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THIS IS F**KING DANGEROUS THREE OPEN SOURCE AI CYBERSECURITY STACK MOST PEOPLE DONT KNOW EXISTS METATRON: point it at a target, it recon's, analyzes, and reports on its own —> fully OFFLINE , zero API keys. NUCLEI : describe a vulnerability in plain English, it writes and runs the... show more

MAX

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97,075 просмотров • 4 дней назад •via X (Twitter)

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Introducing: OpenGranola 🔥 I built an open source meeting copilot for macOS. It transcribes both sides of your call on-device, searches your own notes in real time, and hands you talking points right when the conversation needs them. No audio leaves your Mac. Point it at a folder of markdown files, pick any LLM through OpenRouter (Claude, GPT-4o, Gemini, Llama), and it just works. It's invisible to screen share too — nobody knows you have it. The whole thing is open source. Link below

Introducing: OpenGranola 🔥 I built an open source meeting copilot for macOS. It transcribes both sides of your call on-device, searches your own notes in real time, and hands you talking points right when the conversation needs them. No audio leaves your Mac. Point it at a folder of markdown files, pick any LLM through OpenRouter (Claude, GPT-4o, Gemini, Llama), and it just works. It's invisible to screen share too — nobody knows you have it. The whole thing is open source. Link below

yazin

293,178 просмотров • 5 месяцев назад

this is f**king dangerous Most people treat Claude like a search bar. The ones with a second brain treat it as an intelligence layer on everything they know. Here's the 15-minute setup: → Install Claude Code → Install Obsidian, create a vault → Open it in Claude Code, drop in the CLAUDE.md schema — that one file is the engine → Throw any source in, say "ingest this" Done. From then on, everything you know is queryable by the most capable AI on earth. Claude wires each source against your whole vault and surfaces connections you forgot you had. Build it tonight. full A–Z guide below.

this is f**king dangerous Most people treat Claude like a search bar. The ones with a second brain treat it as an intelligence layer on everything they know. Here's the 15-minute setup: → Install Claude Code → Install Obsidian, create a vault → Open it in Claude Code, drop in the CLAUDE.md schema — that one file is the engine → Throw any source in, say "ingest this" Done. From then on, everything you know is queryable by the most capable AI on earth. Claude wires each source against your whole vault and surfaces connections you forgot you had. Build it tonight. full A–Z guide below.

Kirill

19,358 просмотров • 1 месяц назад

Okay... this is actually insane. OpenCodex feels like the open-source breakthrough I've been waiting for. The best part : You can plug multiple providers into the same OpenAI Codex harness and switch between models depending on the task. Running low on tokens? No problem. Use another provider. OpenRouter free model today? Plug it in. This completely changes how I think about AI coding workflows. And yes... it even works on mobile. OpenCodex might be one of the most useful open-source AI projects I've seen this year. OpenAI built an incredible harness. The open-source community just made it universal.

Okay... this is actually insane. OpenCodex feels like the open-source breakthrough I've been waiting for. The best part : You can plug multiple providers into the same OpenAI Codex harness and switch between models depending on the task. Running low on tokens? No problem. Use another provider. OpenRouter free model today? Plug it in. This completely changes how I think about AI coding workflows. And yes... it even works on mobile. OpenCodex might be one of the most useful open-source AI projects I've seen this year. OpenAI built an incredible harness. The open-source community just made it universal.

CHOI

42,894 просмотров • 1 месяц назад

China just dropped an open source model that turns any phone into a 3D scanner you point it at a room and walk through it the whole space builds itself into a 3D point cloud in real time as the camera moves, no LiDAR and no depth sensor anywhere it held a full 13 minute walkthrough at 25,000 frames without the map drifting or collapsing > ~20 fps on a single GPU > works indoors and outdoors from plain footage > the scan normally needs a $50,000 rig and a technician > Apache 2.0 and runs fully offline on your machine repo in the reply

