signal in the whole thing sits at the end: the company building this is the one asking for a working pause button before the loop closes.

Alex Veremeyenko

33,736 views • 2 months ago

Stop paying for Claude Code. You can run it for FREE. No API tokens. No monthly plan. No cloud costs. Here’s the simple setup: 1. Download Ollama (free). 2. Install a local model like GLM 4.7 Flash. 3. Launch Claude Code using that local model. 4. Done. You’re now running Claude Code fully powered by a local model. Same interface. No API bill. You can even run OpenClaw the same way. Local AI agents. Free. 24/7. Most people are overpaying because they don’t know this exists.

Stop paying for Claude Code. You can run it for FREE. No API tokens. No monthly plan. No cloud costs. Here’s the simple setup: 1. Download Ollama (free). 2. Install a local model like GLM 4.7 Flash. 3. Launch Claude Code using that local model. 4. Done. You’re now running Claude Code fully powered by a local model. Same interface. No API bill. You can even run OpenClaw the same way. Local AI agents. Free. 24/7. Most people are overpaying because they don’t know this exists.

Julian Goldie SEO

103,844 views • 5 months ago

X just made itself plug straight into AI tools with MCP servers. Your agents can now search and post on X directly. Not only read about it. Grok Build, Cursor, Claude, VS Code. All in. What you get: * X MCP; search posts, trends, bookmarks, even publish Articles * Docs MCP; API docs inside your workflow, no tab switching Setup is straightforward: * Go to create an X app * Enable OAuth 2.0; required for authentication * Add redirect URI; * Copy your CLIENT_ID and CLIENT_SECRET * Plug those into your MCP client or config * Run the setup commands; connect X MCP and Docs MCP * Log in once via browser; approve access * Verify; run grok mcp doctor xapi and grok mcp list Log in once. Done. Your workflow now includes X itself. X

X just made itself plug straight into AI tools with MCP servers. Your agents can now search and post on X directly. Not only read about it. Grok Build, Cursor, Claude, VS Code. All in. What you get: * X MCP; search posts, trends, bookmarks, even publish Articles * Docs MCP; API docs inside your workflow, no tab switching Setup is straightforward: * Go to create an X app * Enable OAuth 2.0; required for authentication * Add redirect URI; * Copy your CLIENT_ID and CLIENT_SECRET * Plug those into your MCP client or config * Run the setup commands; connect X MCP and Docs MCP * Log in once via browser; approve access * Verify; run grok mcp doctor xapi and grok mcp list Log in once. Done. Your workflow now includes X itself. X

Mario Nawfal

59,976 views • 1 month ago

If you use Claude Code, install this immediately. It's called Claude Code Templates. It adds an entire ecosystem of AI tools to Claude. Here's what you get: 1. Agent Teams Visual dashboards showing how multiple AI agents collaborate on code. 2. Specialized Agents Front-end developers, backend engineers, QA testers, marketers. 3. MCP Integrations Connect Claude to external tools and workflows. 4. Real-Time Monitoring Track AI development sessions and performance analytics. 5. Automation Scheduling Run tasks automatically every day. Example: You can schedule an agent team to run daily at 5AM. It researches trends, generates content, and builds workflows. All automatically. The best part? Everything is free and open source.

If you use Claude Code, install this immediately. It's called Claude Code Templates. It adds an entire ecosystem of AI tools to Claude. Here's what you get: 1. Agent Teams Visual dashboards showing how multiple AI agents collaborate on code. 2. Specialized Agents Front-end developers, backend engineers, QA testers, marketers. 3. MCP Integrations Connect Claude to external tools and workflows. 4. Real-Time Monitoring Track AI development sessions and performance analytics. 5. Automation Scheduling Run tasks automatically every day. Example: You can schedule an agent team to run daily at 5AM. It researches trends, generates content, and builds workflows. All automatically. The best part? Everything is free and open source.

