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An AI operating system. A cloud worker that runs 24/7. Those are the two ways warmwind describes itself and both are literal, not marketing language. It’s a vision model that sees your screen and operates software the way you would: clicking, typing, navigating fully in the cloud, nothing to... show more

Ai With Piyas

46,598 subscribers

14,274 просмотров • 16 дней назад •via X (Twitter)

Anya Rossi• Live Now

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Комментарии: 28

Фото профиля warmwind

warmwind16 дней назад

let´s go

Фото профиля Liam Holt

Liam Holt16 дней назад

@warmwind_OS This is a practical take on automation. An AI that actually sees the screen and runs workflows in the cloud, without installs or APIs, is more useful than another chatbot. Worth trying the trial while slots are open.

Фото профиля Kaizen 黒

Kaizen 黒16 дней назад

@warmwind_OS Excellent

Фото профиля Javeriya Ahsan

Javeriya Ahsan16 дней назад

@warmwind_OS An AI that actually uses the mouse instead of just talking about work.

Фото профиля Web_Technify

Web_Technify15 дней назад

@warmwind_OS That’s a serious leap for AI agents.

Фото профиля Subhan Qureshi

Subhan Qureshi16 дней назад

@warmwind_OS The effort behind this deserves appreciation. Keep up the great work!

Фото профиля Mimu | AI Tools & News

Mimu | AI Tools & News16 дней назад

@warmwind_OS Amazing share , it’s really working and also helpful for automate your everyday workflow

Фото профиля Paul Sims

Paul Sims15 дней назад

@warmwind_OS Amazing Share

Фото профиля Tips Excel | AI Productivity

Tips Excel | AI Productivity16 дней назад

@warmwind_OS its good

Фото профиля Jara

Jara16 дней назад

@warmwind_OS Great

Фото профиля Kaizen 黒

Kaizen 黒16 дней назад

@warmwind_OS This is a practical take - an AI that actually sees the screen and runs the workflow in the cloud, instead of just talking about the task or waiting on APIs. Worth trying the trial while slots are still open.

Фото профиля Nihan

Nihan16 дней назад

@warmwind_OS Excellent Share

Фото профиля Elyra Future Tech

Elyra Future Tech16 дней назад

@warmwind_OS Solid concept. An AI that actually sees the screen and runs workflows in the cloud, without APIs or installs, is more useful than another chatbot. Worth trying the trial if slots are still open.

Фото профиля AI Mastery Guide

AI Mastery Guide15 дней назад

@warmwind_OS Cloud worker never clocking out

Фото профиля SantrexAI

SantrexAI16 дней назад

@warmwind_OS that's great

Фото профиля James

James16 дней назад

@warmwind_OS This sounds amazing! I'm excited to try out this new operating system.

Фото профиля Vinay Bharambe

Vinay Bharambe16 дней назад

@warmwind_OS Wow really amezing Share

Фото профиля Jessica AI

Jessica AI16 дней назад

@warmwind_OS Awesome post

Фото профиля Safwan

Safwan16 дней назад

@warmwind_OS Nice post

Фото профиля Mr. Jason💡

Mr. Jason💡16 дней назад

@warmwind_OS Wow so helpful share

Фото профиля Zayden Tech

Zayden Tech15 дней назад

@warmwind_OS Impressive share

Фото профиля Liam | AI Tools & News

Liam | AI Tools & News16 дней назад

@warmwind_OS Amazing

Фото профиля David

David16 дней назад

@warmwind_OS Gran herramienta

Фото профиля Ryan Carter

Ryan Carter16 дней назад

@warmwind_OS Thanks for sharing

Фото профиля Zakir Hossain

Zakir Hossain16 дней назад

@warmwind_OS Great share

Фото профиля sporsho

sporsho15 дней назад

@warmwind_OS That's great

Фото профиля Genius💡💹🧲 🤖

Genius💡💹🧲 🤖16 дней назад

@warmwind_OS Vision models operating software like humans feels like a massive unlock

Фото профиля Ayzaa

Ayzaa16 дней назад

@warmwind_OS Amazing

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AI assistants usually stop at giving you an answer. warmwind takes it a step further. It can click, type, navigate software, and handle repetitive workflows like a human entirely in the cloud. Teach it once, then let your cloud worker keep running 24/7. Warmwind OS is live Now. Limited capacity for free trial available. Watch the official launch video: Try Now Warmwind:👇

AI assistants usually stop at giving you an answer. warmwind takes it a step further. It can click, type, navigate software, and handle repetitive workflows like a human entirely in the cloud. Teach it once, then let your cloud worker keep running 24/7. Warmwind OS is live Now. Limited capacity for free trial available. Watch the official launch video: Try Now Warmwind:👇

Leonardo

37,645 просмотров • 15 дней назад

What if your computer didn’t just sit there waiting for you? warmwind is turning the browser into an always-on AI work environment. You show it a workflow once → it can keep running it in the cloud. For example: SAP → check data → open email → process information → update the workflow. No complicated integrations. Warmwind can visually interact with the software clicking, typing, reading, and navigating screens like a human. You teach the workflow. It keeps doing the work. Watch the official launch video: Try Warmwind:

What if your computer didn’t just sit there waiting for you? warmwind is turning the browser into an always-on AI work environment. You show it a workflow once → it can keep running it in the cloud. For example: SAP → check data → open email → process information → update the workflow. No complicated integrations. Warmwind can visually interact with the software clicking, typing, reading, and navigating screens like a human. You teach the workflow. It keeps doing the work. Watch the official launch video: Try Warmwind:

AI Club

10,479 просмотров • 17 дней назад

Run your coding agent on a local model, with QVAC. OpenCode now plugs into a model on your own machine through our official plugin. That changes two things. Privacy by default. Your repo, your prompts, and every command the agent runs stay on your device. No third-party model ever sees your code. For an agent that reads your codebase and runs commands, that is the point, not a nice-to-have. New workflows. With no meter and no rate limit, the agent does not have to stop. Let it loop on a task, refactor a whole repo overnight, or run a watch-build-fix loop that keeps going. Setup takes a few minutes: one line in opencode.json and OpenCode runs on a local QVAC model. In the video demo, it handles three real developer tasks back to back, fully offline.