China just dropped an open source model that turns any phone into a 3D scanner you point it at a room and walk through it the whole space builds itself into a 3D point cloud in real time as the camera moves, no LiDAR and no depth sensor anywhere it held a full 13 minute walkthrough at 25,000 frames without the map drifting or collapsing > ~20 fps on a single GPU > works indoors and outdoors from plain footage > the scan normally needs a $50,000 rig and a technician > Apache 2.0 and runs fully offline on your machine repo in the reply

savip

104,123 просмотров • 1 месяц назад

SOMEONE JUST VIBECODED A PROGRAM THAT DOWNLOADS ANY WEBSITE ON THE INTERNET every $35,000 agency site is now yours to rip clean for $0 fully open source, save it before it's gone you paste one url and it does the rest: → crawls the entire site → grabs every file: html, css, js, images, even the fonts → rewrites every link to run fully offline → packs it all into a downloadable zip runs entirely in the browser, nothing to install or sign up for point it at any site you admire and the whole front-end is yours: → clone it → archive it before it dies → crack open exactly how it was built the thing agencies gatekeep for five figures is now a 10-second download bookmark this one

SOMEONE JUST VIBECODED A PROGRAM THAT DOWNLOADS ANY WEBSITE ON THE INTERNET every $35,000 agency site is now yours to rip clean for $0 fully open source, save it before it's gone you paste one url and it does the rest: → crawls the entire site → grabs every file: html, css, js, images, even the fonts → rewrites every link to run fully offline → packs it all into a downloadable zip runs entirely in the browser, nothing to install or sign up for point it at any site you admire and the whole front-end is yours: → clone it → archive it before it dies → crack open exactly how it was built the thing agencies gatekeep for five figures is now a 10-second download bookmark this one

Argona

126,379 просмотров • 1 месяц назад

GOODBYE TO CYBERSECURITY! Someone just open-sourced an arsenal of AI hacking tools. Not one. Not ten. Hundreds. Inside the repository: • Jailbreak frameworks for LLMs • Prompt injection testing tools • AI red team agents • Model extraction utilities • Supply chain attack demos • Automated AI pentesting frameworks These are the same categories of tools security researchers use to find vulnerabilities before attackers do. Now anyone can study them. That's both exciting... and terrifying. The biggest threat to AI isn't smarter models. It's insecure ones. If you're building with LLMs and you're not actively testing your prompts, agents, and infrastructure— You're probably shipping vulnerabilities you don't even know exist. Open source is accelerating AI. It's also accelerating AI attacks. Repository link in the comments ↓

GOODBYE TO CYBERSECURITY! Someone just open-sourced an arsenal of AI hacking tools. Not one. Not ten. Hundreds. Inside the repository: • Jailbreak frameworks for LLMs • Prompt injection testing tools • AI red team agents • Model extraction utilities • Supply chain attack demos • Automated AI pentesting frameworks These are the same categories of tools security researchers use to find vulnerabilities before attackers do. Now anyone can study them. That's both exciting... and terrifying. The biggest threat to AI isn't smarter models. It's insecure ones. If you're building with LLMs and you're not actively testing your prompts, agents, and infrastructure— You're probably shipping vulnerabilities you don't even know exist. Open source is accelerating AI. It's also accelerating AI attacks. Repository link in the comments ↓

Shruti Codes

124,984 просмотров • 1 месяц назад

I genuinely don't understand why everyone isn't using this yet Andrej Karpathy, a co-founder of OpenAI, posted a simple idea that hit 16 million views: stop using AI to write code, use it to build a second brain. You point Claude Code at a folder, drop in any source, an article, a transcript, a PDF, and Claude reads it, links it, and files it into a living wiki of everything you know. It compounds like interest, the more you feed it, the smarter it gets. Here's the whole thing: > Install Obsidian, create a vault, open it in Claude Code > Paste Karpathy's wiki idea file and tell Claude to build it > Claude makes three folders: raw for sources, wiki for its pages, a CLAUDE.md that runs it > Drop any source into raw and say "ingest this" > Ask questions across everything, forever Five minutes to set up, and you never start from a blank chat again. Full step-by-step guide with Claude and Obsidian, link below. Bookmark this

I genuinely don't understand why everyone isn't using this yet Andrej Karpathy, a co-founder of OpenAI, posted a simple idea that hit 16 million views: stop using AI to write code, use it to build a second brain. You point Claude Code at a folder, drop in any source, an article, a transcript, a PDF, and Claude reads it, links it, and files it into a living wiki of everything you know. It compounds like interest, the more you feed it, the smarter it gets. Here's the whole thing: > Install Obsidian, create a vault, open it in Claude Code > Paste Karpathy's wiki idea file and tell Claude to build it > Claude makes three folders: raw for sources, wiki for its pages, a CLAUDE.md that runs it > Drop any source into raw and say "ingest this" > Ask questions across everything, forever Five minutes to set up, and you never start from a blank chat again. Full step-by-step guide with Claude and Obsidian, link below. Bookmark this

Ridark

6,969,641 просмотров • 2 месяцев назад

The most underrated skill in the world right now is prompting…if you can speak the language of AI, AI will give you what you want. That’s why I had my internal AI transformation hire create a cracked prompting tool for our company to use internally. It essentially helps you create the perfect prompt. I love it - and that’s why I want to open source it.

