与「CryptoGem」相关的搜索结果

Keeping a close eye on $FLIK - Flickabic (sol) The branding is clean, the narrative is easy to understand, and the team is already teasing utility while still in the early stages. Most projects talk — few actually build. Currently sitting at low Mc with 64% bonding curve. If development continues and the community keeps growing, $FLIK could attract much more attention in the coming weeks. CA: 53DzwArXGL4wAqxCraDEUZSN9AgnuWwxKSmtFeu6pump #Solana# #Memecoin# #FLIK# #CryptoGem# 👀🔥

📺NFTv #02📺# NFTゲームの歴史や注目のゲームなどをご紹介していくノンファンジブルな90分！お見逃しなく！ ＜MC＞ 山田耕三（NFT Producer） NF-Teruko ＜GUEST＞ 小澤孝太 (CryptoGames株式会社 代表取締役) 石田晴香 (女優・eスポーツプレイヤー・声優・タレント)

这个 Grok Bot 跑出来的收益，确实有点夸张 我让 Grok Bot 的全自动交易终端运行了一整晚，期间持续自主执行交易。初始本金只有 69.67 美元，睡醒后账户余额已经达到 13,370 美元 整个过程我没有手动干预过任何一笔订单 只需要充值、启动自动交易，后续的机会筛选、进场时机、仓位管理，以及按照预设风控执行止盈止损，都交给机器人完成 我把这套 AI 自动交易系统涉及的 GitHub 开源工具整理成了下面这份清单： 1. Cryptofeed 实时获取各大交易所的成交、价格和盘口数据，为策略扫描提供行情输入 2. CCXT 统一交易所 API 接口，一套代码即可连接多个平台，完成行情查询、资产读取和订单执行 3. Freqtrade 量化交易的核心框架，支持策略回测、模拟交易、仓位监控，并提供可视化管理后台 4. VectorBT 利用历史行情测试不同的开仓和平仓策略，评估收益表现与最大回撤 5. TA-Lib Python 计算常见技术指标，从行情中提取 RSI、MACD、移动平均线等交易信号 6. skfolio 优化投资组合，根据资产权重、换手率和交易成本，辅助制定仓位配置 7. QuantStats 自动分析交易绩效，生成报告，直观呈现胜率、回撤和波动率等指标 8. DuckDB 轻量级数据库，用于保存盘口快照、订单和交易记录，方便后续分析与复盘 9. APScheduler 定时任务调度工具，可自动更新行情、检查账户状态，并按计划生成每日交易报告 10. Lightweight Charts 提供终端 K 线可视化，实时展示行情走势和策略执行的交易标记 这些组件可以通过脚本、API 和 MCP 协议连接起来，组成一套协同工作的自动化交易系统 不过，真正准备接入实盘时，有几条规则不能忽略： 独立管理下单权限，严格限制最大持仓和单日亏损 遇到状态不明确的订单，先核实执行结果，再决定是否重试 策略上线前，先在模拟盘完整运行一个周期 每日复盘必须区分已实现盈利、未平仓头寸、手续费、失败订单和账户资金变化，确保每笔资金流向都有记录 AI 自动交易的价值，不只是让机器人替你下单，而是把行情扫描、策略判断、风险控制和交易复盘串成一套自动化流程

Over the past few months, we have restructured MEGA to move in a new direction. We’ve brought together new capabilities and reorganized our teams, a process that has resulted in a 20% reduction in our staff. These are people who helped build MEGA from its earliest days ( building out the chain / wallet, supporting our ecosystem, and telling our wild stories). To everyone who is leaving: I appreciate you. Your work is foundational in what we’re doing next. If you are hiring, please reach out. These are some of the best people we have worked with, and we will gladly make introductions. Our founders, early employees and core engineering team remain committed to MEGA and to the work we started three years ago with MegaETH. We believe cryptography and distributed systems will change how the world produces and accesses purified intelligence. We have a lot to prove, and a lot of work ahead.

