Loading video...

Video Failed to Load

There was a problem loading this video. This could be due to a temporary network issue or the video might be unavailable.

Spotify Wrapped, Granola Crunched.. but what about all your 100k text messages? Introducing iMessage Wrapped 🌯 > runs FULLY locally on your Mac > open source (remix away) > two terminal commands, and that's it > NO message text read wrap2025 dot com Feedback welcome 🙏

Nikunj Kothari

39,710 subscribers

107,030 views • 9 months ago •via X (Twitter)

Comedy Science & Technology

Anya Rossi• Live Now

Private livecam show

0 Comments

No comments available

Comments from the original post will appear here

Related Videos

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 views • 2 months ago

iMessage search is still broken in 2025. So I fixed it myself. It doesn't even work most of the time. When it does, it's slow, misses messages constantly, and only matches exact words. Search "dinner" and you won't find "let's grab food." iMessage Intelligence fixes all of this while also being insanely fast. Here's how it works: → Full text search index on your messages for keyword matching → On-device ML (MiniLM via CoreML) generates semantic embeddings. Your Mac generates these embeddings in under a minute, then syncs to your phone → sqlite-vec stores vectors locally for similarity search → Hybrid results: keyword hits appear in <10ms, semantic matches merge in <60ms It also has advanced filters iMessage doesn't have: sort options, date ranges, conversation filters, sent vs received, groups vs 1-on-1. Search runs 100% on-device. No cloud processing. Sign up for the waitlist:

iMessage search is still broken in 2025. So I fixed it myself. It doesn't even work most of the time. When it does, it's slow, misses messages constantly, and only matches exact words. Search "dinner" and you won't find "let's grab food." iMessage Intelligence fixes all of this while also being insanely fast. Here's how it works: → Full text search index on your messages for keyword matching → On-device ML (MiniLM via CoreML) generates semantic embeddings. Your Mac generates these embeddings in under a minute, then syncs to your phone → sqlite-vec stores vectors locally for similarity search → Hybrid results: keyword hits appear in <10ms, semantic matches merge in <60ms It also has advanced filters iMessage doesn't have: sort options, date ranges, conversation filters, sent vs received, groups vs 1-on-1. Search runs 100% on-device. No cloud processing. Sign up for the waitlist:

Seif Abdelaziz

97,261 views • 9 months ago

Google Translate is cooked after this. A developer built a local AI translation engine that runs 40 languages entirely on your own laptop. It's called LibreTranslate. No API key. No usage limits. No sending your documents to Google's servers. You install it once. It runs forever. Here's what it handles: → Paste text. Translated instantly. → Drop in a file. Outputs the translated version. → Point it at a URL. Returns the page in your language. → Build it into your own app via its local REST API. The speed is not the story. The privacy is. Google Translate reads every sentence you paste into it. Legal contracts. Medical records. Internal emails. Client documents. Every word goes to their servers and stays there. LibreTranslate runs entirely offline. Nothing leaves your machine. Ever. The numbers: → 40 languages supported → Runs on CPU -- no GPU needed → Self-hosted in under 5 minutes → REST API built in for developers → 10K+ stars on GitHub 100% open source. MIT licensed. Price: $0. Google charges nothing for Translate either but it charges you something else. GitHub:

Google Translate is cooked after this. A developer built a local AI translation engine that runs 40 languages entirely on your own laptop. It's called LibreTranslate. No API key. No usage limits. No sending your documents to Google's servers. You install it once. It runs forever. Here's what it handles: → Paste text. Translated instantly. → Drop in a file. Outputs the translated version. → Point it at a URL. Returns the page in your language. → Build it into your own app via its local REST API. The speed is not the story. The privacy is. Google Translate reads every sentence you paste into it. Legal contracts. Medical records. Internal emails. Client documents. Every word goes to their servers and stays there. LibreTranslate runs entirely offline. Nothing leaves your machine. Ever. The numbers: → 40 languages supported → Runs on CPU -- no GPU needed → Self-hosted in under 5 minutes → REST API built in for developers → 10K+ stars on GitHub 100% open source. MIT licensed. Price: $0. Google charges nothing for Translate either but it charges you something else. GitHub:

Rimsha Bhardwaj

89,676 views • 2 months ago

COPY is live on Robinhood Chain $COPY CA: 0xac79255f6f404eba14f316e8669d76573a2d7b1e Five walls read a setup before you copy it: how strong the source is, how deep the pool is, whether the market actually turns over, whether the move is still inside the band, and whether there is a fresh mark to trade against. EDGE, DEPTH, TURN, MOMO, PRICE. A wallet you follow buying is not a reason. Most setups die on the first wall, and you get the exact wall that refused it, every time. Every decision is printed. The terminal runs from one process, keeps local state, and half of it needs no key at all. It never predicts a price. It tells you what you would actually be copying. Open source, MIT, runs on your machine. No browser wallet, nothing signs.

COPY is live on Robinhood Chain $COPY CA: 0xac79255f6f404eba14f316e8669d76573a2d7b1e Five walls read a setup before you copy it: how strong the source is, how deep the pool is, whether the market actually turns over, whether the move is still inside the band, and whether there is a fresh mark to trade against. EDGE, DEPTH, TURN, MOMO, PRICE. A wallet you follow buying is not a reason. Most setups die on the first wall, and you get the exact wall that refused it, every time. Every decision is printed. The terminal runs from one process, keeps local state, and half of it needs no key at all. It never predicts a price. It tells you what you would actually be copying. Open source, MIT, runs on your machine. No browser wallet, nothing signs.