The most underrated skill in the world right now is prompting…if you can speak the language of AI, AI will give you what you want. That’s why I had my internal AI transformation hire create a cracked prompting tool for our company to use internally. It essentially helps you create the perfect prompt. I love it - and that’s why I want to open source it.

Codie Sanchez

38,700 просмотров • 6 месяцев назад

one of these is a real ugc creator the other is fully ai found a viral tiktok yesterday and rebuilt it with seedance 2.0 in like 20 minutes same hook. same script. same bones. swapped the character. swapped the setting. thats it this is the unlock most brands still dont see you dont need to find the next viral concept you take whats already proven and clone it with ai then spin 50 variations until one fucking booms infinite shots on goal for the price of one shoot real creators cost $200-500 a video and take a week this took 20 minutes and cost cents drop "clone" and ill dm you the full stack (must follow so i can dm) if you're a brand and want this for your products launch a campaign on Affiliate Network below

Sam

163,749 просмотров • 3 месяцев назад

OpenClaw, but built for normal people. Sim is an open-source platform that lets you build AI agent workflows on a drag-and-drop canvas. Connect them to channels like Telegram and WhatsApp and deploy without writing a single line of code. They also have a built-in Copilot that generates entire workflows from plain English, which you can then tweak and customize in the UI. Key features: - Free and open-source (Apache 2.0) - Vector store integration for RAG-grounded agents - Self-host with one command (`npx simstudio`) - Run fully local with Ollama, no API keys needed - Supports vLLM for production-grade self-hosted inference The thing I really like about Sim is the level of control you get. You can add conditional branching, parallel execution, human-in-the-loop approval gates, and even nest workflows inside other workflows. Everything is visible on the canvas, so you know exactly what your agent is doing at every step. And you can build a workflow in Sim, deploy it as an MCP server, and plug it into any agent, including OpenClaw. I've shared the link to Sim's GitHub repo in the next tweet.

OpenClaw, but built for normal people. Sim is an open-source platform that lets you build AI agent workflows on a drag-and-drop canvas. Connect them to channels like Telegram and WhatsApp and deploy without writing a single line of code. They also have a built-in Copilot that generates entire workflows from plain English, which you can then tweak and customize in the UI. Key features: - Free and open-source (Apache 2.0) - Vector store integration for RAG-grounded agents - Self-host with one command (`npx simstudio`) - Run fully local with Ollama, no API keys needed - Supports vLLM for production-grade self-hosted inference The thing I really like about Sim is the level of control you get. You can add conditional branching, parallel execution, human-in-the-loop approval gates, and even nest workflows inside other workflows. Everything is visible on the canvas, so you know exactly what your agent is doing at every step. And you can build a workflow in Sim, deploy it as an MCP server, and plug it into any agent, including OpenClaw. I've shared the link to Sim's GitHub repo in the next tweet.

Akshay 🚀

52,426 просмотров • 6 месяцев назад

SOMEONE BUILT A TERMINAL TORRENT CLIENT THAT SEARCHES EVERY TRUSTED SOURCE AT ONCE AND DOWNLOADS STRAIGHT TO DISK finding a torrent in 2026 is miserable fake download buttons, popups that spawn three more tabs, and half the results are dead with zero seeders. so he built the opposite of all that: > type one query and it hits a curated set of trackers all at once > results stream back tagged with source, size and seeders as fast as each site answers > arrow to the one you want, press d, and it lands on your drive > if one source is down it just skips it and keeps searching the rest > downloads run in the background and pick up where they left off if you quit mid transfer the whole thing is one command. npx and youre running, all you need is node, no browser, no setup, nothing leaves your machine except the request itself. its called torlink, open source and mit. this is the kind of clean terminal tool that does one annoying thing perfectly

