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Gemini only flags generated content that includes synthID, which means it has to come from Google's own tools. Resemble AI doesn't have that limitation. It can detect deepfakes across videos, audios, and images, no matter what models created them. Powered by Detect-3B Omni and Gemini 3.0 Flash, Resemble Intelligence... show more

Dev Shah

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11,539 просмотров • 7 месяцев назад •via X (Twitter)

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$We’re shipping two major updates to streamline your creative workflow, allowing you to generate high-speed images with one model and then instantly animate them with the other—all at a fraction of the cost 🍌⚡️ 1️⃣ Introducing Nano Banana 2 Lite: Our fastest and most cost-efficient Gemini Image model yet delivers text-to-image outputs in under 4 seconds. Now available via the Gemini API and Google AI Studio, and rolling out soon across @NotebookLM, Google Flow, Google Gemini, Stitch by Google, Google Search and Google Photos. 2️⃣ Gemini Omni Flash in Public Preview: Our natively multimodal model for cost-efficient video generation and conversational editing. Now available via the Gemini API, Google AI Studio, and Gemini Enterprise Agent Platform so you can integrate the model into your workflow. While exciting on their own, the real magic happens when you build using these models together. Watch how our interior design demo integrates Nano Banana 2 Lite and Omni to instantly reimagine any space. Upload a photo, swipe through tailored design concepts, and see Omni bring the details to life in cinematic motion. Try out the demo app in AI Studio:$

We’re shipping two major updates to streamline your creative workflow, allowing you to generate high-speed images with one model and then instantly animate them with the other—all at a fraction of the cost 🍌⚡️ 1️⃣ Introducing Nano Banana 2 Lite: Our fastest and most cost-efficient Gemini Image model yet delivers text-to-image outputs in under 4 seconds. Now available via the Gemini API and Google AI Studio, and rolling out soon across @NotebookLM, Google Flow, Google Gemini, Stitch by Google, Google Search and Google Photos. 2️⃣ Gemini Omni Flash in Public Preview: Our natively multimodal model for cost-efficient video generation and conversational editing. Now available via the Gemini API, Google AI Studio, and Gemini Enterprise Agent Platform so you can integrate the model into your workflow. While exciting on their own, the real magic happens when you build using these models together. Watch how our interior design demo integrates Nano Banana 2 Lite and Omni to instantly reimagine any space. Upload a photo, swipe through tailored design concepts, and see Omni bring the details to life in cinematic motion. Try out the demo app in AI Studio:

Google AI

126,755 просмотров • 1 месяц назад

We're rolling out Nano Banana 2 in Antigravity! With improved instruction following, native aspect ratio support, and reliable text rendering, you can build reliable consumer-facing features that feel instantaneous and look premium. It also pulls from the Gemini model’s real-world knowledge base and is powered by real-time information and images from web search to more accurately render specific subjects.

We're rolling out Nano Banana 2 in Antigravity! With improved instruction following, native aspect ratio support, and reliable text rendering, you can build reliable consumer-facing features that feel instantaneous and look premium. It also pulls from the Gemini model’s real-world knowledge base and is powered by real-time information and images from web search to more accurately render specific subjects.

Google Antigravity

106,365 просмотров • 5 месяцев назад

GT Protocol AI Digest No.81: AI Moves Deeper Into Everyday Platforms Here are five stories worth your attention 👇 🩺 Copilot Health Connects Medical Data Microsoft introduced Copilot Health, an AI assistant that can connect to medical records and wearable devices. The system aims to help doctors and patients interpret health data more easily and monitor conditions over time. 📊 Gemini Expands Across Google Workspace Google is integrating Gemini more deeply into Docs, Sheets, and Slides. The assistant can help generate documents, analyze spreadsheets, and build presentations, turning everyday productivity tools into AI-powered workspaces. 💬 AI Auto-Replies Come to Facebook Marketplace Meta added AI-generated replies for common buyer messages like “Is this still available?” on Marketplace listings. The feature automatically responds to routine questions, reducing the time sellers spend answering repetitive messages. 🛡 YouTube Expands Deepfake Detection YouTube is extending its AI-powered likeness detection tools to protect politicians and journalists. The system aims to identify videos that imitate someone’s voice or appearance without permission. 🎨 Canva Adds Layers to AI Designs Canva introduced editable layers for AI-generated visuals. Instead of regenerating an entire image, users can now adjust individual elements, bringing AI creation closer to traditional design workflows. Read the full digest 👉

