After VVV, I’ll be focusing on the infrastructure side of privacy AI. VVV @AskVenice — most of you have likely participated in or heard about this project. As the leading decentralized AI frontend chat tool, it emphasizes local user data storage, no prompt logging, and no content censorship. ✅ Directly competes with AI giants like ChatGPT and Claude ✅ Its core selling points — privacy-first, uncensored, decentralized — have been widely embraced by users, naturally driving the $VVV token up more than tenfold from its lows, with a fully diluted valuation reaching billions of dollars This clearly demonstrates that privacy is a necessity in today’s AI landscape — no one wants to freely hand over their data to large AI companies like ChatGPT. At this pivotal moment, Arcium @Arcium, the leading decentralized confidential computing network, is preparing for its TGE, introducing a groundbreaking product: Arcium enables encrypted training and inference for enterprises and developers while preserving privacy. Arcium’s use cases include: ① Encrypted AI Training: Enterprises can collaboratively train models without exposing their raw datasets (e.g., medical, health, financial data) ② Encrypted Inference: Businesses can run models on private data, receiving outputs without revealing inputs or model weights ③ Applications: Privacy-preserving personalized AI, development of DeFAI (decentralized AI agents), and more If VVV provides ordinary users with access to privacy-focused AI, then Arcium @Arcium delivers the foundational infrastructure for privacy across the entire AI ecosystem.