SOMEONE BUILT A TERMINAL TORRENT CLIENT THAT SEARCHES EVERY TRUSTED SOURCE AT ONCE AND DOWNLOADS STRAIGHT TO DISK finding a torrent in 2026 is miserable fake download buttons, popups that spawn three more tabs, and half the results are dead with zero seeders. so he built the opposite of all that: > type one query and it hits a curated set of trackers all at once > results stream back tagged with source, size and seeders as fast as each site answers > arrow to the one you want, press d, and it lands on your drive > if one source is down it just skips it and keeps searching the rest > downloads run in the background and pick up where they left off if you quit mid transfer the whole thing is one command. npx and youre running, all you need is node, no browser, no setup, nothing leaves your machine except the request itself. its called torlink, open source and mit. this is the kind of clean terminal tool that does one annoying thing perfectly

Om Patel

361,539 просмотров • 1 месяц назад

🚨 JUST IN: CHINA just released an AI EMPLOYEE that works 24X7 on its own. 100% OPEN SOURCE. It researches, codes, builds websites, creates slide decks, and generates videos. All by itself. All on your computer. It's called DeerFlow. You give it a task. It makes a plan, spins up its own team of sub-agents, and gets to work. You come back and there's a finished deliverable waiting. Not a draft. Not a summary. The actual thing. Not a chatbot. Not a research assistant. An AI with its own computer that works while you sleep. Here's what it does on its own: → Spawns multiple sub-agents in parallel, each tackling a different piece of your task, then combines everything into one finished output → Writes real code, runs it, reads the results, and fixes its own mistakes without asking you once → Builds slide decks, websites, full research reports, and data dashboards from scratch → Remembers you across sessions. Your writing style. Your tech stack. Your preferences. Gets better every time. → Reads files you upload, works with them inside its own filesystem, hands you clean finished outputs → Searches the web, runs commands, calls any tool you plug in Here's how it thinks: You give one instruction. The lead agent makes a plan. Sub-agents fan out and work in parallel. Results come back. Everything gets synthesized. You get a deliverable. A single research task might split into a dozen sub-agents, each exploring a different angle, then converge into one finished website with generated visuals. Here's the wildest part: DeerFlow 2.0 launched on February 28th 2026 and hit number 1 on all of GitHub Trending the same day. Version 2.0 was a complete rewrite. Zero shared code with version 1. Because users kept using it for things the team never intended. Data pipelines. Dashboards. Entire content workflows. The community told them what it needed to become. So they burned it down and rebuilt it. 22.7K GitHub stars. 2.7K forks. Built by ByteDance 100% Open Source. MIT License.

🚨 JUST IN: CHINA just released an AI EMPLOYEE that works 24X7 on its own. 100% OPEN SOURCE. It researches, codes, builds websites, creates slide decks, and generates videos. All by itself. All on your computer. It's called DeerFlow. You give it a task. It makes a plan, spins up its own team of sub-agents, and gets to work. You come back and there's a finished deliverable waiting. Not a draft. Not a summary. The actual thing. Not a chatbot. Not a research assistant. An AI with its own computer that works while you sleep. Here's what it does on its own: → Spawns multiple sub-agents in parallel, each tackling a different piece of your task, then combines everything into one finished output → Writes real code, runs it, reads the results, and fixes its own mistakes without asking you once → Builds slide decks, websites, full research reports, and data dashboards from scratch → Remembers you across sessions. Your writing style. Your tech stack. Your preferences. Gets better every time. → Reads files you upload, works with them inside its own filesystem, hands you clean finished outputs → Searches the web, runs commands, calls any tool you plug in Here's how it thinks: You give one instruction. The lead agent makes a plan. Sub-agents fan out and work in parallel. Results come back. Everything gets synthesized. You get a deliverable. A single research task might split into a dozen sub-agents, each exploring a different angle, then converge into one finished website with generated visuals. Here's the wildest part: DeerFlow 2.0 launched on February 28th 2026 and hit number 1 on all of GitHub Trending the same day. Version 2.0 was a complete rewrite. Zero shared code with version 1. Because users kept using it for things the team never intended. Data pipelines. Dashboards. Entire content workflows. The community told them what it needed to become. So they burned it down and rebuilt it. 22.7K GitHub stars. 2.7K forks. Built by ByteDance 100% Open Source. MIT License.