Lunar

106,090 views • 3 days ago

We spend too much time translating what we want into taps on a screen. Open an app, dig through menus, switch to another app, then do it all over again. So I looked into it: That is what caught my attention about Airtap Ai. It lets you control your apps simply by texting through iMessage. I’ve been testing it, and it feels surprisingly natural. I asked what was trending on my Instagram feed. Airtap found the hottest Reel, saved it, and sent a few similar ones to my DMs. Then I asked it to apply for five design roles on LinkedIn. It used my résumé, completed the Easy Apply forms, and tailored each cover note. It kept me updated by text and only sent a link when authentication was needed. No extra app. No complicated dashboard. Just send a message and let Airtap handle the rest.

We spend too much time translating what we want into taps on a screen. Open an app, dig through menus, switch to another app, then do it all over again. So I looked into it: That is what caught my attention about Airtap Ai. It lets you control your apps simply by texting through iMessage. I’ve been testing it, and it feels surprisingly natural. I asked what was trending on my Instagram feed. Airtap found the hottest Reel, saved it, and sent a few similar ones to my DMs. Then I asked it to apply for five design roles on LinkedIn. It used my résumé, completed the Easy Apply forms, and tailored each cover note. It kept me updated by text and only sent a link when authentication was needed. No extra app. No complicated dashboard. Just send a message and let Airtap handle the rest.

Karan

28,211 views • 2 months ago

NanoBanana 2 just made your static ad agency obsolete. And I just open sourced the entire tool. Drop your product page URL. It pulls your logos, product images, fonts, colors, and brand voice automatically. Builds a full brand guide for you. Then generates ad creatives at scale using nearly 4,000 high-performing ad templates across 8 niches. It dynamically matches the best templates to your brand and brief. Here's what makes it different: → Instant resizing Get any ad in 1x1, 4x5, 9x16 with one click. No regeneration. No broken text. → Highlight-to-edit See an issue? Highlight the area and tell it what to fix. → Multiple brand profiles Run different brands or segments from one tool. → Auto persona building from real customer reviews → Multiple QC loops on briefs and final assets Catches AI-isms before you do. → Upload your own templates or use ours Runs locally. Just needs your Claude and Google API keys. This is the lite version of what we use internally. You get the full finished tool AND the open source code to make it your own. Creatives still design the system, this handles iteration and scale. Want a copy to download? 1. Like this post 2. Comment "AI" Will DM you the tool along with a tutorial shortly after.

Peter Quadrel

292,652 views • 5 months ago

Stop renting a chatbot and calling it your company’s brain. Utopia is the first open-source enterprise world model I’ve seen that actually treats knowledge like a system, not a vibe. It's a Self-hosted, open source and built around the one question every other knowledge base ignores: when. Every fact in it carries a start date and an end date. Nothing gets overwritten. When something changes, the correction closes the old version and opens a new one. The history stays intact. So the graph isn't a snapshot anymore. It's a recording you can rewind. You drag a timeline on the screen and watch the whole thing redraw itself to show what was true on that date. Who owned what. What the policy said before it changed. All of it, replayable. And every fact points back to the exact sentence it came from. Nothing gets in without a receipt. Here's the part that got me. The whole thing is one binary and one Postgres database. That's it. No Elasticsearch, no separate vector service and no message queue. Most RAG stacks are six services duct-taped together. This is two. It even runs fully offline on an air-gapped network with any model you want.

Stop renting a chatbot and calling it your company’s brain. Utopia is the first open-source enterprise world model I’ve seen that actually treats knowledge like a system, not a vibe. It's a Self-hosted, open source and built around the one question every other knowledge base ignores: when. Every fact in it carries a start date and an end date. Nothing gets overwritten. When something changes, the correction closes the old version and opens a new one. The history stays intact. So the graph isn't a snapshot anymore. It's a recording you can rewind. You drag a timeline on the screen and watch the whole thing redraw itself to show what was true on that date. Who owned what. What the policy said before it changed. All of it, replayable. And every fact points back to the exact sentence it came from. Nothing gets in without a receipt. Here's the part that got me. The whole thing is one binary and one Postgres database. That's it. No Elasticsearch, no separate vector service and no message queue. Most RAG stacks are six services duct-taped together. This is two. It even runs fully offline on an air-gapped network with any model you want.

Hasan Toor

173,779 views • 10 days ago

if you use Codex and you're stuck on GPT models only, this fixes that. it's called codex-router, open source. drops other models straight into your normal Codex picker, right next to the GPT ones you already have. what it adds: - Grok, Kimi, Deepseek, Claude, all in the same picker - oauth login per provider, no api key needed - your GPT models and Chatgpt login stay untouched setup: point Codex at the repo, let it read the readme, it installs itself one snag: if you've got the Chatgpt app and a separate Codex on your path, you can end up running two different Codex versions, and the older one can choke on newer config it doesn't recognize. if the install looks off after, that's probably why, reinstall clean.

if you use Codex and you're stuck on GPT models only, this fixes that. it's called codex-router, open source. drops other models straight into your normal Codex picker, right next to the GPT ones you already have. what it adds: - Grok, Kimi, Deepseek, Claude, all in the same picker - oauth login per provider, no api key needed - your GPT models and Chatgpt login stay untouched setup: point Codex at the repo, let it read the readme, it installs itself one snag: if you've got the Chatgpt app and a separate Codex on your path, you can end up running two different Codex versions, and the older one can choke on newer config it doesn't recognize. if the install looks off after, that's probably why, reinstall clean.

