2023韭菜生存指南——为什么我们都爱Meme Coin

MarsBitОпубликовано 2023-05-23Обновлено 2023-05-23

Введение

先从从大数据上来说,虚拟货币市场目前的交易量,是牛市的脚拇指尖尖那么多,已经很久没有人再去说主流币,山寨币等等概念了,大多数的币交易量已经迅速下降,流动性极具减弱。如何掘金?

《2023韭菜生存指南》-作者-0xMasiwei (这是一篇长推特,在马桶上手打的,会在蹲结束前写完)

先从从大数据上来说,虚拟货币市场目前的交易量,是牛市的脚拇指尖尖那么多,已经很久没有人再去说主流币,山寨币等等概念了,大多数的币交易量已经迅速下降,流动性极具减弱,三箭资本暴雷,Luna暴雷,FTX暴雷,一大堆机构暴雷,今年是虚拟货币市场的灾荒年份。

再聊聊今年几个热点:

Gamefi: 3A级Gamefi死了个遍,凡事你听过的3A级Gamefi投融资几个亿美金那种,要么机构死掉了,比如3AC死了,天天问自己投资的游戏要退钱,撕逼,比如Alamenda和ftx死了,他们投资的一大堆游戏全烂尾了,比如Luna死了,一堆3A游戏项目方工资发不出来了。玩个屁

Gamefi领域目前能赚钱的有啥呢?不是开盘跑路,就是过几天跑路,来来回回其实就那几个套路,跑不出来什么好项目,主要是因为大制作VC被割怕了,小制作VC看不上,真赚钱也轮不到VC,没大VC背书又上不了大交易所,快速割一波也就死了。

Gamefi目前半死不活,别玩!

NFT领域:几百万个要超越Bayc的项目,全归零了,看着钱包里几千张归零的小图片,全是过往一天到晚管Mod叫爹叫娘吹彩虹屁的时光,往日的我怎能想到今日曾经难以得到的白名单,竟都是些赔钱的烂货。

Moonbird老板摆烂,doodles团队傻逼,Clonex把用户当作消费者冤大头,不过他们都还有机会。

不过多的是你看不到的归零小图片。很多人说,因为土狗所以NFT才没人玩!我说你是不是没见过世面,曾经我们顶着600u的gas,去打一张归零的NFT在NFT牛市,随便一手都是几百U的Gas,那个时候Eth4000呢还,要是NFT赚钱,gas算个球。这几天土狗玩的人少了,NFT也没反弹啊,不赚钱,跟gas没关系。

NFT本质是装逼的社交需求,饱暖思淫欲,只要牛市人才有装逼需求,汽车之家下载量和OpenSea用户增长量时一致的,Opensea就是币圈的汽车之家,现在熊市人饭都吃不饱,你装什么装?装还容易激起仇恨,牛市的时候看你装逼,我也想买个同Collection的一起装逼,可现在不一样了,你装吧,我累了。

NFT没了赚钱效应,短期,玩不了,怎么玩?对了,还有人拐Blur把市场砸烂了,这种心态不亚于那种自己JJ小勃起不了的阳痿男,怪自己女朋友下体不够紧致。连Binance暂时都觉得Blur高估了,再跌跌吧。(其实也是一肚子坏水,只开合约鼓励做空套保),所以,nft就别玩了。

说完了Gamefi和NFT再说说公链,Arb,Op,zkSync,Sui,Aptos我这么说吧,全是垃圾,在一个韭菜的眼里,这些东西全部是垃圾,千万不要买任何一个,买就是脑子瓦特了,知道为什么吗?

一上来就估值几十亿美金,一上来几十亿美金市值,你到底想干啥?全世界人民打车的Uber才多少市值?要脸吗都?

为啥别买?

1 Cex投资,自己便宜筹码,赚发行的钱

2 VC投资,自己托高市值,核心圈VC才能投

3 全明星开发阵容,所有开发都是溢价聘请,实际上没有这个阵容,VC也不会有。

4知名投资人,知名专家,知名大佬站台

5 把币给专业做市商,把韭菜往死里割。

你买它干啥?你买它干啥?