Kanika

738,392 просмотров • 5 месяцев назад

Goldman pays $27,000 per seat for a Bloomberg Terminal. I found 10 open source tools on GitHub that replicate almost all of it for free. Retail investors have never had this much firepower. Bookmark & Repost this one: 1. OpenBB Stocks, options, crypto, forex, and macro data in one research platform. Build your own dashboards, reports, and AI analysts on top of it. The OG of open source finance. 50K+ stars. 2. FinceptTerminal A full financial terminal: global market data, advanced charts, economic indicators, portfolio analysis, and AI research tools. Windows, Mac, and Linux. 3. Neuberg 516 drag-and-drop panels covering equities, bonds, commodities, currencies, credit, and macro. Even connects to Alpaca, Hyperliquid, and Polymarket so you can trade from the terminal itself. 4. Qlib (by Microsoft) An open source AI platform for quant investing. Train ML models, discover signals, backtest strategies, and build portfolios with the same workflow a quant desk uses. 5. FinRobot An AI equity research team on your laptop. Its agents read financial statements, build DCF valuations, debate bull vs bear cases, and generate full investment reports. 6. EdgarTools Turns the SEC database into something humans can actually use. Pull 10-Ks, 10-Qs, insider trades, executive pay, and hedge fund holdings going back to 1994. 7. LEAN (by QuantConnect) An institutional-grade engine for trading algorithms. Write strategies in Python or C#, backtest on decades of data, then connect to real brokers and go live. 8. FinanceToolkit 200+ financial ratios, valuation models, risk metrics, and economic indicators. Works on stocks, ETFs, options, currencies, commodities, and crypto from Python. 9. Ghostfolio A private wealth dashboard for stocks, ETFs, and crypto across all your accounts. Performance, allocation, diversification. Your data never leaves your machine. 10. OpenTerminalUI A self-hosted trading terminal: pro charts, screeners, options chains with live Greeks, portfolio optimization, backtesting, and an AI research agent. Runs entirely on your own hardware. Bloomberg spent 40 years building a $27,000/year moat. Open source is draining it one repo at a time. The software is free. Some live data feeds need your own API keys, but the barrier is now effort, not money. If you want the exact workflows we use to stack these tools with AI, join the AIBullss Discord:

Goldman pays $27,000 per seat for a Bloomberg Terminal. I found 10 open source tools on GitHub that replicate almost all of it for free. Retail investors have never had this much firepower. Bookmark & Repost this one: 1. OpenBB Stocks, options, crypto, forex, and macro data in one research platform. Build your own dashboards, reports, and AI analysts on top of it. The OG of open source finance. 50K+ stars. 2. FinceptTerminal A full financial terminal: global market data, advanced charts, economic indicators, portfolio analysis, and AI research tools. Windows, Mac, and Linux. 3. Neuberg 516 drag-and-drop panels covering equities, bonds, commodities, currencies, credit, and macro. Even connects to Alpaca, Hyperliquid, and Polymarket so you can trade from the terminal itself. 4. Qlib (by Microsoft) An open source AI platform for quant investing. Train ML models, discover signals, backtest strategies, and build portfolios with the same workflow a quant desk uses. 5. FinRobot An AI equity research team on your laptop. Its agents read financial statements, build DCF valuations, debate bull vs bear cases, and generate full investment reports. 6. EdgarTools Turns the SEC database into something humans can actually use. Pull 10-Ks, 10-Qs, insider trades, executive pay, and hedge fund holdings going back to 1994. 7. LEAN (by QuantConnect) An institutional-grade engine for trading algorithms. Write strategies in Python or C#, backtest on decades of data, then connect to real brokers and go live. 8. FinanceToolkit 200+ financial ratios, valuation models, risk metrics, and economic indicators. Works on stocks, ETFs, options, currencies, commodities, and crypto from Python. 9. Ghostfolio A private wealth dashboard for stocks, ETFs, and crypto across all your accounts. Performance, allocation, diversification. Your data never leaves your machine. 10. OpenTerminalUI A self-hosted trading terminal: pro charts, screeners, options chains with live Greeks, portfolio optimization, backtesting, and an AI research agent. Runs entirely on your own hardware. Bloomberg spent 40 years building a $27,000/year moat. Open source is draining it one repo at a time. The software is free. Some live data feeds need your own API keys, but the barrier is now effort, not money. If you want the exact workflows we use to stack these tools with AI, join the AIBullss Discord:

AI Bulls

20,605 просмотров • 27 дней назад

THAT'S CRAZY, THIS CHINESE FOUNDER BUILT A MASSIVE MAC MINI FARM AND EACH ONE RUNNING ITS OWN HERMES AI AGENT LIKE A FULL-TIME EMPLOYEE He's not running one AI assistant. He's running an entire workforce. The stack: Mac Mini + Hermes, scaled out across a full physical farm. Every single Mac Mini in the rack runs its own instance of Hermes Agent – and each one has its own dedicated job. Not duplicated tasks. Actual division of labor, machine by machine, the way you'd structure a real team. No salaries. No sick days. No onboarding. Just racks of hardware, each one handling its own piece of the business, running in parallel, 24/7. This is what it looks like when "AI agent" stops being one chatbot on your laptop and starts being an actual operation. Most people are running one AI tool. This guy built a company out of them. Bookmark this post. Full setup in the video below.

