Web3 手抄报:本周不容错过的行业热点及爆款

长文源:foresightnewsОпубліковано о 2023-11-03Востаннє оновлено о 2023-11-04

Анотація

比特币迎来十五周年,SBF 迈向「世纪审判」终局。

Foresight News 带你速览本周热门话题与推荐内容:


01 比特币十五周年

《比特币十五年演变:超越原始白皮书的进化之路》

《比特币挖矿叙事新解:南方国家能源发展的希望?》

02 SBF「世纪审判」终局

「炮轰」SBF,检方结案陈词还说了啥?

《SBF 庭审实录,「世纪审判」迈向终局》

《FTX 暴雷一年了,加密做市商们还好吗?》

《Coinbase 首席政策官:加密立法已摆脱 FTX 阴影,燎原只是时间问题》

03 项目观察

《押注 RWA 赛道,MakerDAO 与 Frax 孰优孰劣?》

《Polygon 联创「出走单干」,一览 Avail 的数据可用性愿景》

04 行业洞察

Paul Veradittakit:Pantera 正在关注的三个领域

《Do Kwon 被捕全过程:「每个人都在找我」》

《20% 的美国人拥有加密货币?别太乐观,还没那么多》

《马克·库班:Crypto 需要「奶奶也想用的应用」,NFT 终将「王者归来」》


01 比特币十五周年


10 月 31 日是比特币白皮书发布的十五周年,这十五年来,比特币不断发展、不断成长。推荐文章:


比特币十五年演变:超越原始白皮书的进化之路

十五年来,比特币的发展超出了个人可以轻易追踪的范围。自最初的比特币白皮书以来,这段时间已经出现了大量的白皮书。那么,为什么我们每年的这一天都只关注一份原始白皮书呢?仅在去年,就发布了五份可能彻底改变人们与比特币互动方式的重要白皮书。
比特币本身继续存在,就像现在一样,它是一项巨大的、改变世界的成就,但这还不足以创造我们许多人希望看到的世界。当前,比特币尚无法满足足够的规模和功能,以为使用它的人们提供服务的方式来服务整个世界。还有很多工作要做,很多问题要解决,还有很多白皮书要写。


当主流媒体在诋毁比特币挖矿时,有越来越多的数据表明,比特币挖矿不仅能够支持当地的经济发展,而且还增加了当地电网基础设施的弹性。推荐文章:


比特币挖矿叙事新解:南方国家能源发展的希望?

根据德克萨斯州农工大学的数据,比特币挖矿负荷与电力系统范围内的本地电力价格和电力负荷表现出强烈的负相关性。相反,非比特币挖矿活动与电力负荷和价格呈正相关。这意味着比特币挖矿不会对电网造成压力。
德克萨斯州区块链委员会主席 Lee Bratcher 指出,德州电力可靠性委员会(ERCOT)数据表明,比特币矿工的减产努力对电网产生了重大的积极影响。他总结道:「我们认识到,ERCOT 需要更多地了解这些减产的时间,并正在与 ERCOT 合作,以确保实现这一目标。」通过参与需求响应计划,矿工在高需求期间关闭矿机,以确保电力服务的连续性。Bratcher 还补充说,仅在德克萨斯州,比特币矿工就创造了大约 2000 个农村就业岗位。


02 SBF「世纪审判」终局


11 月 3 日,FTX 创始人 SBF 在纽约受审时被判犯有全部七项刑事罪名。据称,如果届时 SBF 被判所有罪名的最高刑罚,将面临 115 年的监禁,SBF 的「世纪审判」也迈向终局。在陈词阶段,检方直指 SBF 贪婪成性、撒谎成瘾、实施欺骗客户和窃取资金等行为,请求伸张正义。推荐文章:


《「炮轰」SBF,检方结案陈词还说了啥?

Nicolas Roos 总结称,我们讨论了被告通过显示客户余额而同时实际上没有这笔钱而建立的虚假借口,讨论了被告建立的信任关系,讨论了被告如何通过让客户相信他们可以信任他来精心策划该计划,讨论了被告如何盗窃和如何挪用资金,并且详细讨论了压倒性的证据,即,证明被告知道自己所做的事情是错误的,知道客户资金发生了什么,有欺诈意图。我们已经检查了所有证据,证明他对客户实施了这些欺诈行为,电汇欺诈也满足。


回顾 10 月 30 日的庭审实录,SBF 重返证人席,接受针对加密货币交易所 FTX 倒闭的欺诈审判,在证词中,SBF 试图强调,虽然他担任 FTX 首席执行官,但他并不总是了解公司运作方式,并将 Alamede 在 FTX 有几乎无限信贷额度的事归咎于前同事 Nishad Singh 和 Gary Wang。推荐文章:


SBF 庭审实录,「世纪审判」迈向终局

SBF 并没有像周四陪审团在场的初次盘问那样给出那种漫无目的的答案,他的回答更加简短。
SBF 在回答检察官问题时,经常说不记得自己到底说过什么,「我不确定」(I am not sure)成为标准的回答。有时他也没有直接回答问题,这促使 Lewis Kaplan 法官一度告诉他「只回答问题」。
检察官试图指出 SBF 关于 FTX 风险管理以及他在交易所倒闭前后参与 Alameda 的说法的差异,试图戳破 SBF 的可信度。


Alameda Research 倒闭近一年后,加密资产的做市业务仍在努力复苏中,加密做市商们的现状如何?推荐文章:


FTX 暴雷一年了,加密做市商们还好吗?