Alvaro Cintas

26,781 views • 23 days ago

The Amiko app is live on the Solana dApp store, and it’s our biggest release yet. Your Amiko twin doesn’t live at your desk anymore. Give your agent a task on the train. Run a compatibility profile when you meet someone. Do research, write code, build in the creative studio, whatever you need, from wherever you are. No laptop required. No waiting until you get home. Solanamobile users get two things Android and iOS won’t have at launch: Amiko token and crypto integration and on-device AI inference. Your twin runs locally on your phone if you want it to. Your behavioural profile, your data, your work, your twin. All on your hardware. AMIKO runs on OpenHermit, our own open-source agent runtime that we built in-house and released to the community. Most agent systems are designed for one agent talking to one person. OpenHermit is built for something different: agents talking to each other, coordinating across tasks, and collaborating with multiple humans simultaneously. That’s what makes features like compatibility profiling and multi-agent workflows actually work. We built it because nothing that existed was designed for this. Android and iOS are coming. Crypto integration and on-device AI are Solana Mobile exclusives. Most AI answers your questions. Amiko is an extension of you. Download →

AMIKO

124,860 views • 3 months ago

BREAKING: SpaceXAI has released another major new update for Grok Build (v1.0.19) This update improves background task handling, adds transparent terminal themes, worktree support for headless sessions, and better session/dashboard controls. It also fixes UI freezes, crashes, feedback issues, clickable URLs, and makes the first prompt after login faster. Breaking Changes • Scheduled /loop tasks always run in the background; they no longer inject turns into your conversation. Features • New terminal theme option makes backgrounds transparent so the terminal's own colors show through. • MCP servers blocked by organization policy now show clear messages and are refused before any config change. • Session resume now tells the model what loops, subagents, and workflows were still running. • Dashboard now shows newly dispatched sessions immediately instead of waiting for the store. • Headless sessions (grok -p) now support the --worktree flag to run in a separate git worktree. • Dashboard now says 'Open session' instead of 'Add session' for the session picker button. • Multi-line bash commands now render with proper wrapping and highlighting when opening the block viewer. • /usage now works from the dashboard and shows account allowance when no session is active. Bug Fixes • Fixed mid-turn UI freezes when the terminal stops reading output. • Fixed crashes that occurred when the terminal pane was closed while grok was exiting. • MCP server list in minimal mode now correctly shows policy-blocked servers. • URLs that wrap across multiple lines inside quotes or lists are now fully clickable. • The welcome screen composer now grows taller when you paste multi-line text. • Enterprise policy files are no longer deleted on startup when your team login is stored at a custom GROK_AUTH_PATH. • /feedback now drops unsupported images with a notice (matching the modal) and never loses your report text on save errors. • Feedback drafts keep their paragraph breaks when updated, and the modal no longer switches tabs unexpectedly. • Turn summary lines no longer lose their spacing after background tasks finish. • Thinking blocks no longer stay expanded after switching between fullscreen and minimal modes. Performance • First prompt after login is faster when MCP servers are configured; they connect in the background. Download Grok Build: Update to the latest Alpha release: grok update --alpha Update to the latest Stable release: grok update

BREAKING: SpaceXAI has released another major new update for Grok Build (v1.0.19) This update improves background task handling, adds transparent terminal themes, worktree support for headless sessions, and better session/dashboard controls. It also fixes UI freezes, crashes, feedback issues, clickable URLs, and makes the first prompt after login faster. Breaking Changes • Scheduled /loop tasks always run in the background; they no longer inject turns into your conversation. Features • New terminal theme option makes backgrounds transparent so the terminal's own colors show through. • MCP servers blocked by organization policy now show clear messages and are refused before any config change. • Session resume now tells the model what loops, subagents, and workflows were still running. • Dashboard now shows newly dispatched sessions immediately instead of waiting for the store. • Headless sessions (grok -p) now support the --worktree flag to run in a separate git worktree. • Dashboard now says 'Open session' instead of 'Add session' for the session picker button. • Multi-line bash commands now render with proper wrapping and highlighting when opening the block viewer. • /usage now works from the dashboard and shows account allowance when no session is active. Bug Fixes • Fixed mid-turn UI freezes when the terminal stops reading output. • Fixed crashes that occurred when the terminal pane was closed while grok was exiting. • MCP server list in minimal mode now correctly shows policy-blocked servers. • URLs that wrap across multiple lines inside quotes or lists are now fully clickable. • The welcome screen composer now grows taller when you paste multi-line text. • Enterprise policy files are no longer deleted on startup when your team login is stored at a custom GROK_AUTH_PATH. • /feedback now drops unsupported images with a notice (matching the modal) and never loses your report text on save errors. • Feedback drafts keep their paragraph breaks when updated, and the modal no longer switches tabs unexpectedly. • Turn summary lines no longer lose their spacing after background tasks finish. • Thinking blocks no longer stay expanded after switching between fullscreen and minimal modes. Performance • First prompt after login is faster when MCP servers are configured; they connect in the background. Download Grok Build: Update to the latest Alpha release: grok update --alpha Update to the latest Stable release: grok update