千万别买任何除了BTC和ETH以外的任何公链代币,要用可以用,但是别买币,真别买,让他们滚。

一上几十亿美金市值,我作为炒币的韭菜,我尼玛陪你玩这个?几十亿美金市值,空间还有多少?融资的时候没有我,私募的时候没有我,IDO的时候没有我,接盘的时候到了,开始吹牛逼了?给我滚,全部滚。

那对于这些公链,我们应该做啥?

1 撸他,他们就是喜欢数据作假,然后根据撸的人的多少给你付刷数据的辛苦费airdrop,那你就撸就完事了,千万别买币。

2 fork eth上的项目,跑出来的,市值低的时候买一点

3 项目方为了生态发展会扶持一些项目,交互交互,玩一空投了呢。

交易所已经变了味道了

上的币啊,不是山顶,就是几亿美金几十亿美金市值

就不能来个几千万美金市值的让用户们去感受下钻石手1-100的快乐吗?

以前交易所勇于捕捉早期机会,现在交易所勇于在最后一棒让用户接盘,这种做法,真的真的对用户没有一点点好处。

简单的道理,种子轮你们包了,第一轮第二轮你们兄弟包了,上了所了,想起兄弟我来了,几亿美金市值了让我冲了,哎,真别这样。

人们为什么去冲meme?这就是最原始的击鼓传花,大家都在击鼓传花,只要最后一棒不是我自己,那就无所谓啊,这不就是一开始Binance能起来的理由吗?17-18年的Binance靠着山寨币疯狂起飞攒到了第一波流量和风口,大V击鼓,大户散户一步一步传花接盘,资金充分换手,很原始但是中间很多人能赚钱的

交易所拿走了太多利益,交易所相关的VC拿走了太多利益,这些价值币千万别碰,价值都是他们告诉你的价值。还有啊交易所上线几十亿美金市值的pepe,是因为他是价值高吗?上币经理那么多,怎么不去死啊?几十亿美金了你上币了,1000w美金前后前面你干嘛去了?死哪里去了?非要把用户套死才甘心?滚啊

所以啊,散户为什么冲meme啊?知道吗?meme是变相的一级市场,类似于500万美金市值的币,你私募多少额度,自己去Dextool买,中了Okx那就是50倍,中了Binance就是100倍。冲meme,冲土狗本质上是一种变相的一级市场ICO,短期市值大小池子大小决定了你私募的轮次和额度多少。

用户希望的永远是百倍币,千倍币,可以发财的币,而不是交易所自己融资,自己讲故事,自己找人发币那种垃圾东西。Dex的火爆也是因为,用户是真的很可怜,实在找不到参与一级市场的办法了。

撸毛,其实也是参与一级市场的,类似于种子伦第一轮的价格,项目方不傻,VC也不傻,你撸毛的成本,加减乘除下来,地址数和空投数据,人家项目方早都安排了一大堆分析师给你那边算呢,不能给你太多,也不能不给,以帮助造假数据的贡献度给一级市场额度了这属于。

明天起床有空继续。

Похожее

Where Is the AI Infrastructure Industry Chain Stuck?

The AI infrastructure (AI Infra) industry chain is facing unprecedented systemic bottlenecks, despite the rapid emergence of applications like DeepSeek and Seedance 2.0. The surge in global computing demand has exposed critical constraints across multiple layers of the supply chain—from core manufacturing equipment and data center cabling to specialty materials and cleanroom facilities. Key challenges include four major "walls": - **Memory Wall**: High-bandwidth memory (HBM) and DRAM face structural shortages as AI inference demand outpaces training, with new capacity not expected until 2027. - **Bandwidth Wall**: Data transfer speeds lag behind computing power, causing multi-level bottlenecks in-chip, between chips, and across data centers. - **Compute Wall**: Advanced chip manufacturing, reliant on EUV lithography and monopolized by ASML, remains the fundamental constraint, with supply chain fragility affecting production. - **Power Wall**: While energy demand from data centers is rising, power supply is a solvable near-term challenge through diversified energy infrastructure. Expansion is further hindered by shortages in testing equipment, IC substrates (critical for GPUs and seeing price hikes over 30%), specialty materials like low-CTE glass fiber, and high-end cleanroom facilities. Connection technologies are evolving, with copper cables resurging for short-range links due to cost and latency advantages, while optical solutions dominate long-range scenarios. Innovations like hollow-core fiber and advanced PCB technologies (e.g., glass substrates, mSAP) are emerging to meet bandwidth needs. In summary, AI Infra bottlenecks are multidimensional, spanning compute, memory, bandwidth, power, and supply chain logistics. Advanced chip manufacturing remains the core constraint, while substrate, material, and equipment shortages present immediate challenges. The industry is moving toward hybrid copper-optical solutions and accelerated domestic supply chain development.

