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A note on recursive STARK mempools (EIP-8288) This is an EIP that I am hoping we can get included in I-star (the fork after Hegota) that you can think of as the next step after Frames, that would unlock extreme amounts of power. Particularly: * Ultra-cheap quantum-safe signatures (SPHINCS-). Much of the cost savings comes from the fact that the signature data (~3 kB) does not have to go onchain * Ultra-cheap quantum-safe privacy protocols. Status quo minimum cost for private txs is ~300k if you engineer very well (no one does), status quo quantum-safe is ~10M gas, this could reduce it to low tens of thousands. * Universal support for your favorite new signature or proof scheme without needing EVM changes. Whatever you use (Falcon, ML-DSA, some other lattice-based thing, something code-based or isogeny-based or even more esoteric), you can just wrap it client-side in a STARK, onchain gas cost low tens of thousands just like privacy protocols. Hopefully, Ethereum will never need "please support my favorite cryptographic algo" politics again. * Private account abstraction: keep your account logic private, and in a private location onchain. Then you can make one transaction to change the ownership of all your onchain state - accounts, defi positions, privacy protocol notes, everything - without revealing which objects' ownership you're changing. Here's how it works. Your transaction can include a type of frame that we call a "dependency frame". The frame is a list of statements, asserting claims like "message hash M was signed by SPHINCS- public key P" and "data hash D was proven to satisfy a statement defined by verification key V". When you send your transaction, you send it in an envelope, which includes a signature or a STARK for each statement in a dependency frame. Once the transaction reaches the mempool, nodes aggregate them. Each node runs a loop: wait one tick (eg. 500ms), aggregate all new envelopes (either single-tx or multi-tx) that you've seen, remove any transactions that are expired, generate a STARK recursively proving all dependencies, and send a new multi-tx envelope containing that STARK. Hence, the bandwidth load is bounded: each node's outbound is one STARK (~100-300 kB) per tick, plus each transaction getting broadcasted through the network once (as happens already). The block builder acts as "yet another mempool node", receiving envelopes from the mempool (plus any side channels), generates its own STARK covering the subset of transactions it intends to include in the block, and adds that STARK to the block. Total onchain overhead: one STARK (100-300 kB), plus 96 bytes for each statement being proven. This is what I've called before ( ) "The Proof Singularity". Today, we have all the ingredients to actually implement it. As a developer, this requires a somewhat different workflow than you are used to, but it is conceptually simple. Any signatures or STARKs, you put into a separate frame. Then the main logic that today is verifying a signature or STARK, you replace with checking for the existence of a frame that includes the correct statement as a dependency. Examples of useful statements: * [tx sighash] verifies against [the pubkey at sload(0)] * there exists a secret and a merkle branch such that hashing secret+0 and applying the merkle branch outputs (public) root R, and hashing secret+1 outputs (public) nullifier N * there exists a secret address A, salt S and signature Z such that sload(0) = hash(A, S) and a merkle proof of address A inside a recent ethereum state contains some pubkey D where [tx sighash] was signed by D [this is private account abstraction; all variables except [tx sighash] and sload(0) are private; you can also make D a STARK verification key] * there exists an ML-DSA signature signing [tx sighash], that verifies against an ML-DSA pubkey whose hash is sload(0) At the core, this is moving any compute and data other than bookkeeping "business logic" outside the core path of Ethereum execution, sharding and parallelizing it via the mempool. Notice also that this requires agreeing on a _language_ (aka. an ISA) for the recursive STARKs to define statements in. The current leading candidate is RISC-V. So this would also de-facto be Ethereum adding RISC-V (or something else we decide on) as a canonical ISA - a big decision that should be done carefully, but that I think will be necessary to drive Ethereum forward.

NextSilicon has the best RISC-V core. Period. At the latest RISC-V Summit, NextSilicon's Yiftach Gilad explained how their new RISC-V CPU core, Arbel, challenged conventional thinking and became a RISC-V core built for the demands of AI and HPC.