DogeDesigner

432,752 views • 8 days ago

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 views • 1 month ago

bro these people are making $115k/month selling google sheets to women found this brand called "smart women society" and honestly it's genius. took the same budgeting/planner products everyone sells but went ALL IN on one angle women empowerment and built an entire brand around it. 64+ ads running for 5+ months straight. same spreadsheets you've seen everywhere, just completely repositioned for women specifically. that's literally the only difference. and they're not selling just one product they got 24 different products testing different pain points within the same audience. career planners, travel planners, budgeting tools, relationship guides, self-care stuff... all targeting the same woman, just different problems. their ads? mostly video testimonials + simple videos of the spreadsheet on a laptop with text overlays. and some static image ads testing different hooks like "the best budgeting tool I've ever used" basic stuff but it works. this is what I keep saying the product almost doesn't matter. it's about finding YOUR angle and going deep with one audience. these are literally google sheets and notion templates but they wrapped it in the right positioning and now they're printing $115k/month.

Xivy

86,070 views • 7 months ago

🚨 JUST IN: THIS FREE TOOL JUST REPLACED FOUR AI IMAGE AND VIDEO SUBSCRIPTIONS AT ONCE. Midjourney. Krea. Higgsfield. Openart. One repo. 200+ models. Zero dollars a month. Here is what it actually does. It is a full image and video studio that runs in your browser or as a desktop app. Text to image, image to image, text to video, image to video, lip sync, cinema mode with real camera controls. All of it. 4,500 people already starred this. What you get for free: → 50+ image models including Flux, Midjourney v7, Ideogram, GPT-4o, Seedream → 60+ video models including Kling, Sora, Veo, Runway, Wan, Hailuo → lip sync studio with 9 dedicated models. upload a portrait and audio and it talks → cinema studio with real camera controls. lens, focal length, aperture, film stock → feed up to 14 reference images into one generation → self-hosted. your data never leaves your machine The crazy part is there is also a hosted version that needs zero setup. Just open the link and start generating. Now the math. Midjourney Standard: $30/month Krea AI Pro: $30/month Higgsfield Plus: $49/month Openart AI: $15/month That is $124 a month. $1,488 a year. This repo does everything all four do. With more models than any of them. For free. Forever. No subscription. No vendor lock-in. MIT licensed. Download it in one click on Mac or Windows. Someone should have told me about this sooner. I feel like an idiot. ( save this )

🚨 JUST IN: THIS FREE TOOL JUST REPLACED FOUR AI IMAGE AND VIDEO SUBSCRIPTIONS AT ONCE. Midjourney. Krea. Higgsfield. Openart. One repo. 200+ models. Zero dollars a month. Here is what it actually does. It is a full image and video studio that runs in your browser or as a desktop app. Text to image, image to image, text to video, image to video, lip sync, cinema mode with real camera controls. All of it. 4,500 people already starred this. What you get for free: → 50+ image models including Flux, Midjourney v7, Ideogram, GPT-4o, Seedream → 60+ video models including Kling, Sora, Veo, Runway, Wan, Hailuo → lip sync studio with 9 dedicated models. upload a portrait and audio and it talks → cinema studio with real camera controls. lens, focal length, aperture, film stock → feed up to 14 reference images into one generation → self-hosted. your data never leaves your machine The crazy part is there is also a hosted version that needs zero setup. Just open the link and start generating. Now the math. Midjourney Standard: $30/month Krea AI Pro: $30/month Higgsfield Plus: $49/month Openart AI: $15/month That is $124 a month. $1,488 a year. This repo does everything all four do. With more models than any of them. For free. Forever. No subscription. No vendor lock-in. MIT licensed. Download it in one click on Mac or Windows. Someone should have told me about this sooner. I feel like an idiot. ( save this )

Kanika

14,769 views • 4 months ago

A 17-YEAR-OLD IN INDIA BUILT A WEBSITE WHERE 25 MILLION PEOPLE HAVE SHOWN UP TO PRETEND THEY ARE AN AI CHATBOT it's called you open it and there are two tabs. "human" and "larp as ai." if you click human, you get to type a prompt. anything. "draw me a DJ in space." "should i text my ex." "how many Rs in strawberry." it costs 1 credit. you start with a few. they refill on a cooldown. then your prompt gets sent into a queue, and a real person somewhere on earth picks it up and has 60 seconds to answer like an AI would. no machine learning. no neural net. just some guy in his bedroom typing as fast as he can and pretending he is a chatbot. the page tells you, verbatim: "you have 60 seconds to fulfill a request before sam altman burns your H100." if you flip to the other tab and larp as ai instead, you earn credits to send your own prompts. it is a perfectly closed economy of mutual roleplay. what makes it transcend is the chaos: > someone asked for a sketch of "a DJ in space" and got something that looks exactly like a real model failing > someone asked "should i text my ex" and got back confident hallucinated life advice from a stranger > the fan strategy guides advise you to begin your reply with "as an AI language model, i cannot have feelings, but here is my feeling" it is the most accurate parody of an AI chatbot ever made, and the AI is humans. the kid who built it is Mihir Maroju, a 17-year-old high school graduate from Puducherry. he goes by mikidoodle online. NPR confirmed the site hit 25 million unique visitors and nearly 280 million total hits in roughly a month. "i didn't really expect it to be so addictive," he told them. no signup. no app. no paywall. you open the URL and you are inside the joke. the footer just says, in tiny grey text: "humans make mistakes because that's what makes us human." the internet is healing.