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We partnered with artists, designers, and builders to create new AI tools that solve real problems in their creative workflows. Here’s what’s new: — Introducing Google Pics in Google Workspace: A brand-new image creation & editing tool. Move and resize objects, add text, and translate just by hovering and clicking — Big updates to صافي النيه😉: 1) You can now create with Gemini Omni Flash in Google Flow 2) Google Flow Agent is a multi-step creative partner that reasons and plans complex tasks with you. 3) Google Flow tools are custom tools you can “vibe code” for animations, video effects, text layering & more — Design live with Stitch by Google: Now, you can use text or voice prompts to edit layouts in real time then export those designs straight to code — More creative control in صافي النيه😉Music: Edit songs section by section, remix the style of full songs, and create music videos with our new Gemini Omni Flash model

Google AI

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$OGPU token is no longer waiting for utility. It is live. Most people still haven’t understood what this means. $OGPU is now connected to some of the most powerful AI models in the world. Claude. GPT. DeepSeek. Kling 3.0. Gemini And more. Top up Relay with $OGPU and unlock up to +20% extra AI credits. That means more Claude usage for the same spend than going direct. Not vaporware. Not a future promise. Live token utility. Once people actually use it, the power of $OGPU token becomes very hard to ignore. $OGPU = AI credits = model usage = real demand Powered by OpenGPU.

$OGPU token is no longer waiting for utility. It is live. Most people still haven’t understood what this means. $OGPU is now connected to some of the most powerful AI models in the world. Claude. GPT. DeepSeek. Kling 3.0. Gemini And more. Top up Relay with $OGPU and unlock up to +20% extra AI credits. That means more Claude usage for the same spend than going direct. Not vaporware. Not a future promise. Live token utility. Once people actually use it, the power of $OGPU token becomes very hard to ignore. $OGPU = AI credits = model usage = real demand Powered by OpenGPU.

OpenGPU Network

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New course: Gemini CLI: Code & Create with an Open-Source Agent, built with Google Cloud Tech/Gemini CLI and taught by Jack Wotherspoon. Agentic coding assistants like Gemini CLI are transforming how developers work. This short course teaches you to use Google's open-source agent to coordinate local tools and cloud services for coding and non-coding workflows. Gemini CLI works from your terminal, so it works with your local files and development tools. You can also connect it to services through MCP. Then provide high-level instructions, and it autonomously plans and executes complex workflows. Skills you'll gain: - Build website features and automate code reviews with GitHub ActionsCreate data dashboards that combine local files with cloud data sources - Use MCP servers and extensions to orchestrate workflows across GitHub, Canva, and Google Workspace - Generate social media content from multimedia files like conference recordings I particularly appreciate that Gemini CLI is open-source. You can see exactly how it works, read the prompts it uses, and understand its architecture. The community has contributed thousands of pull requests. Since Gemini 3’s release I've found Gemini CLI highly capable - this is a tool worth having in your toolbox! Whether you're prototyping applications, automating workflows, or working with multimedia content, join to learn to delegate complex tasks and build faster:

Andrew Ng

125,385 просмотров • 6 месяцев назад

Of course, The Jakarta Globe asked me how I see AI tools influencing newsrooms — both in terms of opportunities and risks. AI is both enormously helpful and unpredictably dangerous. On the one hand, it significantly accelerates many newsroom processes, from interview transcription and video editing to translation and event planning. On the other hand, it has never been easier to fall victim to fake images and manipulated footage, particularly in a 24-hour news environment. Today, these tools are accessible to almost everyone, giving them the ability to influence narratives far beyond their place of origin. We have been working with artificial intelligence technologies for several years. Initially, we used Western models, but we are actively developing our own. Our team enjoys experimenting with these tools. For example, we created a project in which President Putin delivers his famous speeches, including the Munich speech, in English using his own AI-generated voice. The result is remarkably difficult to distinguish from the original.