THAT'S CRAZY, THIS CHINESE FOUNDER BUILT A MASSIVE MAC MINI FARM AND EACH ONE RUNNING ITS OWN HERMES AI AGENT LIKE A FULL-TIME EMPLOYEE He's not running one AI assistant. He's running an entire workforce. The stack: Mac Mini + Hermes, scaled out across a full physical farm. Every single Mac Mini in the rack runs its own instance of Hermes Agent – and each one has its own dedicated job. Not duplicated tasks. Actual division of labor, machine by machine, the way you'd structure a real team. No salaries. No sick days. No onboarding. Just racks of hardware, each one handling its own piece of the business, running in parallel, 24/7. This is what it looks like when "AI agent" stops being one chatbot on your laptop and starts being an actual operation. Most people are running one AI tool. This guy built a company out of them. Bookmark this post. Full setup in the video below.

SCOTTY BEAM

20,503 просмотров • 1 месяц назад

Why the world needs Grokipedia? ➤ Wikipedia isn’t the neutral source of truth it once was. It’s been taken over by far-left activists and often used as a propaganda tool, not an unbiased encyclopedia. ➤ A lot of AIs today get their info from the internet, but the web is full of unfair views, wrong facts, and tons of junk. ➤ Grokipedia will be an open-source encyclopedia focused solely on TRUTH. ➤ Grokipedia won’t be controlled by any activist or political bias. ➤ It will be open-source and free for all to use, a truly public resource without limits. ➤ xAI’s ultimate mission is to understand the universe, and that requires honest, unfiltered information. Grokipedia is a crucial step toward that goal, because you can’t build a truthful AI on biased information. ➤ The vision is for Grokipedia to become the global standard for knowledge. One day, every person and every AI system could rely on it as a trusted source of truth. ➤ Seeking truth is the greatest mission of all and that’s what Grokipedia stands for. Grokipedia is coming.

Why the world needs Grokipedia? ➤ Wikipedia isn’t the neutral source of truth it once was. It’s been taken over by far-left activists and often used as a propaganda tool, not an unbiased encyclopedia. ➤ A lot of AIs today get their info from the internet, but the web is full of unfair views, wrong facts, and tons of junk. ➤ Grokipedia will be an open-source encyclopedia focused solely on TRUTH. ➤ Grokipedia won’t be controlled by any activist or political bias. ➤ It will be open-source and free for all to use, a truly public resource without limits. ➤ xAI’s ultimate mission is to understand the universe, and that requires honest, unfiltered information. Grokipedia is a crucial step toward that goal, because you can’t build a truthful AI on biased information. ➤ The vision is for Grokipedia to become the global standard for knowledge. One day, every person and every AI system could rely on it as a trusted source of truth. ➤ Seeking truth is the greatest mission of all and that’s what Grokipedia stands for. Grokipedia is coming.

DogeDesigner

5,198,879 просмотров • 10 месяцев назад

Why the internet needs Grokipedia? ➤ Wikipedia isn’t the neutral source of truth it once was. It’s been taken over by far-left activists and often used as a propaganda tool, not an unbiased encyclopedia. ➤ A lot of AIs today get their info from the internet, but the web is full of unfair views, wrong facts, and tons of junk. ➤ Grokipedia will be an open-source encyclopedia focused solely on TRUTH. ➤ Grokipedia won’t be controlled by any activist or political bias. ➤ It will be open-source and free for all to use, a truly public resource without limits. ➤ xAI’s ultimate mission is to understand the universe, and that requires honest, unfiltered information. Grokipedia is a crucial step toward that goal, because you can’t build a truthful AI on biased information. ➤ The vision is for Grokipedia to become the global standard for knowledge. One day, every person and every AI system could rely on it as a trusted source of truth. ➤ Seeking truth is the greatest mission of all and that’s what Grokipedia stands for. Grokipedia is coming.