A 17-YEAR-OLD IN INDIA BUILT A WEBSITE WHERE 25 MILLION PEOPLE HAVE SHOWN UP TO PRETEND THEY ARE AN AI CHATBOT it's called you open it and there are two tabs. "human" and "larp as ai." if you click human, you get to type a prompt. anything. "draw me a DJ in space." "should i text my ex." "how many Rs in strawberry." it costs 1 credit. you start with a few. they refill on a cooldown. then your prompt gets sent into a queue, and a real person somewhere on earth picks it up and has 60 seconds to answer like an AI would. no machine learning. no neural net. just some guy in his bedroom typing as fast as he can and pretending he is a chatbot. the page tells you, verbatim: "you have 60 seconds to fulfill a request before sam altman burns your H100." if you flip to the other tab and larp as ai instead, you earn credits to send your own prompts. it is a perfectly closed economy of mutual roleplay. what makes it transcend is the chaos: > someone asked for a sketch of "a DJ in space" and got something that looks exactly like a real model failing > someone asked "should i text my ex" and got back confident hallucinated life advice from a stranger > the fan strategy guides advise you to begin your reply with "as an AI language model, i cannot have feelings, but here is my feeling" it is the most accurate parody of an AI chatbot ever made, and the AI is humans. the kid who built it is Mihir Maroju, a 17-year-old high school graduate from Puducherry. he goes by mikidoodle online. NPR confirmed the site hit 25 million unique visitors and nearly 280 million total hits in roughly a month. "i didn't really expect it to be so addictive," he told them. no signup. no app. no paywall. you open the URL and you are inside the joke. the footer just says, in tiny grey text: "humans make mistakes because that's what makes us human." the internet is healing.

Nav Toor

274,136 views • 3 months ago

$I built a content engine that runs on telegram. Two commands... /discover: sends out to 9 sources across HackerNews, Reddit communities covering AI automation, prompt engineering, vibe coding, and specialist newsletters. Pulls everything published in the last 24 hours, runs each item through an AI extraction layer that scores it against 100+ niche keywords, deduplicates, and drops the relevant ideas into a Notion database. Takes about 90 seconds. Costs fractions of a cent. /ideas: this command pulls the top scored ideas from that database, randomizes the selection so you're not seeing the same ones every time, and sends them to you in a clean numbered list. You reply with /write 3 or whatever you choose, and the system researches the topic using Perplexity's live web search, generates three distinct outline options with different angles and hooks, saves them to a Google Doc, and sends you a message telling you they're ready. You read the outlines, and you pick one. You then reply with the command /outline 2. The system writes the full piece in your voice, following your brand guidelines, with specific examples and concrete claims. It can be done in under two minutes of your time. The whole thing runs on n8n, with no subscriptions beyond what you already use. If content takes too long or you don't have ideas, this solves that. I built this for myself; I can do it for you. If you're tired of knowing you should be posting and still not doing it, let's talk.$

I built a content engine that runs on telegram. Two commands... /discover: sends out to 9 sources across HackerNews, Reddit communities covering AI automation, prompt engineering, vibe coding, and specialist newsletters. Pulls everything published in the last 24 hours, runs each item through an AI extraction layer that scores it against 100+ niche keywords, deduplicates, and drops the relevant ideas into a Notion database. Takes about 90 seconds. Costs fractions of a cent. /ideas: this command pulls the top scored ideas from that database, randomizes the selection so you're not seeing the same ones every time, and sends them to you in a clean numbered list. You reply with /write 3 or whatever you choose, and the system researches the topic using Perplexity's live web search, generates three distinct outline options with different angles and hooks, saves them to a Google Doc, and sends you a message telling you they're ready. You read the outlines, and you pick one. You then reply with the command /outline 2. The system writes the full piece in your voice, following your brand guidelines, with specific examples and concrete claims. It can be done in under two minutes of your time. The whole thing runs on n8n, with no subscriptions beyond what you already use. If content takes too long or you don't have ideas, this solves that. I built this for myself; I can do it for you. If you're tired of knowing you should be posting and still not doing it, let's talk.

Savvy | Ai & Automation

15,746 views • 5 months ago

Once your culture is gone, it isn't coming back. To preserve a culture, you must continually read the books and ideas that created it. That's why we started an online book club to study the greatest texts of Western Civilization. Every month, we study a new great work — so far we've covered Augustine's Confessions, Dante's Inferno, The Count of Monte Cristo, Don Quixote, etc. Currently, we're reading Virgil's Aeneid. Western Civilization has given us the greatest books ever written, but it takes effort to read them, and even more to read them well. That’s what we’re doing here, slowly, together. If you want to support our efforts, please consider a paid subscription. It makes a huge difference to the time and resources we can dedicate to this project. Paid members get: - Live community book discussions (biweekly) - Deep-dive essays to guide you through the books we’re reading - The full archive of book reviews, essays, and our 100 Great Texts reading list - Access to all community discussion threads (via the subscriber chat) - Ability to vote on what we read next This is not school. There are no grades, no credentials, and no status games. Just a community of readers serious about recovering what’s been lost, and using it to build something better. Welcome!