这个Grok Bot跑出来的结果，太暴力了。 我开着Grok Bot全自动交易终端放了一整夜，它自己不停跑单。 本金就69.67美元，睡一觉起来，账户直接到13370美元。 这中间我一笔都没有手动操作。 我只充了本金，点开全自动，剩下全部交给机器人自己搞定： 自己找机会进场、选时间开仓、按照提前设置好的风控自动止盈止损。 我把这套通宵AI自动交易用到的10个GitHub开源库整理出来： 1. Cryptofeed 实时接收各大交易所的成交、价格、盘口信息，给策略扫描提供行情数据。 2. CCXT 统一交易接口，一套API对接很多交易所，查资产、看行情、挂单交易都支持。 3. Freqtrade 量化策略运行主体，可以回测、跑模拟盘、盯着仓位，自带可视化后台。 4. VectorBT 用历史行情测试各种开平仓思路，看看策略盈亏和最大回撤情况。 5. TA-Lib Python 计算技术指标，解析行情，产出RSI、MACD、均线这类信号。 6. skfolio 调整持仓组合，根据权重、换手、手续费，搭配合适的仓位。 7. QuantStats 自动统计交易表现，生成报告，回撤、胜率、波动率都能算明白。 8. DuckDB 轻量的数据库，存盘口快照和交易记录，方便之后复盘。 9. APScheduler 定时工具，自动刷新行情、检查账户状态、每天生成复盘。 10. Lightweight Charts 终端上看K线图，跑策略的时候能看见每一笔交易标记。 11. FOMO 现在热门的Meme币加现货合约平台，填邀请码qkl2058，手续费减免10%。 各个组件靠脚本、API、MCP协议串起来协同工作。 一定要记住：下单权限单独管控，卡死最大持仓和亏损上限，拿不准的订单先核对状态，再考虑重试。 准备拿去实盘跑的策略，先在模拟盘完整跑一轮周期。 每天复盘要分开看：已经落袋的盈利、当前持仓、手续费开销、失败订单，账户里资金变动，都能找到来源。

🚨 Vitalik与以太坊基金会遭前员工起诉！ 前 #以太坊基金会# Protocol Support负责人Kayleen Fulton（Nixo）于11月4日在美国科罗拉多州联邦法院提起诉讼，将 #VitalikButerin# 等列为被告。 📄 起诉书称，基金会《EF Mandate》中的“切腹条款”引发员工反对，79人支持删除，53人联名反对强制表态。 Fulton称，她披露癌症诊断后，于4月6日与另一名联名信组织者相继遭解雇。 ⚖️ 原告提出11项法律诉求。所有相关指控尚未经法院认定。 🚨 Vitalik Buterin and the Ethereum Foundation Face Employee Lawsuit Former #EthereumFoundation# Protocol Support lead Kayleen Fulton, also known as Nixo, filed a lawsuit in Colorado on November 4. The complaint alleges retaliation following internal opposition to the EF Mandate and raises discrimination and medical leave claims after Fulton disclosed a cancer diagnosis. ⚖️ The allegations have not been adjudicated, and no liability has been established. #以太坊# #ETH# #Ethereum# #Vitalik# #CryptoNews# #TECHUBNEWS#

Ever wondered how #XELIS# decodes encrypted balances in milliseconds? Here's the mathematics behind the magic! 👇 🔥 Encrypted on chain: Your balance stays confidential. 🔥 Baby Step, Giant Step (BSGS): A clever mathematical algorithm that avoids checking billions of possibilities individually. 🔥 2⁴⁸ decoding range: Handles an enormous range of possible values. 🔥 Precomputed tables: Around 330 MB of data helps accelerate the decoding process. 🔥 Cuckoo hashing: Enables efficient lookups to find the right values. 🔥 Milliseconds: Complex cryptography becomes a fast, practical wallet experience. 🔥 The result? Strong financial privacy without sacrificing usability. That's how #XELIS# turns advanced mathematics into real world technology. 🎬 Enjoy watching! 👁️ @xelis_project @xelis_fans @web3 @alkazarauniiii @xelisvault #Web3# @Awen__crypto @cryptoprvcy #Crypto# #CryptoMining# #Smartcontracts# #Privacy#