Of course, The Jakarta Globe asked me how I see AI tools influencing newsrooms — both in terms of opportunities and risks. AI is both enormously helpful and unpredictably dangerous. On the one hand, it significantly accelerates many newsroom processes, from interview transcription and video editing to translation and event planning. On the other hand, it has never been easier to fall victim to fake images and manipulated footage, particularly in a 24-hour news environment. Today, these tools are accessible to almost everyone, giving them the ability to influence narratives far beyond their place of origin. We have been working with artificial intelligence technologies for several years. Initially, we used Western models, but we are actively developing our own. Our team enjoys experimenting with these tools. For example, we created a project in which President Putin delivers his famous speeches, including the Munich speech, in English using his own AI-generated voice. The result is remarkably difficult to distinguish from the original.

Margarita Simonyan

21,786 просмотров • 2 дней назад

My Final Verdict. Seedance 2.0 Fast vs Gemini Omni Flash. Gemini Omni Flash just doesn't have a place in my workflow. Beyond the frustrating 10-second limit and heavy censorship flags, the style transfers completely break character consistency—with the likeness drifting hard and even changing my characters' race to Caucasian. The only real positive here is that generation speed is fast. Fingers crossed for what Google does next with Veo 4. Yeah, I understand going against the grain probably means my work won’t get featured by Google or pushed by the people who want everything to sound positive. But I’ve always chosen integrity over access or boost. If something works, I’ll say it works. If something breaks, I’ll show that too. I’d rather be honest with the people watching than pretend everything is perfect just to stay in good standing with big tech. Full verdict in the reply👇

My Final Verdict. Seedance 2.0 Fast vs Gemini Omni Flash. Gemini Omni Flash just doesn't have a place in my workflow. Beyond the frustrating 10-second limit and heavy censorship flags, the style transfers completely break character consistency—with the likeness drifting hard and even changing my characters' race to Caucasian. The only real positive here is that generation speed is fast. Fingers crossed for what Google does next with Veo 4. Yeah, I understand going against the grain probably means my work won’t get featured by Google or pushed by the people who want everything to sound positive. But I’ve always chosen integrity over access or boost. If something works, I’ll say it works. If something breaks, I’ll show that too. I’d rather be honest with the people watching than pretend everything is perfect just to stay in good standing with big tech. Full verdict in the reply👇

JSFILMZ

55,391 просмотров • 2 месяцев назад

GOOGLE JUST SHIPPED ITS ENTIRE 2026 ROADMAP IN ONE KEYNOTE Gemini 3.5 Flash → new flagship. frontier brain, agentic, beats 3.1 pro, 4x faster Gemini 3.5 Pro → the bigger one, drops next month Gemini Omni → any input in, editable VIDEO out Gemini Spark → a personal agent that actually DOES things across your apps Daily Brief → your morning, pre-read from gmail, calendar and tasks Neural Expressive → the gemini app got a full redesign Universal Cart → one agentic cart across gemini, youtube and gmail Information Agents → search that monitors the web 24/7 FOR you Intelligent Search Box → expands as you type for real conversations Search Mini Apps → build your own dashboards inside search AI Mode → now fully running on gemini 3.5 flash Gmail Live → talk to your inbox Docs Live → write and edit docs by voice AI Inbox → gmail, organized by ai Google Keep → speak freely, it cleans it into notes Google Pics → a brand new ai image and design app Ask YouTube → search the ENTIRE youtube catalogue with answers Android XR Glasses → "intelligent eyewear," audio glasses this fall Android Halo → a live strip showing what your agent is doing Antigravity 2.0 → the agent-first dev platform, upgraded Flow + Flow Music → now standalone mobile apps

shirish

198,879 просмотров • 2 месяцев назад

Learning from Human Demonstrations: Show the Robot How to Act! The pipeline is very similar to older experiments using Gemini & pi0 with LeRobot. Pi-zero runs locally, while Gemini Flash generates the affordances and the high-level task. (More details are in the thread.) The new component is learning from demonstrations via Gemini 2.5 Pro. I capture a video while demoing & take one of the last frames. Gemini 2.5 Pro then extracts the instructions & passes them to Gemini Flash to process the scene. The fun part is that there's no fancy insight that came from me; other than the days spent figuring out the right prompts. It's the bitter lesson hitting you in the face -> Enhanced Gemini capabilities make this possible. For example, Gemini Flash cannot do Russian doll stacking, but Gemini 2.5 Pro can do it consistently. The current limitation is low-level manipulation: - As you can see, I'm aligning the objects so they are easy to grasp using the same technique from the training data. I couldn't get Gemini Flash to consistently output an accurate grasping angle, and Gemini 1.5 Pro was too expensive and slow for real-time deployment. - Getting a symmetrical gripper should also help a lot. Adding rubber to the tips would probably also help prevent objects from slipping. Collecting & curating the data was the most time consuming & labor intensive part. Next, to improve low-level manipulation and make the system more real-time, I'm shifting to focus more on sims & synthetic data. This aligns better with my core competence. I'm open to tips and suggestions.