Why the internet needs Grokipedia? ➤ Wikipedia isn’t the neutral source of truth it once was. It’s been taken over by far-left activists and often used as a propaganda tool, not an unbiased encyclopedia. ➤ A lot of AIs today get their info from the internet, but the web is full of unfair views, wrong facts, and tons of junk. ➤ Grokipedia will be an open-source encyclopedia focused solely on TRUTH. ➤ Grokipedia won’t be controlled by any activist or political bias. ➤ It will be open-source and free for all to use, a truly public resource without limits. ➤ xAI’s ultimate mission is to understand the universe, and that requires honest, unfiltered information. Grokipedia is a crucial step toward that goal, because you can’t build a truthful AI on biased information. ➤ The vision is for Grokipedia to become the global standard for knowledge. One day, every person and every AI system could rely on it as a trusted source of truth. ➤ Seeking truth is the greatest mission of all and that’s what Grokipedia stands for. Grokipedia is coming.

DogeDesigner

69,846 просмотров • 10 месяцев назад

The startup world runs on iMessage. The problem is, the Mac messages app is not designed for productivity and there’s no alternative online. If you’re responding to 100+ texts a day, it’s painful and messages get lost easily. As a weekend project, I used Fable to vibecode an AI-native iMessage wrapper. It has: - AI autodrafting that continually learns from your edits - Time sensitive message detection as a separate section - The ability to archive messages so you can get to inbox zero. It reads from the local chat.db on your Mac, and sends messages via AppleScript, so it’s fully secure since it still uses the iMessage protocol on your computer. At Trajectory, we’re all about using AI to accelerate our company as much as possible as possible, and natively bake in CL into all of our processes. This is just one example of how we operate. If there’s enough interest, I’ll clean up the code and send the GH link!

The startup world runs on iMessage. The problem is, the Mac messages app is not designed for productivity and there’s no alternative online. If you’re responding to 100+ texts a day, it’s painful and messages get lost easily. As a weekend project, I used Fable to vibecode an AI-native iMessage wrapper. It has: - AI autodrafting that continually learns from your edits - Time sensitive message detection as a separate section - The ability to archive messages so you can get to inbox zero. It reads from the local chat.db on your Mac, and sends messages via AppleScript, so it’s fully secure since it still uses the iMessage protocol on your computer. At Trajectory, we’re all about using AI to accelerate our company as much as possible as possible, and natively bake in CL into all of our processes. This is just one example of how we operate. If there’s enough interest, I’ll clean up the code and send the GH link!

Ronak Malde

47,636 просмотров • 1 месяц назад

JENSEN HUANG UNVEILED A BOARD THAT RUNS 1 TRILLION PARAMETER AI MODELS. THE $249 NVIDIA BOX UNDER YOUR DESK KILLS A $200/MONTH AI BILL FOR $5 IN ELECTRICITY jensen held it up on stage with one hand and called it the architecture that runs the future of ai. that same technology now ships in a $249 box smaller than your wallet the jetson orin nano super pulls 7-25 watts and does 67 trillion ai operations per second. llama 3, mistral and deepseek run locally with no api fees and no data leaving your machine most developers pay $2,400 a year across chatgpt, openai api, claude pro and cursor. the jetson costs $314 in year one and $60 a year after. 2 year savings hit $4,431 install ollama with one command, change one line of code to point at localhost, and every tool built for openai works identically. zero rewrites, zero rate limits cloud subscriptions keep getting more expensive and rate limits keep getting tighter. the people who own the box in 2026 are going to look very far ahead in 2028 bookmark this and read the article below

JENSEN HUANG UNVEILED A BOARD THAT RUNS 1 TRILLION PARAMETER AI MODELS. THE $249 NVIDIA BOX UNDER YOUR DESK KILLS A $200/MONTH AI BILL FOR $5 IN ELECTRICITY jensen held it up on stage with one hand and called it the architecture that runs the future of ai. that same technology now ships in a $249 box smaller than your wallet the jetson orin nano super pulls 7-25 watts and does 67 trillion ai operations per second. llama 3, mistral and deepseek run locally with no api fees and no data leaving your machine most developers pay $2,400 a year across chatgpt, openai api, claude pro and cursor. the jetson costs $314 in year one and $60 a year after. 2 year savings hit $4,431 install ollama with one command, change one line of code to point at localhost, and every tool built for openai works identically. zero rewrites, zero rate limits cloud subscriptions keep getting more expensive and rate limits keep getting tighter. the people who own the box in 2026 are going to look very far ahead in 2028 bookmark this and read the article below