I updated my 2023 roadmap diagram to overlay where the items that were there sit in the current Strawmap ( ). In general, a lot of overlap, but: * Some things got reshuffled in order (eg. quantum safety up-prioritized) * Some things deprioritized (eg. VDFs; many EVM improvements) * Some things replaced with superior constructions (eg. Verkle -> unified BT -> PBT; state expiry -> new state types) What's most striking, however, is that some completely new things are in the strawmap that are NOT in this diagram, because they were not in the 2023 roadmap at all. These reflect changing priorities. Notably: * First-class attention to strong privacy. This covers: keyed nonces and recent roots, aspects of FOCIL, lean privacy pool & wormholes * Aggressive scaling in the context of post-quantum. This covers: leanSPHINCS signatures and aggregation, zkzk frames (see ) * Lean-ification of the spec, to assist in formal verification (full FV of everything is only possible because of modern AI) * Blob and gas futures (this idea just didn't exist back in 2023) * Native rollups (SNARKs were nowhere near mature enough to even consider this back in 2023) * A more open design space for the "future of the EVM". zkzk frames already implies that the protocol will expose to users some ISA that's not the EVM - current leading candidates are leanISA and RISC-V. These ISAs are more simple, modern and efficient than the EVM. Once they're there, why not expose them to developers everywhere? (And then, why not turn the EVM into being an IR on top of that ISA, instead of an enshrined feature massively complicating the base protocol?) Though much of the deeper exploration here is too early even for the strawmap. * New state types are not just a replacement for expiry, they're a fundamentally different paradigm to how Ethereum does scaling A common theme in scaling, found in both state types and zkzk frames (both new ideas), is that instead of trying to maximally scale ALL ethereum activity, we try to create specialized mechanisms that have more restrictive properties that make them more scaling-friendly, while supporting the heaviest loads incurred by users and applications today (eg. token transfers, swaps) and tomorrow (eg. privacy protocols). The other common theme is treating STARKs and AI-accelerated FV as first-class objects, that we are okay betting the technical future of Ethereum on. There are recursive STARKs in many layers of the protocol, one particular primitive (the "aggregate to union verified dependencies" primitive) is expected to be used in *three* places in the protocol: EL, CL and DL. This can only be safe with formal verification, which is itself only feasible with modern AI tools. In general, many steps forward in maturity. And a huge amount of hard work by many dozens of Ethereum researchers and developers on all of these features. Ethereum will be quantum-safe. Ethereum will put users' privacy first. Ethereum will be secure. Ethereum will be censorship-resistant. Ethereum will be highly performant and scalable while satisfying the above. And Ethereum will be Lean.