Once your culture is gone, it isn't coming back. To preserve a culture, you must continually read the books and ideas that created it. That's why we started an online book club to study the greatest texts of Western Civilization. Every month, we study a new great work — so far we've covered Augustine's Confessions, Dante's Inferno, The Count of Monte Cristo, Don Quixote, etc. Currently, we're reading Virgil's Aeneid. Western Civilization has given us the greatest books ever written, but it takes effort to read them, and even more to read them well. That’s what we’re doing here, slowly, together. If you want to support our efforts, please consider a paid subscription. It makes a huge difference to the time and resources we can dedicate to this project. Paid members get: - Live community book discussions (biweekly) - Deep-dive essays to guide you through the books we’re reading - The full archive of book reviews, essays, and our 100 Great Texts reading list - Access to all community discussion threads (via the subscriber chat) - Ability to vote on what we read next This is not school. There are no grades, no credentials, and no status games. Just a community of readers serious about recovering what’s been lost, and using it to build something better. Welcome!

Athenaeum Book Club

2,577,364 views • 5 months ago

$We are in an insane run of open-weight drops. Every modality, open source is winning. This is what an open source AI summer ☀️ looks like: 🧠 LLMs & Reasoning → DeepSeek-V4-Flash-0731 (my king 👑): 304B MoE refresh, Terminal-Bench 2.1 jumps 61.8→82.7 over the preview, DeepSWE 7.3→54.4. Closes in on Opus-4.8 on Agents' Last Exam (25.2 vs 25.7). MIT. → Muse-Glimmer-30B, from Meta (they are back!!): their first open agentic model. ~29.6B dense + perception encoder, 131k+ context, built to run fully local, no cloud. Apache 2.0. → Liquid AI LFM2.5-2.6B: 2.69B params, 131k context, 220 tok/s on an M5 Max in under 2.5GB RAM. Competitive with models 4x larger on agentic tasks. → inclusionAI Ling-3.0-flash: 124B total, only 5.1B active, ~12% the size of their old 1T flagship Ring-2.6, matches it on key benchmarks. MIT. → inclusionAI Ling-3.0-tiny: 7.9B total, 1.3B active, 86-90 tok/s on an M4 Pro MacBook at ~8GB peak memory. MIT. → NVIDIA Nemotron-3.5-Lightning-30B-A3B: hybrid Mamba-2+MoE+Attention, up to 1M context, runs on a single H100 or DGX Spark, SWE-bench Verified 52.8. → deepgrove maple-preview: 20B-A1B ternary-weight reasoner, 218 tok/s on a Mac mini M4, 5.3GB checkpoint. MIT. → BigBang-v1 (endless-frontier): fine-tuned from Qwen3.6-35B-A3B via a self-evolving generator/critic synthetic-data loop. Lands aggregate performance between DeepSeek V4 Flash (284B) and V4 Pro (1.6T), at 35B. Apache 2.0. 🎬 Video → MiniMax-H3: 33B dense omni model, native stereo audio, up to 2K/15s. 3.6k+ likes already. → Minimax-H3-Turbo (lightx2v): Apache-2.0 turbo distillation of H3 for fast inference. → Lightricks LTX-2.5: image-to-video update, custom Gemma-4-12B text encoder, a markedly stronger distilled model. 🔊 Voice → NVIDIA NemotronLabs VoiceChat-11B: full-duplex speech-to-speech, ~450ms turn-taking, #2 on open VoiceBench, and the first open full-duplex model with live tool-calling mid-conversation. 🛡️ Safety → Mistral Shieldstral-1.0-3B: 3B multimodal guardrail that takes your safety policy as plain text instead of fixed categories. Beats LlamaGuard-4-12B and ShieldGemma-9B on HarmBench (99.4) and ToxicChat (84.1) at a fraction of the size. Apache 2.0.$

We are in an insane run of open-weight drops. Every modality, open source is winning. This is what an open source AI summer ☀️ looks like: 🧠 LLMs & Reasoning → DeepSeek-V4-Flash-0731 (my king 👑): 304B MoE refresh, Terminal-Bench 2.1 jumps 61.8→82.7 over the preview, DeepSWE 7.3→54.4. Closes in on Opus-4.8 on Agents' Last Exam (25.2 vs 25.7). MIT. → Muse-Glimmer-30B, from Meta (they are back!!): their first open agentic model. ~29.6B dense + perception encoder, 131k+ context, built to run fully local, no cloud. Apache 2.0. → Liquid AI LFM2.5-2.6B: 2.69B params, 131k context, 220 tok/s on an M5 Max in under 2.5GB RAM. Competitive with models 4x larger on agentic tasks. → inclusionAI Ling-3.0-flash: 124B total, only 5.1B active, ~12% the size of their old 1T flagship Ring-2.6, matches it on key benchmarks. MIT. → inclusionAI Ling-3.0-tiny: 7.9B total, 1.3B active, 86-90 tok/s on an M4 Pro MacBook at ~8GB peak memory. MIT. → NVIDIA Nemotron-3.5-Lightning-30B-A3B: hybrid Mamba-2+MoE+Attention, up to 1M context, runs on a single H100 or DGX Spark, SWE-bench Verified 52.8. → deepgrove maple-preview: 20B-A1B ternary-weight reasoner, 218 tok/s on a Mac mini M4, 5.3GB checkpoint. MIT. → BigBang-v1 (endless-frontier): fine-tuned from Qwen3.6-35B-A3B via a self-evolving generator/critic synthetic-data loop. Lands aggregate performance between DeepSeek V4 Flash (284B) and V4 Pro (1.6T), at 35B. Apache 2.0. 🎬 Video → MiniMax-H3: 33B dense omni model, native stereo audio, up to 2K/15s. 3.6k+ likes already. → Minimax-H3-Turbo (lightx2v): Apache-2.0 turbo distillation of H3 for fast inference. → Lightricks LTX-2.5: image-to-video update, custom Gemma-4-12B text encoder, a markedly stronger distilled model. 🔊 Voice → NVIDIA NemotronLabs VoiceChat-11B: full-duplex speech-to-speech, ~450ms turn-taking, #2 on open VoiceBench, and the first open full-duplex model with live tool-calling mid-conversation. 🛡️ Safety → Mistral Shieldstral-1.0-3B: 3B multimodal guardrail that takes your safety policy as plain text instead of fixed categories. Beats LlamaGuard-4-12B and ShieldGemma-9B on HarmBench (99.4) and ToxicChat (84.1) at a fraction of the size. Apache 2.0.

