/4 Now here’s the kicker. ViralMind collected this through decentralized rewards using the Forge app. Total cost?.→ 185,000 $VIRAL distributed . Estimated dataset value?.→ $1.5M–$2.5M. That’s a 32,000x–54,000x ROI on data acquisition alone at this MC. The most efficient CUA.

/3 So what is it worth?. Let’s compare to enterprise-level Web2 data acquisition:. ✅ Video w/ synchronized actions: $0.30–$0.50 /mn.✅ Mouse & keyboard logs: $0.05–$0.10 per action.✅ Text prompts: $0.03–$0.10 each. Even conservatively, this dataset would cost:. → $1.5M to.

/2 No Synthethic data. This is:.→ real humans.→ doing real tasks.→ on real desktops.→ across >15 domains (code, paint, trading, speed, office work, etc.). Each frame. Each click. Each drag. Fully labeled. Fully replayable. This is CUA-grade data.

1/ Dataset Growth. January 2025 (:.• 7,431 min of video.• 6.2M user actions.• 38,351 text prompts.• 158 unique users. Now:.• 1.55M+ minutes of video.• 24.9M user actions.• 463,035 text prompts.• 463 users.• 9,700+ training sessions. This is a

7/ Agent-S: First integration attempt. We tested Agent-S, which offers:. -CLI interface.- CLI interface with reasoning + grounding models.-Uses UI-Tars to perform clicks-action matching.- Uses UI-Tars to perform clicks-action matching. It worked — but slowly. Test prompt: “Open.

6/ We looked at 4 projects with SDKs for this loop:. 1⃣@trycua.2⃣UI-TARS SDK.3⃣Agent-S SDK.4⃣@AnthropicAI computer-use-demo.

5/ How Agent Execution Actually Works. Once inside the virtual desktop, the agent needs to interact with it like a human would. This requires a loop made of several steps:. 1. Receive user prompt (e.g. “Open Firefox and search YouTube for Minecraft”).2. Plan a sequence of actions.

4/ First implementation: VM with Linux Desktop. ✅ Built a Linux VM image.✅ Full GUI and pre-installed agent tools.📦 5 GB compressed → 8.5 GB uncompressed.🌐 Accessible through the browser (via webview). This gives us a cross-platform agent-ready virtual desktop, embeddable.

3/ What’s available now. - @trycua runs full VMs, but only supports Apple M-series (70% of users are on Windows, 15% Mac, 5% Linux — so it’s not viable). - @AnthropicAI demo runs in containers but is still experimental. Most solutions are either too platform-dependent or not.

2/ What We Hoped For. We initially planned to integrate existing tools. But nearly all were:. ❌ Browser-focused only.❌ Locked into their own UIs.❌ A few ran full desktop agents… but had major limitations.

1/ Choosing Between VM & Container. To virtualize a desktop agent, we have 2 main options:. Full VMs (Qemu, VirtualBox).🔹 Simulate hardware → can run full desktops like Windows or Linux.🔹 More secure (hardware isolation).🔹 Heavier and slower. Containers (Docker, Podman).🔹.

You’re not just launching chatbots. You’re launching agents that perform desktop tasks. These can be tokenized and monetized. Imagine a Photoshop agent, a trading bot, a full-stack editor—each fine-tuned by you, owned by you.

How it works:. Connect wallet. Create your agent: name, supply, token symbol. Deploy -> Agent gets its own GitHub repo + UI. Metadata + token minted on Solana. UI-TARS model linked. Fine-tune your agent through the Forge.

Why a new team? . The original devs were poached by top AI companies. Instead of letting the project die, we stepped in. We're community members, holders, and experienced Web3 founders/operators. We're here to finish what was started.

8/ Where can we connect ?. As we are shaping the $VIRAL comeback & building momentum, we’ll host AMAs, share tech milestones, announce partnerships, and hang out in Telegram. We’re degens, made in the trenches, who have lived on those pixels for years. Come have a talk, anon.

7/ What's the plan ?. Phase 1: .Reunite the die-hard $VIRAL community. Decompile all tech components and workflows. Run every component together locally. integrate the proprietery data accumulated by OG team. Execute full transition. Ramp up marketing for launchpad delivery by.

6/ But who are we ?. We’re a team of 4, working full-time on this. Cumulating 20+ years in the web3 space. We have funds to run this for the next 12 months. What can we build would you ask. We’ve built a Layer 1 blockchain (UTXO model) with its own consensus, plus multiple.

5/ What about $OMNIS, the “competition” ?. We met with @_farag_ & Wassim from @Omnimind days before their launch. They seemed qualified and genuine with a clear vision. We explored merger potential and went separate ways because keeping the $VIRAL token was paramount to us, and.

4/ What is our vision?. The first launchpad for LAM agents in Web3 will be delivered within the next 4 weeks. We all know how the first launchpad for LLM agents in Web3 performed aka @virtuals_io. They created real utility for #virtuals token & their business model is.

1/ First things first, we are you. Community members from the $VIRAL project for months. Die hard believers in the potential of its use-case. Huge fans of the tech delivered. While things got ugly in the end, we couldn’t accept this would end now. We saw the.