Swarms v.7.8.0 Launch

Holy coook!! 500k Whales know to put noties on me👀 Teleportation to millions. Locked in🔐 某交易平台 season 某用户 printing bangers. Reminds me of Solana during November/December of last year with Griffain, JellyJelly, Neur, Swarms, etc Millionaires being made

Someone asked me about a chart request on $SWARMS, so I highlighted this chart to showcase our strategy for spotting market bottoms. Right now, price action is holding between the 0.786 and 1 Fibonacci levels. This is typically the zone where you want to accumulate an asset after it experiences listing pullbacks not at the peak when everyone is euphoric. Our idea here is purely based on liquidity, nothing else. I’m not concerned about what the project does or doesn’t do; the focus is strictly on liquidity flows. From this point, liquidity signals a potential move to the upside. For SWARMS, the first upside target is around $0.08, followed by a pullback, and then potentially a blow-off top between $0.24 and $0.62. In the best-case scenario, it could even sweep its previous all-time high. With only a $20M market cap, this asset appears extremely undervalued, and I believe buyers are about to step in soon. Bottom formation / Rounding bottom

#SWARMS# has left

In Brief Renlabs has launched Torus on mainnet, introducing a hypergraph-based network that enables autonomous agents to self-organize into swarms, coordinate tasks, and operate with reduced DAO oversight, testing a new model of decentralized intelligence. Research and development group Renlabs

Unibase claims to be the first high-performance Decentralized AI Memory Layer, aimed at providing long-term memory and cross-platform collaboration capabilities for AI agents. Its core mission is to solve the current dilemma of AI agents "forgetting" everything after task completion by endowing them with memory, collaboration, and self-evolution capabilities through Blockchain technology. 01 What is Unibase? Decoding the Decentralization AI Memory Layer Unibase is a high-performance decentralized memory layer built for AI agents, providing verifiable, composable, and settlement-capable memory and collaboration capabilities through an innovative tech stack. In simple terms, Unibase aims to make AI more human-like—capable of remembering past learning and interactions, and continuously growing based on that. The project consists of three core stacks.