Julian Goldie SEO

107,454 views • 5 months ago

Anthropic just launched Computer-Use-Agents on Claude Desktop, meaning it can now take control of your entire computer environment. This is huge for businesses and enterprise, except it's limited by the fact that it requires a personal computer. If you deploy it into a virtual machine on Orgo, you can now manage hundreds or thousands of your clients' Claude accounts, setting up their skills, capabilities, connectors, etc, all on their own machines in the cloud on Orgo.

Anthropic just launched Computer-Use-Agents on Claude Desktop, meaning it can now take control of your entire computer environment. This is huge for businesses and enterprise, except it's limited by the fact that it requires a personal computer. If you deploy it into a virtual machine on Orgo, you can now manage hundreds or thousands of your clients' Claude accounts, setting up their skills, capabilities, connectors, etc, all on their own machines in the cloud on Orgo.

Nick Vasilescu

38,333 views • 4 months ago

We just launched Comfy MCP in public beta, the first MCP built for production pipelines. Connect Claude, Codex, Cursor, or Hermes to the entire ComfyUI ecosystem. → Run any workflow in natural language → Search models, nodes, and templates → Share a workflow URL - your agent picks it up → Re-run saved workflows on new inputs without touching a single node → Hundreds of pre-built workflows. Always auto-updated 20 product-placement images for your brand ads. Character design for your game art. Script-to-shot ideation at scale and so on! Your agent is now a creative technologist.

ComfyUI

235,803 views • 1 month ago

> Training Grok 4.1 or Claude Opus 4.5 to trade gold futures???? > Everyone talking about clawd bot > What if there was a clawd bot for money... wait that's pigeon > pigeon is an omnipresent ai agent that you can control using sms, discord, telegram, or claude code > can continuously do research and even code and run the code on a secure sandbox > here i attempt to lose $100 by shorting into the greatest gold bull run in history on ostium

> Training Grok 4.1 or Claude Opus 4.5 to trade gold futures???? > Everyone talking about clawd bot > What if there was a clawd bot for money... wait that's pigeon > pigeon is an omnipresent ai agent that you can control using sms, discord, telegram, or claude code > can continuously do research and even code and run the code on a secure sandbox > here i attempt to lose $100 by shorting into the greatest gold bull run in history on ostium

jason kim

10,573 views • 6 months ago

Claude Code is a major (and accidental!) hit for Anthropic that surprised even its creator, Boris Cherny. Claude Code, an Agentic AI coding product that lives in the terminal. Most of the new code at Anthropic is created through it today. And in the last 5 months since it was launched publicly, Claude Code went from $0 to $400M in revenue run rate (as per The Information). 00:00 – Intro 01:15 – Did You Expect Claude Code’s Success? 04:22 – How Claude Code Works and Origins 08:05 – Command Line vs IDE: Why Start Claude Code in the Terminal? 11:31 – The Evolution of Programming: From Punch Cards to Agents 13:20 – Product Follows Model: Simple Interfaces and Fast Evolution 15:17 – Who Is Claude Code For? (Engineers, Designers, PMs & More) 17:46 – What Can Claude Code Actually Do? (Actions & Capabilities) 21:14 – Agentic Actions, Subagents, and Workflows 25:30 – Claude Code’s Awareness, Memory, and Knowledge Sharing 33:28 – Model Context Protocol (MCP) and Customization 35:30 – Safety, Human Oversight, and Enterprise Considerations 38:10 – UX/UI: Making Claude Code Useful and Enjoyable 40:44 – Pricing for Power Users and Subscription Models 43:36 – Real-World Use Cases: Debugging, Testing, and More 46:44 – How Does Claude Code Transform Onboarding? 49:36 – The Future of Coding: Agents, Teams, and Collaboration 54:11 – The AI Coding Wars: Competition & Ecosystem 57:27 – The Future of Coding as a Profession 58:41 – What’s Next for Claude Code