Run your coding agent on a local model, with QVAC. OpenCode now plugs into a model on your own machine through our official plugin. That changes two things. Privacy by default. Your repo, your prompts, and every command the agent runs stay on your device. No third-party model ever sees your code. For an agent that reads your codebase and runs commands, that is the point, not a nice-to-have. New workflows. With no meter and no rate limit, the agent does not have to stop. Let it loop on a task, refactor a whole repo overnight, or run a watch-build-fix loop that keeps going. Setup takes a few minutes: one line in opencode.json and OpenCode runs on a local QVAC model. In the video demo, it handles three real developer tasks back to back, fully offline.

QVAC

11,382,936 просмотров • 2 месяцев назад

watch this anon. i gave NVIDIA's biggest model ever a single task. 100 minutes and 440,000 tokens later, it had rendered nothing. not one important thing on the screen. this is Nemotron 3 Ultra. 550 billion parameters, a hybrid Mamba Transformer MoE, the largest model NVIDIA has ever shipped, and they built it specifically for long-running agentic coding. so i handed it exactly that: build a 3D scene from a spec, multiple files, iterate until the tests pass. the same task a frontier model one shotted in minutes. i genuinely wanted to be impressed. it ran for an hour and forty. burned through 440,000 tokens. wrote every file, passed its own tests, and proudly printed "task complete."the browser was blank. the 3D scene never rendered. not once. and the long horizon agentic behavior was genuinely good. it stayed on task the whole hour and forty, wrote real multi-file code, drove its own tools without derailing. it just couldn't turn any of that into something that actually runs. here's the part that gets me. it's a text model, it cannot see its own output. so it sat there looping on a broken vision tool, trying to "look" at the page, hitting error after error, never once reasoning its way out. it declared victory on an empty screen because it had no way to know the screen was empty. to be fair, i genuinely don't know what quant the NIM was serving, so maybe some of that's on the serving, not the model. but the biggest model NVIDIA has ever made, on the exact task it was designed for, couldn't tell it had built nothing in 100 minutes. same task on a local model, below thread👇.

watch this anon. i gave NVIDIA's biggest model ever a single task. 100 minutes and 440,000 tokens later, it had rendered nothing. not one important thing on the screen. this is Nemotron 3 Ultra. 550 billion parameters, a hybrid Mamba Transformer MoE, the largest model NVIDIA has ever shipped, and they built it specifically for long-running agentic coding. so i handed it exactly that: build a 3D scene from a spec, multiple files, iterate until the tests pass. the same task a frontier model one shotted in minutes. i genuinely wanted to be impressed. it ran for an hour and forty. burned through 440,000 tokens. wrote every file, passed its own tests, and proudly printed "task complete."the browser was blank. the 3D scene never rendered. not once. and the long horizon agentic behavior was genuinely good. it stayed on task the whole hour and forty, wrote real multi-file code, drove its own tools without derailing. it just couldn't turn any of that into something that actually runs. here's the part that gets me. it's a text model, it cannot see its own output. so it sat there looping on a broken vision tool, trying to "look" at the page, hitting error after error, never once reasoning its way out. it declared victory on an empty screen because it had no way to know the screen was empty. to be fair, i genuinely don't know what quant the NIM was serving, so maybe some of that's on the serving, not the model. but the biggest model NVIDIA has ever made, on the exact task it was designed for, couldn't tell it had built nothing in 100 minutes. same task on a local model, below thread👇.

Sudo su

32,589 просмотров • 2 месяцев назад

Someone on Reddit built a real operating system using Claude. Not a browser app pretending to be one. An actual OS that runs on bare metal. It's called Fable-OS. The only interface is a sentence. No bash. No commands. You type what you want and an AI agent executes it through direct kernel syscalls. Everything runs in Ring 0. In the demo, the agent realized it didn't have a sound driver. So it found the Intel sound card, built a driver for it from scratch, and played a sound. On its own. The OS writes its own drivers. Evolves itself. The agent's tools are the kernel itself. Open source. Built because the developer got tired of people calling browser apps "AI operating systems." This one actually is.

Someone on Reddit built a real operating system using Claude. Not a browser app pretending to be one. An actual OS that runs on bare metal. It's called Fable-OS. The only interface is a sentence. No bash. No commands. You type what you want and an AI agent executes it through direct kernel syscalls. Everything runs in Ring 0. In the demo, the agent realized it didn't have a sound driver. So it found the Intel sound card, built a driver for it from scratch, and played a sound. On its own. The OS writes its own drivers. Evolves itself. The agent's tools are the kernel itself. Open source. Built because the developer got tired of people calling browser apps "AI operating systems." This one actually is.

