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The latest work has been focused on what happens after a user already has exposure. Getting into a position is only one part of the experience. Managing it needs to feel just as clear. We’re refining how users can understand what they currently hold, what actions are available, and what happens when they make a change. None of this is about adding complexity for the sake of features. It’s the opposite. We want someone to open Zero Stocks, understand their position quickly, make the change they want, and move on without wondering whether they missed something. The privacy infrastructure can be complex underneath. The product itself shouldn’t feel that way.

UPDATE: The database issue has been resolved and SSL is now fully activated. ✅ You can now proceed with your application. We apologize for the inconvenience and appreciate your patience! 💙 🤖 Dear CyberThrone Community, If you haven't secured a mint spot yet, we have good news! 💙 Our Wallet Submission Platform is now available, giving everyone another opportunity to join the CyberThrone mint. 🔹 Complete a few simple tasks 🔹 Submit your wallet 🔹 We review your on-chain activity Submitting a wallet does not guarantee a whitelist spot. We are looking for genuine holders and will check for bot/scripted minting and patterns of quickly flipping free or discounted mints. 🔐 Using a hot + cold wallet? You can submit both, and we will review them together. Our goal is simple: give the remaining spots to those who genuinely want to support and be part of CyberThrone. We support those who support us. 💙 CyberThrone Team

GM 😻 I’ve been so quiet here, and I’ve missed your posts! I’ve been super busy with my company bank account and website, and had a lot going on. If I missed anything, just know I wasn’t ignoring you 🖤

Some mornings quietly rearrange ambition. 🚀 At an @EYnews x Australian Chamber of Commerce joint event a few weeks ago, my NewChic Capital Family Office partners and I weighed in on a conversation about space as private capital's next frontier. We backed SpaceX early, years ago. And the question that stays with me: how do we keep pursuing moonshots while staying practical? Panelists Mahesh Harilela, Space HK co-founder, whose family created The Hari, and Dr Adam Janikowski brought real estate, manufacturing and data centre conversations alongside legacy and vision. With my NewChic Partners, I found possibility. ✨ Which dream earns your conviction? Christy So · Laurence Thoo #SpaceEconomy# #FutureInfrastructure# #FamilyOffice# #HongKongInvesting# #PrivateMarkets#

We recently had a user whose account was compromised. Our customer service team identified the situation quickly and froze the account. We then worked with the user to restore their original email and authenticator, helping secure the account and prevent further risk. Unfortunately, an API key that remained on the account allowed the attacker to transfer the funds before the issue could be fully contained. We are still investigating exactly what happened. But one thing is clear to us: we do not believe the user should have to bear the consequences of this incident. We immediately put together a dedicated team to handle the case, and we have fully compensated the user. We have always believed that being user-first means more than just saying it. When our users need us to step up, we will. Thank you to everyone for your trust, and especially to the user involved for giving our team the time today to work through this properly. We’ll keep learning, keep improving, and keep moving forward.

[开源学习资源] AI Engineering from Scratch 59.8K ⭐️ 作者 @ghumare64 课程共 20 个阶段，以 Python 为主要编程语言，主张在导入任何框架之前，先用纯数学把每个算法手写一遍。 课程地址： 开源地址： 它和常见教程的本质区别 ？ 大多数 AI 教程是“API 驱动”的：装个库、调个接口、跑个 demo。这个项目反其道而行，每节课遵循固定的六段结构： Motto → Problem → Concept → Build It → Use It → Ship It 以 Phase 10 的一节课「Tokenizers: BPE, WordPiece, SentencePiece」 为例，这个格式是真实落地的，而且写作质量相当高： · Problem 部分不讲废话，直接从代价切入：“你的 LLM 不读英语，它读整数。分词器决定这些整数是承载意义还是浪费意义”，然后解释为什么 tokenization 不是预处理，它是架构的一部分（影响上下文窗口利用率、API 计费、推理速度）。 · Concept 部分用“三种失败的方案和一种胜出的方案”来讲演化逻辑：词级切分（词表爆炸、[UNK] 问题）→ 字符级切分（序列过长）→ 子词切分（BPE 的折中），并配上真实语料上 BPE 逐步合并的手工演算。 每节约 3000+ 词，带 Mermaid 图、可运行代码和测试。 另外两个设计值得强调： · 每节课产出一个可复用的 artifact，一个 prompt、一个 skill、一个 agent 或一个 MCP server。学完整个课程，你手里有 523 个可展示的作品，不是 523 个跑完就扔的 notebook。 · 强调“证据留存”：保留命令、退出码、输出，作为学习发生的证明。这明显吸收了工程实践中“可验证性”的思路。 # 课程结构：从线性代数到自主智能体集群 20 个阶段构成一条完整的上升曲线，咱们它分成五个大块来看： 基础层（Phase 0–2）：环境与工具链、数学基础（线性代数/概率/微积分）、经典机器学习。这是给基础不牢的读者铺的路。 深度学习与感知层（Phase 3–6）：神经网络核心、计算机视觉（一路讲到 NeRF、高斯泼溅、世界模型，这已经超出一般教程的覆盖范围）、NLP、语音。 生成与决策层（Phase 7–9）：Transformer 深挖、生成式 AI（GAN、扩散模型、flow matching）、强化学习。 LLM 层（Phase 10–12）：这是全课程的重心之一。Phase 10 的目录我逐条看过，它不只是“从零实现 GPT”这种常规内容，还包含了相当前沿的论文级主题：DeepSeek-V3 架构走读、DualPipe 并行策略、Native Sparse Attention（NSA）、多 token 预测、Jamba 的 SSM-Transformer 混合架构、 speculative decoding 等。Phase 11 转向应用侧（RAG、LoRA、MCP、可观测性），Phase 12 覆盖多模态（从 CLIP 到 computer-use agent）。 智能体层（Phase 13–16）：工具与协议（MCP、A2A、Agent Skills）、54 节课的 agent 工程、自主系统与安全、多智能体集群。这一层的分量很能说明项目的判断：它认为 AI 工程的重心正在从“训模型”转向“构建可靠协作的智能体”。 收尾（Phase 17–19）：生产基础设施、伦理与对齐、毕业设计。 # 生态与周边：不只是一个课程仓库 网站：带浏览器本地存储的学习进度追踪、术语表、课程目录和路线图。 六卷本书籍：课程内容由 CI（pandoc）自动构建成 EPUB/PDF，附在 GitHub Releases 上，课程即书，且随仓库持续更新。 Agent 导师模式：运行 npx skills add rohitg00/ai-engineering-from-scratch，可以把整个课程装进 Claude Code、Codex 等编码智能体，变成一个带分级测验（placement quiz）和个性化路径的交互式导师，学习进度写在 LEARNING.md 里。这是“用你正在学的工具来学”的巧妙闭环。 认证备考：5 条备考路径、67 节课、505 道练习题，覆盖 Anthropic 的 Claude 认证和 Agentic AI Foundation 的 MCPA。项目明确声明与这些考试机构无关联，只是独立的备考材料。 12 种语言的翻译（含中文），以及四条核心学习路径（构建与部署 AI 应用、软件工程基础、Agent 辅助工程、产品判断与交付）供不同目标的人选路。