Two weeks ago, Ethereum researchers met in Berlin to continue charting the protocol's long-term trajectory, following along discussions with client teams in Svalbard in April. The updated strawmap is at and I attached a picture of it to this post. My own high-level takeaways: * "Lean Ethereum" is not a single one-shot upgrade, it is a collection of improvements that will come online to the Ethereum network over the course of three or four years. But make no mistake, this IS the third major iteration of Ethereum in the same way that the Merge was the second. Almost every major piece of the protocol will be replaced: - Verification through recursive STARKs, rather than direct re-execution. Recursive STARKs become an enshrined first-class core component of the protocol - Replacing everything quantum-vulnerable with quantum-safe alternatives - Consensus: decoupled available chain and finality, one or two-round finality. Theoretically optimal security properties, simpler than today, and faster than today - Multidimensional gas - State: not just tree structure, but what *types* of state are available - Changes to client architecture ... At the same time, simplification, cleanup and future-proofing. And this will all be done in a way that minimizes disruption to existing application. We've done this before (the Merge), we can do it again. * H-star (aka Hegota) is probably Ethereum's last thematically "pre-Lean" fork. Starting from I-star, most of everything we do will have a very strong "Lean" feel to it in one way or another. * Privacy is no longer an afterthought, it is a first class goal. When designing Frames, the mempool, additions to the state tree, we explicitly ask the question "okay, how do quantum-safe, intermediary-free privacy protocol transactions go through this, and what is the overhead?" * Formal verification of everything for security. * FV also makes us much more comfortable with canonicalization (having pieces of the protocol that are directly defined as a piece of bytecode expressed in some language). evm-asm is being written in part to become a canonical proof system for the EVM. * Quantum safety has shifted up a LOT in priority. This adds a lot of work (eg. finalizing a quantum-safe blobs design has become urgent; this work has already been ongoing for months) * Probably the single most disruptive part of the plan is the changes to state. There is growing consensus around leaving present-day-style "dynamic state" mostly unchanged, but scaling it only a medium amount, and adding new types of state that are more scalability-friendly (eg. no need for builders to sync/store all of it) but more restrictive, and that will scale a large amount. eg. possible Ethereum in 2030: 2 TB of present-day-style (dynamic) state, and 100 TB of new-style (scalable