marsbit27 мин. назад

Where Is the AI Infrastructure Industry Chain Stuck?

marsbit27 мин. назад

Autonomy or Compatibility: The Choice Facing China's AI Ecosystem Behind the Delay of DeepSeek V4

DeepSeek V4's repeated delay in early 2026 has sparked global discussions on "de-CUDA-ization" in AI. The highly anticipated trillion-parameter open-source model is undergoing deep adaptation to Huawei’s Ascend chips using the CANN framework, representing China’s first systematic attempt to run a core AI model outside the CUDA ecosystem. This shift, however, comes with significant engineering challenges. While the model uses a MoE architecture to reduce computational load, it places extreme demands on memory bandwidth, chip interconnects, and system scheduling—areas where NVIDIA’s mature CUDA ecosystem currently excels. Migrating to Ascend introduces complexities in hardware topology, communication latency, and software optimization due to CANN’s relative immaturity compared to CUDA. The move highlights a broader strategic dilemma: short-term compatibility with CUDA offers practical benefits and faster adoption, as seen in CANN’s efforts to emulate CUDA interfaces. Yet, long-term over-reliance on compatibility risks inheriting CUDA’s limitations and stifling native innovation. If global AI shifts away from transformer-based architectures, strict compatibility could lead to technological obsolescence. Despite these challenges, DeepSeek V4’s eventual release could demonstrate the viability of a full domestic AI stack and accelerate CANN’s ecosystem growth. However, true technological independence will require building an original software-hardware paradigm beyond compatibility—a critical task for China’s AI ambitions in the next 3-5 years.

marsbit46 мин. назад

Autonomy or Compatibility: The Choice Facing China's AI Ecosystem Behind the Delay of DeepSeek V4

marsbit46 мин. назад

How Blockchain Fills the Identity, Payment, and Trust Gaps for AI Agents?

AI Agents are rapidly evolving into autonomous economic participants, but they face critical gaps in identity, payment, and trust infrastructure. They currently lack standardized ways to prove who they are, what they are authorized to do, and how they should be compensated across different environments. Blockchain technology is emerging as a solution to these challenges by providing a neutral coordination layer. Public ledgers offer auditable credentials, wallets enable portable identities, and stablecoins serve as a programmable settlement layer. A key bottleneck is the absence of a universal identity standard for non-human entities—akin to "Know Your Agent" (KYA)—which would allow Agents to operate with verifiable, cryptographically signed credentials. Without this, Agents remain fragmented and face barriers to interoperability. Additionally, as AI systems take on governance roles, there is a risk that centralized control over models could undermine decentralized governance in practice. Cryptographic guarantees on training data, prompts, and behavior logs are essential to ensure Agents act in users' interests. Stablecoins and crypto-native payment rails are becoming the default for Agent-to-Agent commerce, enabling seamless, low-cost transactions for AI-native services. These systems support permissionless, programmable payments without traditional merchant onboarding. Finally, as AI scales, human oversight becomes impractical. Trust must be built into system architecture through verifiable provenance, on-chain attestations, and decentralized identity systems. The future of Agent economies depends on cryptographically enforced accountability, allowing users to delegate tasks with clearly defined constraints and transparent operation logs.

marsbit1 ч. назад

How Blockchain Fills the Identity, Payment, and Trust Gaps for AI Agents?

marsbit1 ч. назад

Торговля

Спот
Фьючерсы
活动图片