starmex

54,448 просмотров • 2 месяцев назад

New open-source agent harness just landed! I got early access to TrueForge by TrueFoundry and have been running it locally for the past few days. The harness layer deserves as much attention as the model, and open source matters here because you can inspect the loop, run it on your own infrastructure, and swap to the latest or cheaper models. TrueForge handles the runtime work that makes an agent reliable. It drives the tool-calling loop, manages context, coordinates subagents, and executes code in a sandbox, with any model you choose. Every tool call re-sends the growing context to the model, so in practice the harness controls most of what an agent costs to run. A few things stood out from my testing and their published benchmarks. Vendor-Neutral by design. It runs OpenAI, Anthropic, and Google models alongside open-weight models like Kimi, GLM, and DeepSeek. Model routing is a setting, and you can send each task to the model that fits it. On a 14-task enterprise agent benchmark, it matched the accuracy of Claude Managed Agents running the same Opus 4.8 model at roughly 30% lower cost per run (3.8M tokens vs 10M for the same answers). Routing the same tasks to GLM-5.2 held accuracy and brought cost down by about 75%, around $3 per run instead of $12. Fully self-hosted and Open Source (MIT License). I had it running locally with one command, with sandboxed code execution working out of the box. It's time to own your agent harness. Thanks to TrueFoundry for partnering on this post.

New open-source agent harness just landed! I got early access to TrueForge by TrueFoundry and have been running it locally for the past few days. The harness layer deserves as much attention as the model, and open source matters here because you can inspect the loop, run it on your own infrastructure, and swap to the latest or cheaper models. TrueForge handles the runtime work that makes an agent reliable. It drives the tool-calling loop, manages context, coordinates subagents, and executes code in a sandbox, with any model you choose. Every tool call re-sends the growing context to the model, so in practice the harness controls most of what an agent costs to run. A few things stood out from my testing and their published benchmarks. Vendor-Neutral by design. It runs OpenAI, Anthropic, and Google models alongside open-weight models like Kimi, GLM, and DeepSeek. Model routing is a setting, and you can send each task to the model that fits it. On a 14-task enterprise agent benchmark, it matched the accuracy of Claude Managed Agents running the same Opus 4.8 model at roughly 30% lower cost per run (3.8M tokens vs 10M for the same answers). Routing the same tasks to GLM-5.2 held accuracy and brought cost down by about 75%, around $3 per run instead of $12. Fully self-hosted and Open Source (MIT License). I had it running locally with one command, with sandboxed code execution working out of the box. It's time to own your agent harness. Thanks to TrueFoundry for partnering on this post.

elvis

11,303 просмотров • 7 дней назад

THIS SHELF OF MAC MINIS REPLACES $4,080 A YEAR IN AI SUBSCRIPTIONS 00:02 the camera pans across a shelf of stacked Mac minis and the trick is obvious: that silent little farm runs the models you rent every month most people pay 7 companies for AI and use 3 of the tools. they forget the rest on the credit card and call it a stack the Mac mini M4 ends that. one shared memory pool means a $599 box runs 7B and 8B models faster than Windows machines that cost twice as much ollama pull, one command. open webui in one docker line. point Claude Code at localhost and it just works it draws 10 to 30 watts, sits silent next to a router, and runs 24/7 for $3 a month in power it pays back a $20 ChatGPT Plus sub in 3 months, then saves you $4,000 a year while the frontier still rents you compute every month you wait is another $340 gone for compute that fits on a shelf

THIS SHELF OF MAC MINIS REPLACES $4,080 A YEAR IN AI SUBSCRIPTIONS 00:02 the camera pans across a shelf of stacked Mac minis and the trick is obvious: that silent little farm runs the models you rent every month most people pay 7 companies for AI and use 3 of the tools. they forget the rest on the credit card and call it a stack the Mac mini M4 ends that. one shared memory pool means a $599 box runs 7B and 8B models faster than Windows machines that cost twice as much ollama pull, one command. open webui in one docker line. point Claude Code at localhost and it just works it draws 10 to 30 watts, sits silent next to a router, and runs 24/7 for $3 a month in power it pays back a $20 ChatGPT Plus sub in 3 months, then saves you $4,000 a year while the frontier still rents you compute every month you wait is another $340 gone for compute that fits on a shelf

Fokki

12,933 просмотров • 2 месяцев назад