💥 Gate Square Event: #PostToWinCC 💥
Post original content on Gate Square related to Canton Network (CC) or its ongoing campaigns for a chance to share 3,334 CC rewards!
📅 Event Period:
Nov 10, 2025, 10:00 – Nov 17, 2025, 16:00 (UTC)
📌 Related Campaigns:
Launchpool: https://www.gate.com/announcements/article/48098
CandyDrop: https://www.gate.com/announcements/article/48092
Earn: https://www.gate.com/announcements/article/48119
📌 How to Participate:
1️⃣ Post original content about Canton (CC) or its campaigns on Gate Square.
2️⃣ Content must be at least 80 words.
3️⃣ Add the hashtag #PostTo
Noticed something wild lately - certain AI models like Sonnet 4.5 can apparently keep running for over 30 hours straight, and Codex isn't far behind with its extended operation windows. Got me wondering about the architecture behind this.
Anyone come across research papers or technical docs that dig into how these systems sustain such long inference sessions? Curious whether it's about model architecture innovations, infrastructure optimization, or something entirely different. Would love to see what the research community is saying about this capability.