Claude Code is a major (and accidental!) hit for Anthropic that surprised even its creator, Boris Cherny. Claude Code, an Agentic AI coding product that lives in the terminal. Most of the new code at Anthropic is created through it today. And in the last 5 months since it was launched publicly, Claude Code went from $0 to $400M in revenue run rate (as per The Information). 00:00 – Intro 01:15 – Did You Expect Claude Code’s Success? 04:22 – How Claude Code Works and Origins 08:05 – Command Line vs IDE: Why Start Claude Code in the Terminal? 11:31 – The Evolution of Programming: From Punch Cards to Agents 13:20 – Product Follows Model: Simple Interfaces and Fast Evolution 15:17 – Who Is Claude Code For? (Engineers, Designers, PMs & More) 17:46 – What Can Claude Code Actually Do? (Actions & Capabilities) 21:14 – Agentic Actions, Subagents, and Workflows 25:30 – Claude Code’s Awareness, Memory, and Knowledge Sharing 33:28 – Model Context Protocol (MCP) and Customization 35:30 – Safety, Human Oversight, and Enterprise Considerations 38:10 – UX/UI: Making Claude Code Useful and Enjoyable 40:44 – Pricing for Power Users and Subscription Models 43:36 – Real-World Use Cases: Debugging, Testing, and More 46:44 – How Does Claude Code Transform Onboarding? 49:36 – The Future of Coding: Agents, Teams, and Collaboration 54:11 – The AI Coding Wars: Competition & Ecosystem 57:27 – The Future of Coding as a Profession 58:41 – What’s Next for Claude Code

Matt Turck

82,161 views • 1 year ago

🚨 Founders: free, private, 100% local AI is finally here I downloaded Qwen 3.6 and ran it on my MacBook inside Strawberry browser. I couldn't believe it. We now have 100% free and private AI that is on par with the best models from OpenAI, Anthropic and Google. (see video!) The CTO of Hugging Face called this "the second revolution of AI." He's right. If you are a building an AI product, you HAVE to start thinking about how you can leverage open source models in your product. It's only a matter of time until local models are mainstream and can run on most people's devices. LLMs are commoditizing. The human brain only requires a AAA battery's worth of energy to run. If biology figured out efficient intelligence, software can too. Maybe we won't need artificial super intelligence and thousands of data centres to do most economically valuable work. Maybe there's a future where AI agents just run on your laptop, fine-tuned to you, fully owned by you, costing only what your energy bill costs. In this future, it's all about building the most delightful, intuitive experience. We've been building for exactly this moment. Stay tuned.

🚨 Founders: free, private, 100% local AI is finally here I downloaded Qwen 3.6 and ran it on my MacBook inside Strawberry browser. I couldn't believe it. We now have 100% free and private AI that is on par with the best models from OpenAI, Anthropic and Google. (see video!) The CTO of Hugging Face called this "the second revolution of AI." He's right. If you are a building an AI product, you HAVE to start thinking about how you can leverage open source models in your product. It's only a matter of time until local models are mainstream and can run on most people's devices. LLMs are commoditizing. The human brain only requires a AAA battery's worth of energy to run. If biology figured out efficient intelligence, software can too. Maybe we won't need artificial super intelligence and thousands of data centres to do most economically valuable work. Maybe there's a future where AI agents just run on your laptop, fine-tuned to you, fully owned by you, costing only what your energy bill costs. In this future, it's all about building the most delightful, intuitive experience. We've been building for exactly this moment. Stay tuned.

Charles Maddock

12,731 views • 3 months ago

EIGHT USED RTX 3090s. 192GB OF VRAM. ONE PRIVATE BOX BUILT TO RUN 70B AI MODELS WITHOUT RENTING A DATACENTER. 00:06 the team lowers all eight GPUs into the chassis at once, turning a pile of old gaming cards into the core of a serious local AI server. each 3090 contributes 24GB of memory. combined, the rack has enough VRAM for heavyweight models, large document collections, long context and multiple jobs running side by side. these cards are five years old, but AI economics work differently from gaming. memory capacity matters more than having the newest badge, which is why used 3090s remain valuable. the server can keep one model loaded while separate GPUs handle video, images, transcription and overnight agents without sending private company data into the cloud. bookmark this build before yesterday’s gaming GPUs become tomorrow’s cheapest AI infrastructure.