Vaibhav Sisinty

20,562 просмотров • 1 месяц назад

Your AI coding agent comes with defaults: which model runs, what you pay, and what leaves your machine. You can turn those defaults into choices. In our new short course, AI Coding Workflows: From Cloud to Local, built in partnership with JetBrains and taught by Paul Everitt | @pauleveritt@fosstodon.org, Developer Advocate at JetBrains, you'll rebuild the same app across cloud, hybrid, and fully local setups. Along the way, you'll split work across subagents, put cheaper models on the routine tasks, and finish with models running on your own machine. Enroll for free:

Your AI coding agent comes with defaults: which model runs, what you pay, and what leaves your machine. You can turn those defaults into choices. In our new short course, AI Coding Workflows: From Cloud to Local, built in partnership with JetBrains and taught by Paul Everitt | @[email protected], Developer Advocate at JetBrains, you'll rebuild the same app across cloud, hybrid, and fully local setups. Along the way, you'll split work across subagents, put cheaper models on the routine tasks, and finish with models running on your own machine. Enroll for free:

DeepLearning.AI

18,674 просмотров • 1 месяц назад

IT'S NOT THAT HIS FABLE 5 IS MORE CAPABLE THAN YOURS. IT'S THAT HE LETS IT KEEP WORKING. MOST PEOPLE BUY AN AI BUILT TO OPERATE FOR DAYS THEN SHUT IT DOWN AFTER A FEW MINUTES. Nine out of ten users open a chat, assign one task, and close the window. He gives Fable 5 a long-term objective and walks away. It breaks the job into smaller pieces, delegates work to sub-agents, reviews its own outputs with vision, and keeps moving without waiting for another prompt. While you're typing your next request, his system has already finished another task and improved its workflow along the way. The agent that creates the work never decides if it's good enough. A separate evaluator checks every result, and the process repeats until the required standard is met. At $10 per million input tokens and $50 per million output tokens, you pay only for the work completed not a monthly subscription. While he was away, the system generated $7,800 worth of results. Meanwhile, others spent the week opening chats and closing tabs. Most people see a more expensive AI model. He sees an autonomous worker that handles a week's worth of tasks every single day and keeps going long after everyone else has logged off. You finished reading this. The question is whether you'll put it to work or just scroll on.

IT'S NOT THAT HIS FABLE 5 IS MORE CAPABLE THAN YOURS. IT'S THAT HE LETS IT KEEP WORKING. MOST PEOPLE BUY AN AI BUILT TO OPERATE FOR DAYS THEN SHUT IT DOWN AFTER A FEW MINUTES. Nine out of ten users open a chat, assign one task, and close the window. He gives Fable 5 a long-term objective and walks away. It breaks the job into smaller pieces, delegates work to sub-agents, reviews its own outputs with vision, and keeps moving without waiting for another prompt. While you're typing your next request, his system has already finished another task and improved its workflow along the way. The agent that creates the work never decides if it's good enough. A separate evaluator checks every result, and the process repeats until the required standard is met. At $10 per million input tokens and $50 per million output tokens, you pay only for the work completed not a monthly subscription. While he was away, the system generated $7,800 worth of results. Meanwhile, others spent the week opening chats and closing tabs. Most people see a more expensive AI model. He sees an autonomous worker that handles a week's worth of tasks every single day and keeps going long after everyone else has logged off. You finished reading this. The question is whether you'll put it to work or just scroll on.

Аnnetta

21,945 просмотров • 1 месяц назад

I tried MUZIM by OpenSoul on my Mac this week. Most “AI for your files” tools want you to upload everything into someone else’s cloud. MUZIM is different. It is a local AI for your photo and video library. Not another chatbot. Your raw files stay on your machine. I imported a messy media dump and searched the way I actually remember things. Not filenames. Vibes. I typed “that rainy cafe by the window.” It found the shot. It can even land on a moment inside a video. And after the model downloads, that kind of search keeps working offline. Then the Smart Organization kicked in. I did not rebuild folders. MUZIM built Collections on its own from the dump. Nature, outfits, travel vibes. The library went from chaos to something I could browse. The part that surprised me most is what happens next. Once the library is organized, the AI Agent helps turn it into something I can actually ship. Captions. An X thread. A short highlight concept with hooks. Cold storage becomes a private workspace. You can also plug in your own Claude or GPT key if you want cloud AI on top of local files. Still your library. Still your control. This is the kind of AI I want. More understanding. Less uploading everything to the cloud. Try it:

I tried MUZIM by OpenSoul on my Mac this week. Most “AI for your files” tools want you to upload everything into someone else’s cloud. MUZIM is different. It is a local AI for your photo and video library. Not another chatbot. Your raw files stay on your machine. I imported a messy media dump and searched the way I actually remember things. Not filenames. Vibes. I typed “that rainy cafe by the window.” It found the shot. It can even land on a moment inside a video. And after the model downloads, that kind of search keeps working offline. Then the Smart Organization kicked in. I did not rebuild folders. MUZIM built Collections on its own from the dump. Nature, outfits, travel vibes. The library went from chaos to something I could browse. The part that surprised me most is what happens next. Once the library is organized, the AI Agent helps turn it into something I can actually ship. Captions. An X thread. A short highlight concept with hooks. Cold storage becomes a private workspace. You can also plug in your own Claude or GPT key if you want cloud AI on top of local files. Still your library. Still your control. This is the kind of AI I want. More understanding. Less uploading everything to the cloud. Try it:

Robert Scoble

64,009 просмотров • 25 дней назад

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

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

Julian Goldie SEO

104,024 просмотров • 6 месяцев назад

Kimi K3 dropped 3 days ago and i already used it to build my own PUBG the model that just took the number one coding spot on earth and it runs on a free tier no team no engine i just fed it free open models and assets that are already public and told it what i wanted it built the entire game itself the shooting the recoil the hit detection all of it came straight out of the model i barely wrote a line what youre watching here is the deathmatch mode and its already live battle royale is next im deep in it and the graphics get reworked right after i know it looks raw right now i wont pretend otherwise but the endgame is a build that runs perfect on phones and the moment its on mobile you drop ads in and it earns on its own the part that still gets me is my whole cost for this was a single subscription

Kimi K3 dropped 3 days ago and i already used it to build my own PUBG the model that just took the number one coding spot on earth and it runs on a free tier no team no engine i just fed it free open models and assets that are already public and told it what i wanted it built the entire game itself the shooting the recoil the hit detection all of it came straight out of the model i barely wrote a line what youre watching here is the deathmatch mode and its already live battle royale is next im deep in it and the graphics get reworked right after i know it looks raw right now i wont pretend otherwise but the endgame is a build that runs perfect on phones and the moment its on mobile you drop ads in and it earns on its own the part that still gets me is my whole cost for this was a single subscription

savip.