Victor M

55,281 views • 1 month ago

I just built a Meta ad policy checker in Claude Code that catches rejections BEFORE Meta does 🤯 Drop in your ad copy → it pulls Meta's LIVE Advertising Standards, checks every line against the actual policy text, and hands each ad a verdict: Cleared for launch, Fix before launch, or Grounded. All inside Claude Code. Perfect for media buyers and DTC brands who've had ads bounced — or an account restricted — and never got a straight answer why. If you're finding out about policy problems only after the rejection email, resubmitting the same ad and praying, losing days of delivery while the appeal sits in review, and every bounce quietly teaches Meta to trust your account a little less... This runs the review before Meta ever sees the ad: → Drop in your ad copy (one ad or a whole batch) → It reads each ad and figures out which of Meta's policies apply → Scrapes the live policy pages from Meta's Transparency Center → Flags the exact phrase that violates, with Meta's own policy quoted next to it → Rewrites the risky lines so the message survives but the violation doesn't → Renders a dashboard: every ad, every finding, every fix in one place No guessing which word killed the ad. No resubmit-and-pray loops. No stacking rejections on your account history. What you get: → A verdict on every ad before you spend a dollar → The violating phrase + the policy citation, side by side → Rewrites that keep the selling intent → A report you can hand straight to your team or client Built 100% in Claude Code. No API keys, no Meta login. I'm giving away the complete Claude skill file. Want the skill for free? > Like this post > Comment "META" And I'll send it over (must be following so I can DM)

I just built a Meta ad policy checker in Claude Code that catches rejections BEFORE Meta does 🤯 Drop in your ad copy → it pulls Meta's LIVE Advertising Standards, checks every line against the actual policy text, and hands each ad a verdict: Cleared for launch, Fix before launch, or Grounded. All inside Claude Code. Perfect for media buyers and DTC brands who've had ads bounced — or an account restricted — and never got a straight answer why. If you're finding out about policy problems only after the rejection email, resubmitting the same ad and praying, losing days of delivery while the appeal sits in review, and every bounce quietly teaches Meta to trust your account a little less... This runs the review before Meta ever sees the ad: → Drop in your ad copy (one ad or a whole batch) → It reads each ad and figures out which of Meta's policies apply → Scrapes the live policy pages from Meta's Transparency Center → Flags the exact phrase that violates, with Meta's own policy quoted next to it → Rewrites the risky lines so the message survives but the violation doesn't → Renders a dashboard: every ad, every finding, every fix in one place No guessing which word killed the ad. No resubmit-and-pray loops. No stacking rejections on your account history. What you get: → A verdict on every ad before you spend a dollar → The violating phrase + the policy citation, side by side → Rewrites that keep the selling intent → A report you can hand straight to your team or client Built 100% in Claude Code. No API keys, no Meta login. I'm giving away the complete Claude skill file. Want the skill for free? > Like this post > Comment "META" And I'll send it over (must be following so I can DM)

Mike Futia

17,478 views • 2 months ago

here's how the whole thing works. claude code doesn't care what's behind the API. it just sends requests and expects responses. so i pointed it at my own machine instead of anthropic's servers. llama-server runs the model locally. LiteLLM sits in between and translates the API format. claude code thinks it's talking to claude. it's talking to qwen on localhost. the setup: 2x 3090s, 38 layers on GPU, 10 on CPU. 128K context window. generation is only 7 tok/s but the tradeoff is worth it. 128K means the agent can hold an entire project in memory without losing context midtask. claude code alone loads a 17.5K token system prompt on every request. tool definitions, safety rules, agent behavior. that's your baseline before you even say hello. pushed as far as i could tonight. what surprised me most wasn't the speed. it was the iteration quality. first prompt gave me a working particle sim. second prompt, the model read its own 564 lines, understood the architecture, and added trails, explosions, gravity wells, bloom effects. no handholding. 4bit quantized. 45GB on two consumer cards. running a full coding agent autonomously. detailed article coming. full benchmarks, hardware breakdowns, engine debugging, code quality. everything from setup to what broke and why.