but restrictive) state This "new-style" state would work very well for ERC20s, NFTs, many defi use cases, but not eg. highly "central" objects like Uniswap contracts, or onchain order books, or other complex things (which are crucial for Ethereum but which only take up a small percentage of state) Hence, it will not be *necessary* to rewrite any apps, but it will be *very cost-effective* to eg. rewrite an ERC20 token into a newer design that uses a new type of UTXO storage that is currently being explored, so that it will have >10x lower txfees. Design of these new state types (current ideas: keyed nonces, ring buffers, UTXOs, statically accessible state, temp state) is an area where we will need a lot of feedback from application developers (incl. privacy-friendly application developers) and probably several rounds of rethinking and iteration. * In the context of a much larger total state size, we need to figure out the incentive issues around who stores this state and what motivates them to. Even saying "each node stores 1%" is not good enough - why do they store that 1% and why are they willing to serve it? This is being elevated as a first-class research area. * Ethereum will need to have a "VM" other than EVM in one form or another - at the very least, we need something like leanISA for recursive STARKs - and the gains are large in exposing it to users so that we support programmable privacy and better scalability. Right now, the most likely contenders are leanISA and RISC-V. My own ideal is that in this world, we adjust the protocol so that the EVM becomes a high-level-language compiler-level feature, and the protocol only "sees" RISC-V / leanISA directly. But this is still far away. * Gas limit increases, blob increases and slot time decreases will happen many times over the next ~5 years. We expect a large gas limit increase with Glasterdam. Each step of increased scale or decreased slot time is a matter of getting to the point where it is safe to do it, which comes from a combination of client optimization and protocol changes. Ethereum is CROPS. Ethereum is scaling. Ethereum is reinventing itself. Onward.

@aleabitoreddit 还是太牛了，一个纯血传奇的前Reddit WSB交易员，绑定推特创作者收益才发过两次工资，两次工资就已经有8014美金了。。。。。。 现在在推特上面美股内容最具有影响力的人之一了，这可能跟她以前干的事情有关，她以前是RISC-V基金会成员和人工智能研究科学家之一， 现在的她已经转型为人工智能和半导体供应链中“未知瓶颈”的敏锐猎手了，她的内容很有参考价值， 而且最牛的是她今年的战绩！可以说截至目前她投资的回报率约为+3,840%至+4,500%左右， 再看看前两年累计的回报率是+22,560%，这已经是超过了226倍！！！ 我看她经常公开预测$AXTI，$SOI和$AAOI等等这些股票，并且基本都实现了10倍以上的涨幅，被彭博社和路透社引用她写的内容都已经成为常态了。 @aleabitoreddit @aleabitoreddit is truly amazing. A former Reddit WSB trader with pure-blooded legendary status, she's only received two paychecks from her Twitter creator earnings, and those two paychecks already totaled $8,014... She's now one of the most influential people on Twitter regarding US stocks. This is likely related to her past work; she was a member of the RISC-V Foundation and an AI research scientist. Now, she's transformed into