68,984 просмотров • 1 месяц назад

A toy robot. A home assistant. A humanoid on a factory floor. They all need the same thing: a brain. QVAC is that brain, and it runs on the robot itself. No cloud to phone, no latency, nothing leaving your home. The intelligence is on the machine, so it keeps thinking even with the internet off. The robots are coming. This is what wakes them up:

A toy robot. A home assistant. A humanoid on a factory floor. They all need the same thing: a brain. QVAC is that brain, and it runs on the robot itself. No cloud to phone, no latency, nothing leaving your home. The intelligence is on the machine, so it keeps thinking even with the internet off. The robots are coming. This is what wakes them up:

QVAC

5,250,097 просмотров • 2 месяцев назад

YOUR OLD ANDROID PHONE IS A FREE AI VISION SERVER AND YOU DON’T KNOW IT one dev built an app that turns any android into a local openai-compatible LLM server with vision support, analyzes camera feeds entirely on-device, no cloud, no subscriptions, nothing leaves your network you already own the hardware, it’s just sitting in a drawer full breakdown below ↓

YOUR OLD ANDROID PHONE IS A FREE AI VISION SERVER AND YOU DON’T KNOW IT one dev built an app that turns any android into a local openai-compatible LLM server with vision support, analyzes camera feeds entirely on-device, no cloud, no subscriptions, nothing leaves your network you already own the hardware, it’s just sitting in a drawer full breakdown below ↓

leopardracer

21,844 просмотров • 2 месяцев назад

Cyber defense is entering the superintelligence era. ⚡ Introducing the CrowdStrike Cyber Superintelligence Lab, the first frontier AI research organization built for cyberdefense and AI safety. The Lab delivers CrowdStrike SafeMind, a family of purpose-built security models and harnesses. SafeMind runs as one system designed to deliver AI safety: an offensive model that finds the attack path, a defensive model that closes it, and the harnesses that operate both in the same loop. Built using NVIDIA Nemotron open models and using CoreWeave’s AI Cloud for training and inference, SafeMind goes beyond AI that simply identifies threats, it defeats them. Learn more:

Cyber defense is entering the superintelligence era. ⚡ Introducing the CrowdStrike Cyber Superintelligence Lab, the first frontier AI research organization built for cyberdefense and AI safety. The Lab delivers CrowdStrike SafeMind, a family of purpose-built security models and harnesses. SafeMind runs as one system designed to deliver AI safety: an offensive model that finds the attack path, a defensive model that closes it, and the harnesses that operate both in the same loop. Built using NVIDIA Nemotron open models and using CoreWeave’s AI Cloud for training and inference, SafeMind goes beyond AI that simply identifies threats, it defeats them. Learn more:

CrowdStrike

57,771 просмотров • 12 дней назад

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

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

AshutoshShrivastava

17,696 просмотров • 6 месяцев назад

Marketing agents are the NEW coding agents. It's code in the cloud that makes decisions off your live business data on a loop. It researches, acts, reads the results, improves, and goes again. Picture an agent that runs your entire Facebook ad account by itself. It researches your customer's pain points, generates on-brand creative, publishes it, kills the losers, scales the winners, and makes more of whatever's working. We show you the EXACT stack. Perplexity to scrape Reddit for real pain points, Nano Banana for on-brand static creative, a vision model to check it against brand guidelines, HeyGen for AI UGC video, all wired into a loop that reads Facebook's data and reacts. Now point it at a business. What are some startup ideas you can point marketing agents to? WordPress runs 43% of the internet. Take the plugins people already pay for, like Yoast, WooCommerce, and WP Forms, and build the AI-first version of each. Examples: Yoast (~$15M ARR) shows you red and green dots and tells you to fix your SEO yourself. The AI version just does it. Proven demand, no AI-native competition, and thousands of site owner pay agenices $1,000 a month and many wish they'd pay less and got more. Coding agents changed who gets to build software. Marketing agents change who gets to grow a company. Full breakdown on The Startup Ideas Podcast (SIP) 🧃. Thanks to Cody Schneider for the sauce. Will break down more marketing agents if people are interested? Just LMK. Watch. I'm rooting for you and happy growing. I think we've heard a lot about coding agents recently. And we're about to hear a lot more about marketing agents.

