361°🔆🐬TermMax
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昨天币安上线新项目可以呀,一觉醒来,感觉都要笑醒了,有点crypto summer的感觉了。🤣

Every scaled network needs a way to coordinate the participants who depend on it. The ARC whitepaper explores how ARC could serve as the native coordination asset of the Arc network, aligning users, builders, validators, and institutions around long-term network health. arc.network/blog/introduci…




Arc 🤝 Dynamic @dynamic_xyz is delivering seamless onboarding and authentication infrastructure for developers building on Arc. This gives builders the tools to create intuitive user experiences without giving up self-custody. → Embedded wallets and signing flows → Customizable social and email onboarding → Flexible wallet infrastructure built for scale Arc is built for adoption. Designed for real users from day one.

Our recent @lablabai hackathon with @GoogleDeepMind brought in 227 submissions exploring what becomes possible when AI agents, APIs, content, and real-world services can all be monetized with sub-cent USDC payments on Arc. What stood out across the builds: → Agent-to-agent payments and autonomous economic activity → Pay-per-call APIs, content, and intelligence → Real-time settlement for trading, oracle, and security workflows → New monetization models for creators, researchers, and developers The quality and breadth of submissions made it clear that programmable dollars and nanopayments are unlocking new internet business models. Congrats to the winners below. On-site 1st Prize: Vertex Dynamic Ad Exchange A new kind of ad exchange where autonomous buyer and seller agents bid at sub-cent levels and settle impressions in real time. Demo: lablab.ai/ai-hackathons/… On-site 2nd Prize: Gyasss A pay-per-query oracle where AI agents pay $0.001 per gas price query and users can earn USDC back for reporting data. Demo: lablab.ai/ai-hackathons/… On-site 3rd Prize: MEV Shield A paid market intelligence tool that analyzes live blockchain transactions and alerts traders to risky activity before a trade is executed. Demo: lablab.ai/ai-hackathons/… Online 1st Prize: Cairn A nanopayment environmental oracle where community sensor operators get paid per verified weather, air quality, and seismic reading. Demo: lablab.ai/ai-hackathons/… Online 2nd Prize: StreamArc A pay-per-second video platform where viewers pay only for what they watch and creators earn instantly. Demo: lablab.ai/ai-hackathons/…

Arc Hackathon Spotlight: Chariot Chariot is an Arc Hackathon Spotlight project exploring how lending infrastructure can work across chains with ETH-backed collateral, vault logic, and automated risk controls. Join @samconnerone and Sipho Yawe live on May 7 at 11:00 AM ET for a walkthrough of the build: → ETHEscrow to BridgedETH → ERC-4626 vault design → Liquidation logic and circuit breakers → Vault agent architecture See how hackathon projects on Arc turn into real, composable financial infrastructure. RSVP: community.arc.network/public/events/…





首富整天把“卖房买比特币”的故事挂在嘴边。但这个事情的真相到底是什么?当年买这套房子的首付款从哪里来?卖掉的又是谁的房子? 在用这件事证明自己英明伟大、反复拿来炫耀的时候,有没有想过,当年心疼女儿女婿、如今已经年迈的岳父母的感受? 有很多事情我从未对外提及,甚至连回忆都懒得去回忆。因为落井下石、或者用他人的私生活进行道德绑架,从来不是我的行为准则。若不是那本充满谎言的书无端把我牵扯进来,我也不会再提这些陈年旧事。


Crypto量化+预测市场,这8个开源项目就是你的自动印钞机(代码版)。 从CEX到DEX到预测市场,自动化交易的全套武器库👇 1️⃣ 全自动AI交易助手 NOFX,由@Web3Tinkle推动,AI自主选模型、抓数据、执行策略,支持Binance、OKX、Hyperliquid等主流CEX/DEX。真正的AI自己炒币。 🔗 github.com/NoFxAiOS/nofx 2️⃣ 加密货币交易机器人 Freqtrade,Python写的策略机器人,内置回测引擎+机器学习参数优化,Telegram/网页端随时管理。上手门槛最低的量化入口。 🔗 github.com/freqtrade/freq… 3️⃣ 高频交易策略框架 Hummingbot,专注高频,CEX和DEX同时支持,做市、套利、网格策略自动化,适合想跑高频的玩家。 🔗 github.com/hummingbot/hum… 4️⃣ 高性能量化交易框架 Nautilus Trader,Python+Rust双引擎,低延迟高吞吐,内置回测+实盘模块,多交易所支持。性能控的终极选择。 🔗 github.com/nautechsystems… 5️⃣ 交易所统一接入库 CCXT,一套API对接100+交易所,量化策略和套利机器人的行业标准底层库。⚠️ 注意:之前被曝出抽佣问题,实际使用建议审查并重写相关源码。 🔗 github.com/ccxt/ccxt 6️⃣ Polymarket官方SDK py-clob-client,封装完整的限价订单簿API,查行情、挂单、撤单,想在Polymarket上跑自动化交易的起点。 🔗 github.com/Polymarket/py-… 7️⃣ 预测市场历史数据集 目前公开可用的最大规模Polymarket+Kalshi历史数据,配套数据采集框架和分析工具,做策略回测的基础素材。 🔗 github.com/Jon-Becker/pre… 8️⃣ 预测市场统一交易库 pmxt,一套API打通Polymarket、Kalshi、Limitless等多平台,跨预测市场量化交易的标准接口。 🔗 github.com/pmxt-dev/pmxt ⚠️ 以上工具仅供学习研究,自动化交易有风险,亏钱了别怪GitHub。