a keen hunter of "unknown bottlenecks" in the AI ​​and semiconductor supply chains. Her content is highly valuable. And what's most impressive is her performance this year! It's estimated that her investment return rate so far is approximately +3,840% to +4,500%. Consider the cumulative return rate over the previous two years: +22,560%—that's over 226 times! I've noticed that she frequently makes public predictions about stocks like $AXTI, $SOI, and $AAOI, and these predictions have generally yielded gains of over 10 times. It's become commonplace for Bloomberg and Reuters to cite her writings

那个45倍的「白毛女股神」，到底在买什么？ 事情是这样的。 最近币圈和美股圈都在传一个名字。 @aleabitoreddit 一个X账号，头像是个白毛二次元少女。 2026年5月晒出年度战绩。 4502.45%。 我当时就愣了。 45倍？ 这尼玛是什么操作？ 我跟你说，兄弟们，她不是蒙的。 公开讨论的35只股票，31只正收益。 胜率接近90%。 超10只股票翻倍。 SIVE年内涨超10倍。 AXTI涨超5倍。 AAOI涨超5倍。 而且最骚的是，这些公司，在Serenity公开讨论之前，市值大多不到2亿美元。 华尔街的研究几乎没人覆盖。 机构根本看不上。 但当市场发现，这些企业居然是AI产业链中不可替代的关键环节时。 估值开始疯狂重估。 我跟你说，这人的厉害之处，不是敢买小票。 真正厉害的是，他不是在预测股价。 他是在推演供应链哪里会断。 01）普通人看AI，Serenity看什么？ 大部分人看AI，通常会问： 谁最火？ 谁涨最多？ 谁是龙头？ 谁最确定？ 所以最后大家都会看向英伟达、微软、Meta、台积电。 但Serenity的思路不是这样。 他真正问的是： 如果AI继续扩张，最后会被谁卡住？ 这就是他最核心的方法。 不找热门，找瓶颈。 02）瓶颈中的瓶颈 比如AI发展，第一反应当然是需要更多GPU。 但GPU只是第一层。 GPU变多之后，数据中心会变得更大。 数据中心变大之后，服务器之间、机柜之间、芯片之间的数据传输压力会越来越高。 于是光通信、激光器、硅光、CPO，就会变得越来越重要。 再继续往下挖： 谁提供关键材料？ 谁提供测试设备？ 谁掌握细分产能？ 谁是那个不起眼，但一旦缺货就会拖慢全链条的环节？ 这就是所谓的，瓶颈中的瓶颈。 一个公司不一定名气最大，也不一定收入最大。 但如果它卡在一条大产业链的关键位置。 当需求爆发，而供给短期跟不上。 它就可能被市场重新定价。 03）Serenity的七层卡脖子地图 Serenity把AI供应链拆成了七层。 每一层都找到了那个「没有它整个链条就断掉」的关键节点。 第一层，原材料。 AXTI，做InP磷化铟衬底。 没有它，光子学建设会倒下。 第二层，pBN坩埚。 信越化学，做InP晶体生长设备。 第三层，衬底加工。 AXTI加上一个未命名的双寡头。 Serenity说，这是「皇冠明珠卡脖子」。 第四层，CW激光器。 SIVE，Sivers Semiconductors。 控制下一代CPO的连续波激光光源。 市值不到3亿美元，Serenity说「严重错误定价」。 第五层，光模块。 AAOI、LITE、COHR、中际旭创。 组装光模块的。 第六层，测试设备。 AEHR，做光子学测试。 第七层，光纤电缆。 GLW康宁、Prysmian、Furukawa。 传统光纤加空心光纤。 你看，从原材料到成品，每一层都有一个「没有它就不行」的节点。 Serenity不是在买股票。 他是在画一张AI供应链的「断点地图」。 04）三个经典案例 案例一：SIVE，10倍股 Sivers Semiconductors，瑞典半导体公司。 做AI光互联激光器和光子芯片。 Serenity反复提及超过190次。 公开讨论前，市值不到1.5亿美元。 长期交易量不到100万美元。 没人关注。 但Serenity看到了什么？ 他看到了CPO，也就是共封装光学。 下一代数据中心，光模块要直接封装到芯片旁边。 这需要CW激光光源。 而SIVE控制了这个卡脖子点。 他预测，2026/27年SIVE可能还是零收入、亏损5000万。 但2028年收入可能到5亿。 2029年到10亿。 更骚的是，空头机构Two Sigma建仓SIVE净空。 股价暴涨之后，空头保证金压力越来越大。 被迫平仓，被动买盘助推。 至少一家空头认亏出局，损失数千万美元级。 这就是Serenity说的逼空共振。 在一个流通盘极小的股票里，做空本身就是在给多头递刀子。 SIVE最高涨了近20倍。 案例二：AXTI，5倍股 AXT Inc，美国衬底材料商。 做InP磷化铟衬底。 Serenity说，AXTI「基本上是整个光子学供应链」。 垂直整合了4个不同的卡脖子点。 他用了一个类比。 霍尔木兹海峡。 全球20%的石油通过霍尔木兹海峡。 一旦堵住，整个系统停摆。 AXTI就是光子学领域的霍尔木兹海峡。 Serenity说，大多数人完全不知道自己在说什么。 尽管日波动15%到25%，他仍然持有。 认为当前估值合理。 后来AXTI从十几美元涨到百元以上。 涨幅接近10倍。 案例三：AAOI，数倍股 Applied Optoelectronics，美国光模块公司。 Serenity说，这家公司「激光→设计→组装→销售光模块，拥有整个供应链」。 正在建设ELSFP，也就是外置光源。 进入CPO领域。 他预测，2027年下半年光模块收入10倍增长。 他在84美元左右买入相当数量。 说66亿市值对他来说太便宜了。 后来股价从30多美元一路上涨数倍。 05）Serenity的五步选股法 Serenity的方法，可以总结成五步。 第一步，找超级趋势。 AI、数据中心、算力、半导体、光通信。 大趋势要足够大，足够确定。 第二步，找第一层瓶颈。 GPU、HBM、电力、网络、数据中心。 这些是最明显的瓶颈。 但也是最拥挤的。 第三步，找第二层瓶颈。 激光器、硅光、CPO、特殊材料、测试设备、系统集成。 真正的认知差，往往藏在这里。 第四步，找「小市值 + 关键卡位」的公司。 不是因为它小就买。 而是因为它小，同时又卡在重要位置。 大趋势很大。 公司很小。 位置很关键。 市场还没完全理解。 