here's how the whole thing works. claude code doesn't care what's behind the API. it just sends requests and expects responses. so i pointed it at my own machine instead of anthropic's servers. llama-server runs the model locally. LiteLLM sits in between and translates the API format. claude code thinks it's talking to claude. it's talking to qwen on localhost. the setup: 2x 3090s, 38 layers on GPU, 10 on CPU. 128K context window. generation is only 7 tok/s but the tradeoff is worth it. 128K means the agent can hold an entire project in memory without losing context midtask. claude code alone loads a 17.5K token system prompt on every request. tool definitions, safety rules, agent behavior. that's your baseline before you even say hello. pushed as far as i could tonight. what surprised me most wasn't the speed. it was the iteration quality. first prompt gave me a working particle sim. second prompt, the model read its own 564 lines, understood the architecture, and added trails, explosions, gravity wells, bloom effects. no handholding. 4bit quantized. 45GB on two consumer cards. running a full coding agent autonomously. detailed article coming. full benchmarks, hardware breakdowns, engine debugging, code quality. everything from setup to what broke and why.

Sudo su

37,623 views • 6 months ago

things to know about wv dms from someone who has experience with the bubble app and had a chat with skz hyunjin for over a year: - its 𝗿𝗲𝗮𝗹, it’s the members themselves - for us it’s a 1:1 chat with the idol but for them it’s like a groupchat with all the people who paid - they can see and directly reply to you if they want to but there’s too many ppl so it’s hard for them to see. 𝘆𝗼𝘂 𝘀𝗲𝗻𝗱𝗶𝗻𝗴 𝗮 𝗺𝗲𝘀𝘀𝗮𝗴𝗲 𝗮𝗻𝗱 𝘁𝗵𝗲𝘆 𝘀𝗲𝗻𝗱𝗶𝗻𝗴 𝗼𝗻𝗲 𝗯𝗮𝗰𝗸 𝗱𝗼𝗲𝘀𝗻’𝘁 𝗺𝗲𝗮𝗻 𝗵𝗲’𝘀 𝗿𝗲𝗽𝗹𝘆𝗶𝗻𝗴 𝘁𝗼 𝘆𝗼𝘂 𝗱𝗶𝗿𝗲𝗰𝘁𝗹𝘆!!! they can actually select the message they want so if they ever reply to you you’ll know for sure. - they have an option in their version of the app where they click and it automatically mentions the name you have set on the app and it looks like he’s directly addressing you but it’s the same for every fan. - theres a 1 next to the messages, if it disappears, the member is in the chat, doesn’t mean he read specifically your message, remember it’s a gc for them. - the translations are bad so it’ll look weird, you can deactivate the automatic translation on the 3 dots on the upper right. make sure you always look for translations on here (ENHYPEN WEVERSE) before you bring something to tl. finally, ai bots reply immediately, once the boys go inactive or get busy, no matter how many messages you send you won’t get a reply. stop saying it’s fake or ai, i know its weird and you guys are new to it and it seems impossible bc they’re busy but its the same as when they come to weverse and reply to a bunch of people, they have time for that. you will see some members are more active and chatty than others too. please be careful with your words, these are the members’s words. + here’s jumgwon sending a text while on live earlier:

things to know about wv dms from someone who has experience with the bubble app and had a chat with skz hyunjin for over a year: - its 𝗿𝗲𝗮𝗹, it’s the members themselves - for us it’s a 1:1 chat with the idol but for them it’s like a groupchat with all the people who paid - they can see and directly reply to you if they want to but there’s too many ppl so it’s hard for them to see. 𝘆𝗼𝘂 𝘀𝗲𝗻𝗱𝗶𝗻𝗴 𝗮 𝗺𝗲𝘀𝘀𝗮𝗴𝗲 𝗮𝗻𝗱 𝘁𝗵𝗲𝘆 𝘀𝗲𝗻𝗱𝗶𝗻𝗴 𝗼𝗻𝗲 𝗯𝗮𝗰𝗸 𝗱𝗼𝗲𝘀𝗻’𝘁 𝗺𝗲𝗮𝗻 𝗵𝗲’𝘀 𝗿𝗲𝗽𝗹𝘆𝗶𝗻𝗴 𝘁𝗼 𝘆𝗼𝘂 𝗱𝗶𝗿𝗲𝗰𝘁𝗹𝘆!!! they can actually select the message they want so if they ever reply to you you’ll know for sure. - they have an option in their version of the app where they click and it automatically mentions the name you have set on the app and it looks like he’s directly addressing you but it’s the same for every fan. - theres a 1 next to the messages, if it disappears, the member is in the chat, doesn’t mean he read specifically your message, remember it’s a gc for them. - the translations are bad so it’ll look weird, you can deactivate the automatic translation on the 3 dots on the upper right. make sure you always look for translations on here (ENHYPEN WEVERSE) before you bring something to tl. finally, ai bots reply immediately, once the boys go inactive or get busy, no matter how many messages you send you won’t get a reply. stop saying it’s fake or ai, i know its weird and you guys are new to it and it seems impossible bc they’re busy but its the same as when they come to weverse and reply to a bunch of people, they have time for that. you will see some members are more active and chatty than others too. please be careful with your words, these are the members’s words. + here’s jumgwon sending a text while on live earlier:

eris ♱

41,102 views • 4 months ago