GREG ISENBERG

132,662 просмотров • 1 месяц назад

Dear ICP community, the Internet Computer has now been running strong for 5 years 👏👏👏 Here is a celebratory preview of ICP "cloud engines," the sovereign frontier cloud technology the network shall soon provide from Main points: — Cloud engines enable anyone to spin up their own sovereign frontier cloud. The technology involves an extraordinary inventive step, in which cloud is created from a mathematically secure network of nodes. The nodes run as part of the Internet Computer network ( but are selected and configured by the cloud engine's owner. — The frontier cloud provided by engines is strongly focused on enabling AI agents to build and update online applications and services for us. The world is changing fast, and nearly all new online apps and services are already being built with the help of AI, and thus cloud engines target the future of cloud. — Software hosted on cloud engines is tamperproof, which means that it is immune to infrastructure hacks, because it runs inside a mathematically secure network protocol, rather than on computers directly. This means that AI agents, and those building with them, don't need to have a security team in the loop, or to trust someone else's security team. This is crucial, because in the future, non technical people will demand the freedom to build with full automation — where they just need to issue instructions to AI about what to build, and don't need to worry about anything or anyone else. Of course, apps and services running on engines are also vastly safer from the new breed of hacker being enabled by frontier AI. (The cloud engines themselves are also "tamperproof." Even if a hacker gains physical access to some portion of a cloud engine's nodes, and can make arbitrary changes, the computations and data of the hosted apps and services cannot be corrupted or interrupted so long as the network's fault bounds aren't exceeded. The recent hack of Vercel, a major cloud platform, which gave hackers access to the apps it hosted, provides additional perspective on the importance of this advantage.) — Software hosted on cloud engines is guaranteed to run, so long as a sufficient number of the engine's nodes are running. This means that AI can build applications and services without the need to have a human systems admin team constantly tinkering with the underlying platform to keep it running, which is again crucial, because in the future, non technical people will expect the freedom to use AI to build without the support of others. — New frontier programming language technology, in the form of the Motoko language developed by Caffeine Labs, leverages seminal "orthogonal persistence" technology that unifies program logic and data to deliver further unlocks for AI (Motoko is the first computer language being developed that targets agents that are writing software rather than humans engineers per se). Nowadays, AI can build and update production apps at a prodigious rate, even at the speed of conversation. But it can also make mistakes, and there's a risk that an update it creates might be "lossy" in the sense it causes some transformed data to be lost. Again, in this new world, it's both undesirable and impractical for everyone to have to have a systems admin team on-hand to detect lossy updates and roll them back, but Motoko provides a solution: it can detect new software updates are lossy before they are applied, reducing potentially catastrophic errors by AI to harmless coding retries. — Software hosted on cloud engines is "serverless" but unlike traditional serverless software, directly it directly incorporates data through "orthogonal persistence." Another key purpose is simplify backend software logic and fuel the modeling power of AI by increasing abstraction (sorry for the technical language!!!). Put simply, this enables AI to produce more sophisticated backends, faster, and at dramatically lower costs, as measured by the number AI API tokens consumed during coding. (Tip for the technical: orthogonal persistence is a new paradigm where "the program is the database," and data lives inside program variables, which is possible because it's as if hosted software runs forever in persistent memory). — An expanding database of skills at shall make it possible to develop and directly deploy apps and services to your cloud engines directly from Claude Code, Perplexity, Codex and other AI platforms. Further, your account on can be connected, so that new apps and updates created through conversation automatically appear hosted from your cloud engine. In the future, R&D is going to be very seamless. You converse with AI, and your secure and unstoppable apps or services are created or updated. Cloud engines are designed to directly support this "self-writing cloud" future where we can work hands-free. — Tech sovereignty is becoming a huge issue worldwide, with governments and corporations seeking to create sovereign tech stacks owing to geopolitical tensions. Increasingly, people are realizing that tech provided by foreign nations can come with hidden backdoors and kills switches, from the base platform, right up through hosted apps and services. ICP technology is open source, and those building on ICP using AI own their own source code. When you have the source code, you can verify that there are no backdoors, and when you own the source code thanks to AI, you can update it at will, freeing you from vendor lock-in. But cloud engines take sovereignty much further... — You create a cloud engine by selecting the nodes that will be combined. You can choose the class of nodes used, and their number, but more importantly, you can choose who operates the nodes, and where they are located. Almost any configuration is possible, because the Internet Computer scales the security privileges afforded to hosted software within the network according to configuration (software hosted on cloud engines can directly interoperate with software on other engines and traditional subnets, but base restrictions are applied according to security rules). A cloud engine can be created within a region such as Europe, to comply with regs such as GDPR, or completely within a sovereign state like Switzerland or Pakistan. But cloud engines go further still... — Sovereignty is also about freedom from vendor lock-in. Cloud engines are essentially ICP (Internet Computer