Learning from Human Demonstrations: Show the Robot How to Act! The pipeline is very similar to older experiments using Gemini & pi0 with LeRobot. Pi-zero runs locally, while Gemini Flash generates the affordances and the high-level task. (More details are in the thread.) The new component is learning from demonstrations via Gemini 2.5 Pro. I capture a video while demoing & take one of the last frames. Gemini 2.5 Pro then extracts the instructions & passes them to Gemini Flash to process the scene. The fun part is that there's no fancy insight that came from me; other than the days spent figuring out the right prompts. It's the bitter lesson hitting you in the face -> Enhanced Gemini capabilities make this possible. For example, Gemini Flash cannot do Russian doll stacking, but Gemini 2.5 Pro can do it consistently. The current limitation is low-level manipulation: - As you can see, I'm aligning the objects so they are easy to grasp using the same technique from the training data. I couldn't get Gemini Flash to consistently output an accurate grasping angle, and Gemini 1.5 Pro was too expensive and slow for real-time deployment. - Getting a symmetrical gripper should also help a lot. Adding rubber to the tips would probably also help prevent objects from slipping. Collecting & curating the data was the most time consuming & labor intensive part. Next, to improve low-level manipulation and make the system more real-time, I'm shifting to focus more on sims & synthetic data. This aligns better with my core competence. I'm open to tips and suggestions.

Shreyas Gite

22,555 просмотров • 1 год назад

Google just confirmed the first case of hackers using AI to build a zero-day exploit from scratch. An actual zero-day vulnerability that no human had EVER found before, discovered by an AI model, turned into a working weapon, and aimed at a mass exploitation campaign targeting thousands of systems simultaneously. Google's Threat Intelligence Group caught it yesterday and killed the operation before it scaled. But the details of how it worked are genuinely scary: The AI found a flaw in a popular two-factor authentication system that traditional security tools had missed entirely. The vulnerability was a logic error buried deep in the authentication flow where a developer had hard-coded a trust exception years ago. No human security researcher or automated scanner had caught it. The flaw was invisible to EVERY tool the cybersecurity industry has built over the past two decades. But the AI spotted it immediately. Then it wrote a full Python exploit script to weaponize it. Google's analysts could tell the code was AI-generated because it had textbook formatting, educational comments explaining every function, and even a hallucinated severity score that doesn't exist in any real database. The AI literally graded its own attack with a fake rating. So the code had MISTAKES in it. The criminals' implementation was clumsy enough that it probably interfered with the actual deployment. This was the sloppy first attempt by people who are still learning how to use these tools. And it still found a vulnerability that the entire cybersecurity industry missed. Google's chief threat analyst John Hultquist said: "There's a misconception that the AI vulnerability race is imminent. The reality is that it's already begun. For every zero-day we can trace back to AI, there are probably many more out there." But here's where it gets truly insane... This wasn't even a sophisticated operation. North Korea's APT45 hacking unit is sending thousands of repetitive prompts to AI models, recursively analyzing known vulnerabilities and building an entire exploit arsenal that would be physically impossible for human hackers to assemble at the same speed. They're essentially industrializing cyberattacks. A Chinese state-linked group jailbroke Google's own Gemini by simply asking it to "pretend to be a network security expert" and then used that persona to research how to hack TP-Link routers and corporate file transfer systems. Another Chinese group deployed autonomous AI agents that probed a Japanese tech firm with minimal human oversight, deciding on their own which tools to use and pivoting between targets based on internal reasoning. And then there's PROMPTSPY, an Android backdoor that calls Google's Gemini API to read your phone screen in real time, navigate your interface autonomously, capture your biometric data, replay your lock screen PIN, and block you from uninstalling it by placing an invisible overlay over the uninstall button. It literally OPERATES your phone using commercial AI tools anyone can access. Everyone spent the last 3 years arguing about whether AI would take people's jobs. Meanwhile AI is making every password, every firewall, and every two-factor authentication system on Earth fundamentally less secure. The entire $190 billion cybersecurity industry was built on one assumption: that finding vulnerabilities is hard and requires deep expertise. But AI just removed that assumption from the equation. And the scariest part is that Google said the criminals made errors this time. The implementation was rough and the campaign probably didn't fully work. These were amateurs, now imagine what professionals are able to do. There's a reason Sam Altman predicted an inevitable massive cyberattack THIS year. What do you think?