EIGHT USED RTX 3090s. 192GB OF VRAM. ONE PRIVATE BOX BUILT TO RUN 70B AI MODELS WITHOUT RENTING A DATACENTER. 00:06 the team lowers all eight GPUs into the chassis at once, turning a pile of old gaming cards into the core of a serious local AI server. each 3090 contributes 24GB of memory. combined, the rack has enough VRAM for heavyweight models, large document collections, long context and multiple jobs running side by side. these cards are five years old, but AI economics work differently from gaming. memory capacity matters more than having the newest badge, which is why used 3090s remain valuable. the server can keep one model loaded while separate GPUs handle video, images, transcription and overnight agents without sending private company data into the cloud. bookmark this build before yesterday’s gaming GPUs become tomorrow’s cheapest AI infrastructure.

Gipp 🦅

118,882 views • 1 month ago

Grok CLI >>> Cursor and Claude Code We wanted an IDE for xAI's Grok so we did something meta: we prompted the newly released Grok 4 to create... Grok CLI itself! Grok CLI can: 1. Modify local files and use the shell 2. Go through huge codebases and fix them 3. Persist for longer and solve really complex math and physics problems Instant setup on Replit ⠕ Bonus: Can create and run ai agents with it's completely open source!! link to the code: link to the repl:

Grok CLI >>> Cursor and Claude Code We wanted an IDE for xAI's Grok so we did something meta: we prompted the newly released Grok 4 to create... Grok CLI itself! Grok CLI can: 1. Modify local files and use the shell 2. Go through huge codebases and fix them 3. Persist for longer and solve really complex math and physics problems Instant setup on Replit ⠕ Bonus: Can create and run ai agents with it's completely open source!! link to the code: link to the repl:

Karan Vaidya

345,808 views • 1 year ago

We built MiniMax a CLI coding agent like Claude Code, powered by MiniMax M3. It can: → Read files → Write code → Run shell commands autonomously → Understand large codebases with long-context reasoning → Handle real multi-file engineering tasks → Work entirely inside your terminal And it's fully hackable. Swap prompts. Add tools. Customize workflows. Make it your own. No GUI. Just code. Built for developers who live in the terminal.

We built MiniMax a CLI coding agent like Claude Code, powered by MiniMax M3. It can: → Read files → Write code → Run shell commands autonomously → Understand large codebases with long-context reasoning → Handle real multi-file engineering tasks → Work entirely inside your terminal And it's fully hackable. Swap prompts. Add tools. Customize workflows. Make it your own. No GUI. Just code. Built for developers who live in the terminal.

Darshal Jaitwar

18,861 views • 2 months ago

Today we're launching iMessage video ads in Claude. Faceless video is the best-performing ad format right now — and Claude can now generate a full one end to end, in one prompt. Here's how it works: 1. Install: npx gooseworks install --all 2. Run: /goose-video make an iMessage ad for [your product] Claude writes the script, generates the photos in the thread, animates the conversation, and closes on your brand. SFX, music, end card, all of it. The trick: it's just HTML. No video generation models, so it's fast and cheap — and it works because it doesn't look like an ad. It's that easy. But this is just the start. We have created a library with 100+ open-source skills for growth that some of the fastest growing startups in the world are using every day to run ads, content, competitor research, gtm, seo and more. Comment Goose and I'll DM you the full open-source skill library.