Protocol) network configurations, and this means the underlying compute nodes they combine can be swapped out without interrupting their hosted apps and services. This is a big deal. In addition, cloud engines now support nodes that are instances running on Big Tech's clouds, in addition to nodes that are dedicated specialized hardware, as per the Gen I and Gen II nodes that dominate the Internet Computer today. For example, it is possible to have an engine running across different AWS data centers, say, and then reconfigure the engine to run across a mixture of AWS, Google, Azure and Hetzner for even more resilience, without the users of hosted apps and services noticing a thing. That's true freedom. — Sovereign AI is becoming increasingly important too, and cloud engines allow special "AI nodes" to be added to them, so that hosted software can perform inference on hardware provisioned by the owner from a location the owner has selected. Even though the AI nodes are only accessible within the cloud engine, they can still benefit from the forthcoming Internet Intelligence Gateway (IG), which will make it possible to validate inference performed on key frontier open weights LLMs, even when the inference is performed on completely independent AI clouds. When the results of inference are received, this technology can verify that neither the prompt+context (input) nor the inference result (output) have been modified, and that the results were produced by the precise LLM expected. This ensures that AI clouds don't cheat by running inference on cheaper models than are being paid for, and bad actors aren't modifying the inputs or outputs to surreptitiously insert advertising into results, say, or change facts, or insert malware when code is being generated. What's super cool about this technology is the cost of the verification is scalable. A very valuable additional security can be achieved with only 1-2% of extra cost. — Scaling apps and services when they hit capacity limits is another thorny problem that cloud engines help the world address. Engines make scaling possible without rewriting or reconfiguring software. The query workload capacity of hosted software can be horizontally scaled simply by adding new nodes to an engine, and nodes can also be added in geographical proximity to demand. Meanwhile, update workload capacity can first be scaled-up by swapping an engine's nodes out for the next class up, and then when no larger class of node is available, horizontally scaled-out by "splitting" the engine into two, which doubles available capacity. (Technical tip: horizontally scaling update capacity by splitting engines requires multi-canister architectures). — For those who have been following how Caffeine builds apps that can efficiently store large numbers of files, I should mention that apps built on cloud engines will also support the new ICP Blob Storage cloud network (since cloud engines currently have up to about 3 TB of memory, which apps storing large amounts of files can easily exceed). We are also working on allowing blob storage nodes to be added to cloud engines, to enable sovereign mass blob storage within an engine, similarly to how AI nodes can be added currently. — Lastly, but certainly not least, I should mention that cloud engines are multi-blockchain capable, and ready for digital assets, thanks to the clever math at their core. For example, an e-commerce service built on a cloud engine can securely accept and custody stablecoin payments, or a multi-chain DEX could be hosted. Further, engines can support software autonomy (software orchestrated and controlled by other autonomous software, in a decentralized way) and can themselves be orchestrated by SNS technology, and thus run autonomously too. Today, though, the focus is on *mainstream* cloud. This year, the cloud industry will generate approximately one trillion dollars in revenue. That number is already huge, but is expected to grow to two trillion dollars by 2030. After years of continuous development, which have seen more than $500m spent on R&D, the Internet Computer network is now tacking directly toward this mainstream cloud market with cloud engine technology. In their first version, cloud engines are not meant to be a cloud panacea. For example, currently they are not ideal for working with big data. You should use something like DataBricks for that. Cloud engines are carefully targeted at enabling AI to produce traditional online applications and services, including SaaS, in a safer and more productive way, which represents a new market segment with tremendous potential. Of course, DFINITY will continue to work relentlessly to push forward ICP's capabilities, so expect further developments. It's worth mentioning that this cloud segment isn't just about creating new apps and services using AI, it's also about replacing legacy systems and apps built on super expensive SaaS services. Caffeine Labs is working to produce technology (Caffeine Snorkel) that can study an enterprise's legacy systems and app built on SaaS, create replacement systems and apps, and migrate the data, while supporting key stakeholders through the process over email and chat, with full automation. Thus the legacy systems and SaaS markets shall also be addressed by cloud engines. Zooming out, and reasoning in a more metaphysical way, we believe, as we always have, that there is room for a new kind of cloud created by mathematical networks, that provides seminal advances in the fields of security and resilience, as well as true sovereignty and freedom from lock-in. That this same technology, with the help of additional technologies like orthogonal persistence and Motoko, enables AI to build for us without the need for so much oversight, and to create more backend sophistication while consuming fewer AI API tokens, enables ICP to bring game-changing advances to the world. Cloud engines will work synergistically with the Intelligence Gateway, which will enable apps and services running on engines to seamlessly leverage AI, wherever that AI is running, while providing verifiability at extremely low cost for open weights frontier models. We believe that cloud engines represent an inflection point in the storied history of the Internet Computer project, and I'm very proud to be sharing the details with you on the network's fifth birthday 💪 I'll be back with more news soon!!