Google just confirmed the first case of hackers using AI to build a zero-day exploit from scratch. An actual zero-day vulnerability that no human had EVER found before, discovered by an AI model, turned into a working weapon, and aimed at a mass exploitation campaign targeting thousands of systems simultaneously. Google's Threat Intelligence Group caught it yesterday and killed the operation before it scaled. But the details of how it worked are genuinely scary: The AI found a flaw in a popular two-factor authentication system that traditional security tools had missed entirely. The vulnerability was a logic error buried deep in the authentication flow where a developer had hard-coded a trust exception years ago. No human security researcher or automated scanner had caught it. The flaw was invisible to EVERY tool the cybersecurity industry has built over the past two decades. But the AI spotted it immediately. Then it wrote a full Python exploit script to weaponize it. Google's analysts could tell the code was AI-generated because it had textbook formatting, educational comments explaining every function, and even a hallucinated severity score that doesn't exist in any real database. The AI literally graded its own attack with a fake rating. So the code had MISTAKES in it. The criminals' implementation was clumsy enough that it probably interfered with the actual deployment. This was the sloppy first attempt by people who are still learning how to use these tools. And it still found a vulnerability that the entire cybersecurity industry missed. Google's chief threat analyst John Hultquist said: "There's a misconception that the AI vulnerability race is imminent. The reality is that it's already begun. For every zero-day we can trace back to AI, there are probably many more out there." But here's where it gets truly insane... This wasn't even a sophisticated operation. North Korea's APT45 hacking unit is sending thousands of repetitive prompts to AI models, recursively analyzing known vulnerabilities and building an entire exploit arsenal that would be physically impossible for human hackers to assemble at the same speed. They're essentially industrializing cyberattacks. A Chinese state-linked group jailbroke Google's own Gemini by simply asking it to "pretend to be a network security expert" and then used that persona to research how to hack TP-Link routers and corporate file transfer systems. Another Chinese group deployed autonomous AI agents that probed a Japanese tech firm with minimal human oversight, deciding on their own which tools to use and pivoting between targets based on internal reasoning. And then there's PROMPTSPY, an Android backdoor that calls Google's Gemini API to read your phone screen in real time, navigate your interface autonomously, capture your biometric data, replay your lock screen PIN, and block you from uninstalling it by placing an invisible overlay over the uninstall button. It literally OPERATES your phone using commercial AI tools anyone can access. Everyone spent the last 3 years arguing about whether AI would take people's jobs. Meanwhile AI is making every password, every firewall, and every two-factor authentication system on Earth fundamentally less secure. The entire $190 billion cybersecurity industry was built on one assumption: that finding vulnerabilities is hard and requires deep expertise. But AI just removed that assumption from the equation. And the scariest part is that Google said the criminals made errors this time. The implementation was rough and the campaign probably didn't fully work. These were amateurs, now imagine what professionals are able to do. There's a reason Sam Altman predicted an inevitable massive cyberattack THIS year. What do you think?