Soham Mehta

49,849 views • 1 month ago

"why didn't you tweet yesterday bro?" idk bro claude can now control adobe, blender, autodesk fusion, ableton, affinity, splice, sketchup and resolume. 9 creative tools at once and natural language interface across all of them. > blender: debug an entire scene, batch apply changes across every object, build custom scripts, and add new tools directly into blender's interface > autodesk fusion: create and modify 3d models through conversation > adobe creative cloud: 50+ tools across photoshop, premiere, firefly, and express through one connector > ableton: you don’t need to learn via forums anymore… just ask via natural language to access all knowledge from docs > canva’s affinity: batch image changes, layer renaming, file export, and custom features generated inside the app > splice: search their royalty free sample catalog from inside claude > sketchup and resolume: 3d modeling via conversation and live visual control yes, Claude for CAD exists now. and so does claude for ableton… and so does claude for the entire adobe stack. and the bigger move barely anyone’s noticed: anthropic also joined the blender development fund as a patron. meaning likely more open infra for us the connector itself is built on MCP, which means it works for other AI models too. "that's why I haven't tweeted bro" I had some things to comprehend

"why didn't you tweet yesterday bro?" idk bro claude can now control adobe, blender, autodesk fusion, ableton, affinity, splice, sketchup and resolume. 9 creative tools at once and natural language interface across all of them. > blender: debug an entire scene, batch apply changes across every object, build custom scripts, and add new tools directly into blender's interface > autodesk fusion: create and modify 3d models through conversation > adobe creative cloud: 50+ tools across photoshop, premiere, firefly, and express through one connector > ableton: you don’t need to learn via forums anymore… just ask via natural language to access all knowledge from docs > canva’s affinity: batch image changes, layer renaming, file export, and custom features generated inside the app > splice: search their royalty free sample catalog from inside claude > sketchup and resolume: 3d modeling via conversation and live visual control yes, Claude for CAD exists now. and so does claude for ableton… and so does claude for the entire adobe stack. and the bigger move barely anyone’s noticed: anthropic also joined the blender development fund as a patron. meaning likely more open infra for us the connector itself is built on MCP, which means it works for other AI models too. "that's why I haven't tweeted bro" I had some things to comprehend

klöss

62,257 views • 3 months ago

THIS CHINESE BUILDER TURNED 8 RETIRED TESLA P40s INTO A 192GB PRIVATE AI SERVER THAT CAN WORK 5,760 GPU-HOURS EVERY MONTH. 00:06 he holds up one used Tesla P40 while seven more sit behind it, then installs the full stack inside a massive dual-Xeon server chassis. each card carries 24GB of VRAM, giving the system 192GB across eight GPUs for local models, video processing, transcription, private documents and AI agents. the real advantage is parallel work. some cards can serve a local model while the rest generate images, process files and run overnight automation at the same time. eight GPUs running continuously deliver 5,760 GPU-hours every 30 days. rent that workload from the cloud and the meter keeps moving for every minute the server stays online. a $412 monthly AI stack already costs $4,944 a year before serious GPU rental. he bought retired hardware once, kept the data local and built a machine that keeps working after the browser closes.

THIS CHINESE BUILDER TURNED 8 RETIRED TESLA P40s INTO A 192GB PRIVATE AI SERVER THAT CAN WORK 5,760 GPU-HOURS EVERY MONTH. 00:06 he holds up one used Tesla P40 while seven more sit behind it, then installs the full stack inside a massive dual-Xeon server chassis. each card carries 24GB of VRAM, giving the system 192GB across eight GPUs for local models, video processing, transcription, private documents and AI agents. the real advantage is parallel work. some cards can serve a local model while the rest generate images, process files and run overnight automation at the same time. eight GPUs running continuously deliver 5,760 GPU-hours every 30 days. rent that workload from the cloud and the meter keeps moving for every minute the server stays online. a $412 monthly AI stack already costs $4,944 a year before serious GPU rental. he bought retired hardware once, kept the data local and built a machine that keeps working after the browser closes.

Gipp 🦅

42,332 views • 1 month ago