Dear ICP community, the Internet Computer has now been running strong for 5 years 👏👏👏 Here is a celebratory preview of ICP "cloud engines," the sovereign frontier cloud technology the network shall soon provide from Main points: — Cloud engines enable anyone to spin up their own sovereign frontier cloud. The technology involves an extraordinary inventive step, in which cloud is created from a mathematically secure network of nodes. The nodes run as part of the Internet Computer network ( but are selected and configured by the cloud engine's owner. — The frontier cloud provided by engines is strongly focused on enabling AI agents to build and update online applications and services for us. The world is changing fast, and nearly all new online apps and services are already being built with the help of AI, and thus cloud engines target the future of cloud. — Software hosted on cloud engines is tamperproof, which means that it is immune to infrastructure hacks, because it runs inside a mathematically secure network protocol, rather than on computers directly. This means that AI agents, and those building with them, don't need to have a security team in the loop, or to trust someone else's security team. This is crucial, because in the future, non technical people will demand the freedom to build with full automation — where they just need to issue instructions to AI about what to build, and don't need to worry about anything or anyone else. Of course, apps and services running on engines are also vastly safer from the new breed of hacker being enabled by frontier AI. (The cloud engines themselves are also "tamperproof." Even if a hacker gains physical access to some portion of a cloud engine's nodes, and can make arbitrary changes, the computations and data of the hosted apps and services cannot be corrupted or interrupted so long as the network's fault bounds aren't exceeded. The recent hack of Vercel, a major cloud platform, which gave hackers access to the apps it hosted, provides additional perspective on the importance of this advantage.) — Software hosted on cloud engines is guaranteed to run, so long as a sufficient number of the engine's nodes are running. This means that AI can build applications and services without the need to have a human systems admin team constantly tinkering with the underlying platform to keep it running, which is again crucial, because in the future, non technical people will expect the freedom to use AI to build without the support of others. — New frontier programming language technology, in the form of the Motoko language developed by Caffeine Labs, leverages seminal "orthogonal persistence" technology that unifies program logic and data to deliver further unlocks for AI (Motoko is the first computer language being developed that targets agents that are writing software rather than humans engineers per se). Nowadays, AI can build and update production apps at a prodigious rate, even at the speed of conversation. But it can also make mistakes, and there's a risk that an update it creates might be "lossy" in the sense it causes some transformed data to be lost. Again, in this new world, it's both undesirable and impractical for everyone to have to have a systems admin team on-hand to detect lossy updates and roll them back, but Motoko provides a solution: it can detect new software updates are lossy before they are applied, reducing potentially catastrophic errors by AI to harmless coding retries. — Software hosted on cloud engines is "serverless" but unlike traditional serverless software, directly it directly incorporates data through "orthogonal persistence." Another key purpose is simplify backend software logic and fuel the modeling power of AI by increasing abstraction (sorry for the technical language!!!). Put simply, this enables AI to produce more sophisticated backends, faster, and at dramatically lower costs, as measured by the number AI API tokens consumed during coding. (Tip for the technical: orthogonal persistence is a new paradigm where "the program is the database," and data lives inside program variables, which is possible because it's as if hosted software runs forever in persistent memory). — An expanding database of skills at shall make it possible to develop and directly deploy apps and services to your cloud engines directly from Claude Code, Perplexity, Codex and other AI platforms. Further, your account on can be connected, so that new apps and updates created through conversation automatically appear hosted from your cloud engine. In the future, R&D is going to be very seamless. You converse with AI, and your secure and unstoppable apps or services are created or updated. Cloud engines are designed to directly support this "self-writing cloud" future where we can work hands-free. — Tech sovereignty is becoming a huge issue worldwide, with governments and corporations seeking to create sovereign tech stacks owing to geopolitical tensions. Increasingly, people are realizing that tech provided by foreign nations can come with hidden backdoors and kills switches, from the base platform, right up through hosted apps and services. ICP technology is open source, and those building on ICP using AI own their own source code. When you have the source code, you can verify that there are no backdoors, and when you own the source code thanks to AI, you can update it at will, freeing you from vendor lock-in. But cloud engines take sovereignty much further... — You create a cloud engine by selecting the nodes that will be combined. You can choose the class of nodes used, and their number, but more importantly, you can choose who operates the nodes, and where they are located. Almost any configuration is possible, because the Internet Computer scales the security privileges afforded to hosted software within the network according to configuration (software hosted on cloud engines can directly interoperate with software on other engines and traditional subnets, but base restrictions are applied according to security rules). A cloud engine can be created within a region such as Europe, to comply with regs such as GDPR, or completely within a sovereign state like Switzerland or Pakistan. But cloud engines go further still... — Sovereignty is also about freedom from vendor lock-in. Cloud engines are essentially ICP (Internet Computer Protocol) network configurations, and this means the underlying compute nodes they combine can be swapped out without interrupting their hosted apps and services. This is a big deal. In addition, cloud engines now support nodes that are instances running on Big Tech's clouds, in addition to nodes that are dedicated specialized hardware, as per the Gen I and Gen II nodes that dominate the Internet Computer today. For example, it is possible to have an engine running across different AWS data centers, say, and then reconfigure the engine to run across a mixture of AWS, Google, Azure and Hetzner for even more resilience, without the users of hosted apps and services noticing a thing. That's true freedom. — Sovereign AI is becoming increasingly important too, and cloud engines allow special "AI nodes" to be added to them, so that hosted software can perform inference on hardware provisioned by the owner from a location the owner has selected. Even though the AI nodes are only accessible within the cloud engine, they can still benefit from the forthcoming Internet Intelligence Gateway (IG), which will make it possible to validate inference performed on key frontier open weights LLMs, even when the inference is performed on completely independent AI clouds. When the results of inference are received, this technology can verify that neither the prompt+context (input) nor the inference result (output) have been modified, and that the results were produced by the precise LLM expected. This ensures that AI clouds don't cheat by running inference on cheaper models than are being paid for, and bad actors aren't modifying the inputs or outputs to surreptitiously insert advertising into results, say, or change facts, or insert malware when code is being generated. What's super cool about this technology is the cost of the verification is scalable. A very valuable additional security can be achieved with only 1-2% of extra cost. — Scaling apps and services when they hit capacity limits is another thorny problem that cloud engines help the world address. Engines make scaling possible without rewriting or reconfiguring software. The query workload capacity of hosted software can be horizontally scaled simply by adding new nodes to an engine, and nodes can also be added in geographical proximity to demand. Meanwhile, update workload capacity can first be scaled-up by swapping an engine's nodes out for the next class up, and then when no larger class of node is available, horizontally scaled-out by "splitting" the engine into two, which doubles available capacity. (Technical tip: horizontally scaling update capacity by splitting engines requires multi-canister architectures). — For those who have been following how Caffeine builds apps that can efficiently store large numbers of files, I should mention that apps built on cloud engines will also support the new ICP Blob Storage cloud network (since cloud engines currently have up to about 3 TB of memory, which apps storing large amounts of files can easily exceed). We are also working on allowing blob storage nodes to be added to cloud engines, to enable sovereign mass blob storage within an engine, similarly to how AI nodes can be added currently. — Lastly, but certainly not least, I should mention that cloud engines are multi-blockchain capable, and ready for digital assets, thanks to the clever math at their core. For example, an e-commerce service built on a cloud engine can securely accept and custody stablecoin payments, or a multi-chain DEX could be hosted. Further, engines can support software autonomy (software orchestrated and controlled by other autonomous software, in a decentralized way) and can themselves be orchestrated by SNS technology, and thus run autonomously too. Today, though, the focus is on mainstream cloud. This year, the cloud industry will generate approximately one trillion dollars in revenue. That number is already huge, but is expected to grow to two trillion dollars by 2030. After years of continuous development, which have seen more than $500m spent on R&D, the Internet Computer network is now tacking directly toward this mainstream cloud market with cloud engine technology. In their first version, cloud engines are not meant to be a cloud panacea. For example, currently they are not ideal for working with big data. You should use something like DataBricks for that. Cloud engines are carefully targeted at enabling AI to produce traditional online applications and services, including SaaS, in a safer and more productive way, which represents a new market segment with tremendous potential. Of course, DFINITY will continue to work relentlessly to push forward ICP's capabilities, so expect further developments. It's worth mentioning that this cloud segment isn't just about creating new apps and services using AI, it's also about replacing legacy systems and apps built on super expensive SaaS services. Caffeine Labs is working to produce technology (Caffeine Snorkel) that can study an enterprise's legacy systems and app built on SaaS, create replacement systems and apps, and migrate the data, while supporting key stakeholders through the process over email and chat, with full automation. Thus the legacy systems and SaaS markets shall also be addressed by cloud engines. Zooming out, and reasoning in a more metaphysical way, we believe, as we always have, that there is room for a new kind of cloud created by mathematical networks, that provides seminal advances in the fields of security and resilience, as well as true sovereignty and freedom from lock-in. That this same technology, with the help of additional technologies like orthogonal persistence and Motoko, enables AI to build for us without the need for so much oversight, and to create more backend sophistication while consuming fewer AI API tokens, enables ICP to bring game-changing advances to the world. Cloud engines will work synergistically with the Intelligence Gateway, which will enable apps and services running on engines to seamlessly leverage AI, wherever that AI is running, while providing verifiability at extremely low cost for open weights frontier models. We believe that cloud engines represent an inflection point in the storied history of the Internet Computer project, and I'm very proud to be sharing the details with you on the network's fifth birthday 💪 I'll be back with more news soon!!