这才是十倍股可能出现的地方。 第五步，做前瞻推演。 这家公司未来拿到订单的概率大不大？ 有没有产能扩张能力？ 管理层在做哪些布局？ 过去有没有进入核心供应链的经验？ 它卡住的瓶颈，会不会越来越重要？ 这一步最难。 因为此时订单可能还没明显增加。 财报还没验证。 机构也还没大规模买入。 市场还没给出确定性。 但真正的超额收益，恰恰来自这里。 机构等订单确认、收入兑现、财报验证之后才敢买。 Serenity做的是，在这些信号完全出现之前。 先基于供应链逻辑和工程常识。 判断这家公司有没有机会进入核心位置。 06）为什么是小市值？ Serenity专门挑小市值公司。 不是因为小市值涨得快。 而是因为大基金有体量限制。 一个管理百亿美元的基金，不可能去买一个市值2亿的股票。 买多了，流动性不够，进出都困难。 所以小盘股存在定价真空。 华尔街的研究几乎没人覆盖。 机构根本看不上。 但Serenity不一样。 他用的是自己的钱，加上1.4倍杠杆。 集中持仓。 他不需要考虑流动性。 他只需要考虑，这家公司卡在产业链的哪个位置。 当市场发现这个卡脖子点的时候。 估值就会疯狂重估。 这就是信息差。 市场上研究英伟达的人有几万人。 研究激光器供应链的人可能只有几十个。 研究硅光材料的人可能只有几个人。 而研究某个特殊外延片供应商的人。 可能全世界不到十个人。 Serenity就是这几个人之一。 07）Serenity是谁？ 说实话，没人知道。 全网现在还不知道这个人的真实身份。 没有人知道她的真实姓名、国籍、年龄、职业。 是完全隐匿于网络的顶级投资大佬。 X账号简介写的是： AI半导体产业链研究院、Nature论文作者、RISC-V基金会核心成员。 整个含金量拉满。 她还公开了一段过往。 2018年拒绝了英伟达AI团队主管的邀约。 那时候英伟达股价只有6美元。 我跟你说，这人的背景，大概率是真的。 因为她对AI硬件的理解，不是看研报能看出来的。 是从工程细节里抠出来的。 她自己说过，「Only buys what he's touched」。 只买自己摸过的东西。 她大概率是真的在半导体行业干过。 08）机构轮动理论 Serenity还有一个核心观点。 机构轮动。 她抓住了内存名称上涨的尾巴。 SNDK、三星、SK海力士、美光。 然后机构之前用AAOI、AXTI、LITE、COHR等光子学名称跑赢。 现在再次通过大量增加SiPh、ELS来做到这一点。 她说的三阶段轮动是： 第一阶段，内存。 第二阶段，光模块。 第三阶段，外置光源和硅光。 她认为自己现在处于第三阶段的开端。 而大部分人还在第一阶段徘徊。 这就是认知差。 09）风险与争议 Serenity的方法也不是没有风险。 第一，幸存者偏差。 她公开讨论的股票，涨了的大家都能看到。 跌了的，可能就不提了。 第二，没有监管披露。 她没有基金，没有13F报告。 持仓大小、进出时间，都不透明。 第三，高波动。 她持仓的股票，日波动15%到25%是常态。 普通人根本扛不住。 第四，流动性风险。 小市值股票，进出都困难。 她想卖的时候，可能根本没人接盘。 第五，逼空风险。 她自己也参与逼空。 但逼空是双刃剑。 空头被逼平仓，股价暴涨。 但如果空头坚持不撤，或者更多空头加入。 股价可能暴跌。 10）普通人能学到什么？ Serenity的方法，普通人很难完全复制。 因为她有实打实的AI科研背景。 她对供应链的理解，是从工程细节里抠出来的。 不是看几篇研报就能学会的。 但有几个思路，是可以借鉴的。 第一，不追热门，找瓶颈。 热门股已经被充分定价。 瓶颈股，市场还没发现。 第二，往下挖三层。 英伟达需要GPU。 GPU需要光模块。 光模块需要激光器。 激光器需要衬底材料。 每一层都可能有机会。 第三，小市值+关键卡位。 大趋势很大。 公司很小。 位置很关键。 第四，做前瞻推演。 在订单确认之前，先判断逻辑是否成立。 第五，接受高波动。 如果承受不了15%的日回撤。 就别玩这个。 说到底 Serenity的方法，本质上是「供应链断点投资」。 她不是在看股价。 她是在看产业链哪里会断。 当需求爆发，供给跟不上。 卡在关键节点的公司，就会被重新定价。 这就是十倍股的来源。 但说实话，这种方法，门槛极高。 你需要对产业链有极深的理解。 你需要能接受高波动。 你需要有耐心，等市场发现你发现的逻辑。 我跟你说，股市会奖励错误。 以至于很多人赚到钱之后，就意识不到自己的错误。 但把时间拉长来看，市场是公平的。 所有短期的盈利靠运气。 长期的超额收益，永远靠认知壁垒。 Serenity的认知壁垒，就是她比全世界99.99%的人，更了解AI供应链的断点在哪里。 这就是她一年赚45倍的原因。

如果你对美股AI硬件和供应链机会感兴趣，不妨关注一下@aleabitoreddit这个账号。他曾是Reddit WallStreetBets（WSB）的知名交易员，现在专注于AI、半导体和光子学等供应链分析，自称交易未知瓶颈。 他的Bio显示曾任RISC-V基金会和AI研究员，目前重点挖掘AI数据中心、半导体、光子学等领域的被市场忽略机会，内容风格偏向深度基本面分析，常配图表、backlog数据和市场份额测算，专注发现小盘或中盘AI基础设施股的潜力。 近期推文显示，他对AI数据中心相关瓶颈保持非常乐观的态度。例如，加拿大变压器公司 $HPS.A是其长期看好的核心标的，他认为其在干式变压器市场占比高，需求来自AMZN、MSFT、META等超大客户，股价已上涨83%，仍具复合增长潜力。光子学公司 $AAOI也是重点，他看好激光供应瓶颈加剧和长期订单带来的增长，即便市值已达130亿美元。韩国ETF $EWY中的三星、SK海力士等标的，通过期权暴涨也体现出内存超级周期的机会。他还关注欧洲前沿科技股，如 $SOI、 $RPI和 $SIVE，认为被本地媒体低估，但后来表现强劲。 整体投资逻辑围绕AI硬件供应链未知瓶颈，选股重点是中下游隐形冠军，包括变压器、电力基础设施、光子学模块、内存及半导体材料等，偏好高backlog、产能即将放量、定价权强且被市场低估的公司。仓位上，他偏好股票和长线期权（LEAPs），重点标的覆盖加拿大、美国、韩国，并关注中国在欧洲技术收购中的机会。核心观点是AI数据中心建设远未结束，资源争夺将持续推高小众公司的业绩和估值。

散户是很难当股神的 一年赚几十倍的Serenity @aleabitoreddit 很多人都不知道，她可不是普通散户 据说Serenity拒绝过英伟达的工作 而且她还是RISC-V Foundation成员 RISC-V Foundation的核心Krste Asanovic 是全球芯片架构的超顶级专家 所以Serenity能把AI产业链 尤其英伟达的产业链吃的如此之透 不是没有原因的 AI时代，谁理解的越深 谁就能挖掘更多机会 普通散户如果不懂行业 自己瞎琢磨，很难持续赚钱 不理解自己买的是什么，也不敢拿太久 如果你不想浪费脑细胞，就跟着股神走 让她给当你老师，并且给你“打工”😄