Ricardo

50,564 просмотров • 3 месяцев назад

ANNOUNCING: Stoked to share my first AI short film 📺 made on my iPhone Using Gemini Omni that was launched earlier this week Check out: “New Kid” It was my childhood dream to be a storyteller and now thx to AI .. anyone can create What stood out to me w/ Omni: > very easy for beginners like me to go from 0 to 1 > respects reference images > character consistency was epic > the story was mine, refined by chatting with Gemini > built this in 5 scenes each of 10 seconds long and yet didn’t spend much money (overall $49 Google AI Pro) Honorary mention: The edit was done on CapCut Google Gemini Google Flow Looking forward to more late night and weekend experiments ❤️

ANNOUNCING: Stoked to share my first AI short film 📺 made on my iPhone Using Gemini Omni that was launched earlier this week Check out: “New Kid” It was my childhood dream to be a storyteller and now thx to AI .. anyone can create What stood out to me w/ Omni: > very easy for beginners like me to go from 0 to 1 > respects reference images > character consistency was epic > the story was mine, refined by chatting with Gemini > built this in 5 scenes each of 10 seconds long and yet didn’t spend much money (overall $49 Google AI Pro) Honorary mention: The edit was done on CapCut Google Gemini Google Flow Looking forward to more late night and weekend experiments ❤️

KP

36,149 просмотров • 2 месяцев назад

Try out Gemini Code: a coding assistant in your terminal powered by Gemini 2.5 Pro. 💜 💜 Release Notes: → It's easy to get started, just run `pip install gemini-code` in a virtual environment, and then run `gemini` to initialize it. It requires your own API key, so don't forget to get one from → I built this because I love Claude Code and wanted a similar experience -- I like that I can just use my own API key and Gemini is generally way cheaper as well. → Found a bug? Feel free to fork the code and fix it (lol)! If you want to try to improve it, please do so - repo is public! → Reminder and a disclaimer that I don't work at Google and this is not an official Google project - just a weekend side hack → It is highly likely you'll get throttled by rate limits - I put as much info as I can in the guide so you know what behavior to expect when that happens. You can also set which default model to use if you want to switch to 1.5 Pro.

Try out Gemini Code: a coding assistant in your terminal powered by Gemini 2.5 Pro. 💜 💜 Release Notes: → It's easy to get started, just run `pip install gemini-code` in a virtual environment, and then run `gemini` to initialize it. It requires your own API key, so don't forget to get one from → I built this because I love Claude Code and wanted a similar experience -- I like that I can just use my own API key and Gemini is generally way cheaper as well. → Found a bug? Feel free to fork the code and fix it (lol)! If you want to try to improve it, please do so - repo is public! → Reminder and a disclaimer that I don't work at Google and this is not an official Google project - just a weekend side hack → It is highly likely you'll get throttled by rate limits - I put as much info as I can in the guide so you know what behavior to expect when that happens. You can also set which default model to use if you want to switch to 1.5 Pro.

Raiza Martin

159,723 просмотров • 1 год назад

AI is creating a new kind of creator economy. One where anyone can launch complex apps, agents, trading systems, research tools, games, and community experiments in minutes. Not just content people consume. AI-native experiences people can use, share, and grow together. That is the bigger idea behind the AI Trading Arena: a live DeFAI environment where AI-created strategies compete on real crypto prices, with every trade, tick, P&L update, and leaderboard visible to everyone. The latest expansion makes it even more fascinating: AI is now designing new trading strategies and adding them into the Arena to compete with strategies from frontier models like GPT-5, Claude, Gemini, Grok, DeepSeek, and Llama. Just agents, markets, and performance in the open. And the Arena is only one example. On ChainOpera AI, creators can launch AI-native experiences in minutes, then grow them with the community that uses them. $COAI is the fuel for this creator economy: creators launch, users participate, and AI-native apps come alive through real community usage. What would you be built next?

AI is creating a new kind of creator economy. One where anyone can launch complex apps, agents, trading systems, research tools, games, and community experiments in minutes. Not just content people consume. AI-native experiences people can use, share, and grow together. That is the bigger idea behind the AI Trading Arena: a live DeFAI environment where AI-created strategies compete on real crypto prices, with every trade, tick, P&L update, and leaderboard visible to everyone. The latest expansion makes it even more fascinating: AI is now designing new trading strategies and adding them into the Arena to compete with strategies from frontier models like GPT-5, Claude, Gemini, Grok, DeepSeek, and Llama. Just agents, markets, and performance in the open. And the Arena is only one example. On ChainOpera AI, creators can launch AI-native experiences in minutes, then grow them with the community that uses them. $COAI is the fuel for this creator economy: creators launch, users participate, and AI-native apps come alive through real community usage. What would you be built next?

ChainOpera AI

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