dom | icp

310,509 просмотров • 4 месяцев назад

one half of this keynote sells you the cloud forever, the other half shows the chip that lets you stop renting it this is the other half, AMD's CEO holding the chip in her hand 00:00 - Lisa Su introduces the Ryzen AI Halo, a system built for local AI 00:29 - the line that matters, it runs models up to 200 billion parameters locally, not connected to anything 00:42 - a 200 billion parameter model, the tier of the top paid AI plans, on a desktop that fits in your hand so the cloud wants $200 a month, forever, for access you never own this is the box that runs the same class of model with nothing leaving the room that is the whole point of my breakdown, the $200 a month was never the intelligence, it was the meter and the meter just became optional most people will see a spec demo the part that matters is what it lets you stop paying for full breakdown below

one half of this keynote sells you the cloud forever, the other half shows the chip that lets you stop renting it this is the other half, AMD's CEO holding the chip in her hand 00:00 - Lisa Su introduces the Ryzen AI Halo, a system built for local AI 00:29 - the line that matters, it runs models up to 200 billion parameters locally, not connected to anything 00:42 - a 200 billion parameter model, the tier of the top paid AI plans, on a desktop that fits in your hand so the cloud wants $200 a month, forever, for access you never own this is the box that runs the same class of model with nothing leaving the room that is the whole point of my breakdown, the $200 a month was never the intelligence, it was the meter and the meter just became optional most people will see a spec demo the part that matters is what it lets you stop paying for full breakdown below

John Doe

25,960 просмотров • 3 месяцев назад

Today, we launched browser use inside Codex to further close the build & verify loop for local development! Now, you can ask Codex to build your front end, and test it like a user would by clicking through the app. Codex sees everything a user sees through vision & checks the network/console logs to help debug & fix any issues that it finds. This change brings us closer to fully autonomous coding agents that delivers high quality and tested changes. Watch Codex test my app in the browser, catch & fix a real bug, and doing that loop again with a brand new feature.

James Sun

226,907 просмотров • 4 месяцев назад

this shouldn't be legal Elon's team just dropped an app where you record yourself doing a boring task once and it does that task for you from then on. no prompt. it's called Grok Bot. SpaceX is paying $60,000,000,000 for the people who built it and it costs you $0 if you already pay for SuperGrok Heavy set it up in 3 moves: 1. make a bot, open its computer, hit "teach a task" 2. do the boring job once while it watches, that recording becomes a skill 3. put the skill on a schedule and it runs without you the free week burns in 20 minutes. save this before you waste yours

this shouldn't be legal Elon's team just dropped an app where you record yourself doing a boring task once and it does that task for you from then on. no prompt. it's called Grok Bot. SpaceX is paying $60,000,000,000 for the people who built it and it costs you $0 if you already pay for SuperGrok Heavy set it up in 3 moves: 1. make a bot, open its computer, hit "teach a task" 2. do the boring job once while it watches, that recording becomes a skill 3. put the skill on a schedule and it runs without you the free week burns in 20 minutes. save this before you waste yours

Argona

103,961 просмотров • 1 месяц назад

META launches a new feature that will allow Facebook and Instagram to continuously scan all your photos and video and upload them to their cloud “Facebook is now using AI to scan every single photo and video within your phone — This is terrifying. Not only are they scanning those photos and videos, but then they're uploading it to the cloud continuously. It's operating continuously in the background scanning those photos to figure out the time of day, the location, the other people in your photos, that it can determine what it thinks you should post” The scanning happens on-device using AI models for suggestions, but Meta can upload and process data to the cloud when you interact It’s in opt in feature, so make sure to never opt in and if you have make sure to opt out The service is called ‘Camera Roll Sharing Suggestions’

META launches a new feature that will allow Facebook and Instagram to continuously scan all your photos and video and upload them to their cloud “Facebook is now using AI to scan every single photo and video within your phone — This is terrifying. Not only are they scanning those photos and videos, but then they're uploading it to the cloud continuously. It's operating continuously in the background scanning those photos to figure out the time of day, the location, the other people in your photos, that it can determine what it thinks you should post” The scanning happens on-device using AI models for suggestions, but Meta can upload and process data to the cloud when you interact It’s in opt in feature, so make sure to never opt in and if you have make sure to opt out The service is called ‘Camera Roll Sharing Suggestions’

Wall Street Apes

219,433 просмотров • 2 месяцев назад