

anxu430
408 posts






iPhone 17 搭载MIE硬件级“内存安全”:EMTE实时校验+系统默认开启,拦截越界/UAF等0-day攻击链,减少侧信道风险.据统计,内存安全漏洞占所有软件漏洞的70%,这项升级对高净值用户&频繁签名者来说简直是福音!钱包签名、Passkeys更安全,必买理由来了🎉



午饭老师大概是说笑,但联想到一个点,一直想聊几句但一直忘记抽时间说了: 很多人在牛市里,是死在“对账号市值的心理锚点”这个巨大的坑上, 为了回到一个心里锚定的账号市值(执念), 侥幸心理下一波拉高杠杆(抵挡不住走捷径满足执念的诱惑), 结果导致一下子回到解放前。这个我自己过去10年亲历过吃过多次教训,所以深有体会。 比如,20万进场的, 经过牛市的3~6个月变成100万, (这多好啊) 来来回回两三波亏回50~75万, (还是很不错的状态了啊) 可大多人的反应,不是知足适可而止歇一歇, 而是想“这回我大搞一把,就搞这一把,只要回到90万+就不玩了”(账号市值心理锚点) 然后就...


这两天周末去香港玩,我顺便又开了两个香港银行账户,一个是建设银行亚洲,另一个是汇立银行,简单分享一下开户流程。 我发现建设银行亚洲,可能是目前香港开户最简单的一家实体银行。 不需要地址证明、资产证明、投资证明,不会详细审核职业或资产信息,没有资金要求,可以说是真正的 0 门槛开户。 带好身份证和港澳通行证,落地香港之后,直接下载建设银行亚洲的 App,按照提示一步步操作。 隔天就会提示开户成功,对应的银行卡会直接邮寄到你填写的通讯地址。 我很喜欢这种线上 App 操作的开户方式,不需要预约、不需要到网点排队,简单省事。 毕竟绝大多数人开通香港账户,要么是为了入金美股,要么是为了出金 USDT,所以有银行账户就够了,一般用不到实体卡,没必要跑到网点开户。 另外,这次新开的汇立银行是一家虚拟银行,类似于众安、蚂蚁,也是在 App 上开通,按照提示一步步操作,大概 5 分钟左右就可以搞定,一如既往地省事儿。 对于香港银行账户来说,我认为只要没有管理费和年费,趁着现在内地用户开户不设限制,能开则开,多开几个备用,预防政策和冻结风险。 毕竟从今年的监管政策上来看,无论是美股还是币圈,都在不断地收缩。香港银行的开户口子还能存在多久,得打上一个大大的问号。 下周我应该还会再出一期视频,详细分享一下港卡开户的流程。感兴趣的朋友可以给推文点个赞,提前订阅一下我的 Youtube 频道:@NicoGrowthz" target="_blank" rel="nofollow noopener">youtube.com/@NicoGrowthz







New paper coming.


AI’s next frontier is Spatial Intelligence, a technology that will turn seeing into reasoning, perception into action, and imagination into creation. But what is it? Why does it matter? How do we build it? And how can we use it? Today, I want to share with you my thoughts on building and using world models to unlock spatial intelligence in this essay below. 1/n

I finally understand the difference between LLMs, RAG, and AI Agents. After building production AI systems for 2 years... Here's what actually matters: They're not competing technologies. They're three layers of the same intelligence stack, and most people are using them completely wrong. > The LLM is the brain < It can reason, write, and understand language. But here's the catch: it's frozen in time. GPT-4 knows nothing past its training cutoff. Ask it about yesterday's news? Hallucination city. LLMs are brilliant at thinking but blind to the present. > RAG is the memory system < It connects that frozen brain to live knowledge. When you ask a question, RAG searches external databases, pulls relevant documents, and feeds them to the LLM as context. Suddenly your static model becomes dynamic. Fresh data. Real facts. Zero retraining needed. The accuracy gains are immediate. Instead of guessing from training data, the model reasons over actual retrieved information. You can audit exactly which documents influenced each answer. > AI Agents are the decision-makers < While LLMs think and RAG informs, neither can act. Agents wrap a control loop around the brain. They perceive goals, plan steps, execute actions, and reflect on results. An Agent doesn't just answer questions. It researches topics, pulls data, synthesizes reports, and sends emails. All autonomous. Here's where it gets interesting. Most AI demos are just LLMs with fancy prompting. Real production systems layer all three: the LLM for reasoning, RAG for accuracy, and the Agent framework for autonomy. Use an LLM alone when you need pure language tasks: writing, summarizing, explaining. Add RAG when accuracy matters: answering from internal docs, technical manuals, domain-specific knowledge. Deploy Agents when you need real autonomy: systems that decide, act, and manage complex workflows. The future isn't about choosing one. It's about architecting all three together. LLMs for thinking. RAG for knowing. Agents for doing. That's the actual intelligence stack.


只要你手里持有Tesla股票,一定抓紧投票,很多朋友问我怎么投,请看我帖子中的Broker清单,都有对应方法,有些小券商你需要和他们联系,另外如果你是通过银行买的 $TSLA 请和你的客户经理、banker联系,他们不一定会主动发给你投票的邮件。 一共14个议题,投票建议在楼下仅供参考,支持Elon!!


中国,欢迎来到 Polymarket。我们诚挚地欢迎您所在地区最优秀的 Polymarket 交易员加入我们的 Polymarket 交易员大家庭。欢迎继续分享您的交易和见解,我们期待您的光临。