🐍🏰 THE DRAGON KITE OF SHERWOOD 🐉✨ Even the greatest Outlaw knows that some treasures cannot be bought with gold. ❤️ Laughter. 🐉 Imagination. 🌳 Freedom. 👑 A childhood without crowns. In Sherwood, every child deserves to dream BIG! The next generation of Outlaws is rising! 🚀 🐍 @HISSRH 🌐 #HISS# #RobinhoodChain# #CryptoCommunity# #Sherwood#

And yeah @fermah_xyz started with a problem that sits deep inside the ZK stack. Zero knowledge applications can prove that a computation was done correctly, but producing those proofs at scale takes serious infrastructure: specialised hardware, several proving systems, workload scheduling, and reliability and cost controls. A team building a ZK rollup, zkVM, bridge or coprocessor cannot simply ask for "a proof" and move on. Fermah's first answer was a universal proof generation layer. Provers with GPUs and other hardware supply capacity, applications that need proofs create the demand, and Fermah matches the two. That marketplace is now called Froben. The problem behind the proof Running this in production exposed something bigger. A proof is one step in a longer sequence. Something has to trigger the work, the work has to run, the result has to be verified, and then the result usually has to start the next action. Fermah's argument is that blockchains are good at recording state and weak at starting what happens next. Take a lending position that crosses its liquidation threshold. The chain records the fact, but nothing forces the liquidation. A keeper, bot or backend still has to notice the condition, build the transaction and submit it. Consensus settles what happened, and a human run service still decides what happens after. Fermah calls the missing piece protocol agency: a protocol's ability to act on a verifiable condition without depending on an outside operator. What Kernel does Kernel is Fermah's Protocol Agency Engine, and its pitch is short: Define. Execute. Attest. A developer defines a workflow, Kernel runs it, and the result is published onchain with a cryptographic proof. Three design choices matter here: -Typed nodes. Workflows are built from a library of verified building blocks such as HTTP calls, onchain reads, price feeds and math functions. The type system validates how they connect before anything runs. -Sandboxed execution. Workflows run in an isolated environment built for untrusted code, and the same inputs always produce the same output. - AI where it helps, code where it counts. Fermah says AI agents can compose workflows, but deterministic code executes them, with no LLM in the execution path. Kernel can work as an oracle too. A smart contract requests a workflow, Kernel runs it, and the contract receives the result with a proof that the workflow ran exactly as written. Froben and Flashcast Fermah did not walk away from ZK. Froben still runs, now on top of Kernel, and its paying customers include ZKsync Era and Abstract. In Froben, a workflow defines the proving pipeline and Kernel schedules the work across the prover fleet. Flashcast Social shows a different use of the same engine. A user posts a question, and within seconds it becomes a live prediction market. Kernel then runs the resolution workflow and settles the market automatically when the event happens, with no committee and no dispute window. Proof generation and market resolution have little in common on the surface. What they share is a condition that has to produce an action, and that is the workload Kernel is built around. Fermah also lists data aggregation, pricing oracles and cross chain coordination as things Kernel can run. Where agents fit Fermah's latest thinking extends this to autonomous software agents. An agent working onchain needs to find available actions, check whether it is allowed to run them, pay, execute, and use the output as the input to its next step. Fermah describes this as action manifests, which make actions machine readable across discovery, eligibility, execution, payment and output. The shift in one line The old question was how to generate ZK proofs efficiently at scale. The new one is how a protocol can turn a verifiable condition into a complete, executable sequence. Proving is still part of the system, but it is now one workload among several that Kernel coordinates.

☕ GM Krynians Wednesday. Halfway through the week. 👽 Kryn’s got his coffee. We’ve got our vision. Still building. Still growing. Still Zelkryn. 💙 Explore. Build. Belong. $ZKRY #Zelkryn# #BNBChain# #Memecoin# #CryptoCommunity# #krynian#