Digital Asset Capital Management 联合创始人 Richard Galvin 表示,「由于交易量下降、多个司法管辖区的监管框架不确定以及对交易所交易对手风险的担忧加剧,今年对做市商来说非常艰难。」 他补充说,如果最近的反弹持续下去,「对于仍然活跃在市场上的做市商和交易者来说将是一个可喜的获利机会」。自一年前 FTX 崩溃以来,各交易所的交易量减少了一半。


FTX 的倒闭和 SBF 的被捕除损害了加密行业的声誉,使得许多立法者不愿参与进来,加密立法之路遥遥。如今,情况开始好转,Coinbase 正带头在华盛顿特区为加密货币辩护。《财富》(Fortune)杂志采访了 Coinbase 首席政策官 Faryar Shirzad,详细了解了 Coinbase 在帮助推进加密立法方面所做的工作,以及自 FTX 倒闭以来立法者的观点发生了怎样的变化。推荐文章:


Coinbase 首席政策官:加密立法已摆脱 FTX 阴影,燎原只是时间问题

Faryar Shirzad:Coinbase 与华盛顿特区立法者合作的主要方法是教育、与政策制定者会面,对于大多数立法者来说,这意味着几乎从零开始。我从事过公共政策,我从来没有遇到过任何一个我工作过的领域会经常发生这样的情况:
你走进一个房间,里面有立法者,然后不可避免地会有其它人,譬如一个工作人员、立法者的家人或其他什么人,他们对加密货币很了解并谈论它,因此,与立法者的谈话,通常从他们对学习更多内容的浓厚兴趣开始。
Coinbase、其他业内人士以及基层民众都有责任帮助政策制定者理解「什么是加密货币?」「这有什么关系?」「为什么我们需要制定正确的公共政策?」,我认为,一旦我们进行了这些对话,事情就不可避免地会朝着一个更好的方向发展。
我们很幸运,这不是一个党派问题。有一些政策制定者对加密货币非常敌视——Elizabeth Warren 可能是头号人物,美国证券交易委员会(SEC)的 Gary Gensler 也是如此。
但总的来说,这不是一个党派问题,民主党人对此持开放态度,共和党人也是如此,但作为社区和行业,我们必须接受并承担起教育的责任。


03 项目观察


作为去中心化稳定币,MakerDAO 与 Frax 现在都以大量 RWA 资产作为储备,那么这两个 DeFi 巨头谁更胜一筹?推荐文章:


押注 RWA 赛道,MakerDAO 与 Frax 孰优孰劣?

DAI 的储备包括 ETH、稳定币和 RWA,其中大部分是美国国债。FRAX 储备状况近期有所变化,Terra 之后开始从算法稳定币转向抵押稳定币,目前抵押率已接近 100%,之后也不会将 FXS 作为储备。此外,近期 Frax 将 sFRAX 作为 RWA 储备资产,之后还会推出 FXB(债券)。


今年 3 月,Polygon 的三名联创之一的 Anurag Arjun 宣布离职,称将带领其团队全身心投入到了另一个新项目 Avail 上。Avail 已从 Polygon 分拆了出来,作为独立实体运营。推荐文章:


Polygon 联创「出走单干」,一览 Avail 的数据可用性愿景

从分拆至今,Avail 在 6 月开启了为期三个月的 Kate 测试网,推出了「数据证明桥」,并与 Equilibrium Group 合作开源了 Optimism EVM(OpEVM)软件开发工具包(SDK)新原型,Avail 称 Kate 测试网有望在 10 月结束,接下来最重要的进展就是将推出激励测试网,而主网上线的时间预计为 2023 年第四季度或 2024 年第一季度。


04 行业洞察


Pantera Capital 管理合伙人 Paul Veradittakit 分享了 Pantera Capital 正在关注的三个领域:社交和消费者用例、ZK 支持的模块化和可组合性和比特币生态系统。推荐文章:


Paul Veradittakit:Pantera 正在关注的三个领域

Web2 已经从社交转向金融,而 Web3 正在从金融转向社交。从 Friend.tech 到链上忠诚度,最近 Web3 的社交元素受到越来越多的关注,寻求利用代币化来改变社交行为。随着消费者在链上的交易可能变得更加频繁,我们相信稳定币作为 DeFi 和 TradFi 之间的入口和出口结算解决方案将发挥越来越重要的作用。此外,生成式人工智能的最新进展可能会带来更加抽象、个性化和简化的用户体验。随着人工智能抽象的推广,我们希望它能够减少 Web3 的入门和教育障碍,使非技术背景的人更容易访问区块链数据。


价值 400 亿美元的加密货币 LUNA 崩盘后,Do Kwon 穿越亚洲和欧洲以逃避当局的抓捕。黑山最高警官、内政部长 Filip Adžić 向《华尔街日报》讲述了逮捕过程。推荐文章:


Do Kwon 被捕全过程:「每个人都在找我」

黑山法院判定 Adžić和 Han 使用伪造护照罪名成立。法院判处他们四个月监禁,但在等待引渡时可以关押更长时间。Kwon 表示,他没有意识到这些护照是假的,他被新加坡给他护照的机构欺骗了。自被捕以来,Kwon 一直被关押在斯普兹监狱,这是波德戈里察附近山谷中的一组砖砌建筑。他每天可以在一个院子里呆一小时,院子里有铁丝网、杂草丛生的田野和布满岩石的山坡。 一位知情人士称,入狱后,Kwon 与妻子曾重聚,泪流满面,他对自己给妻子和年幼的女儿带来的麻烦表示遗憾。 


Coinbase 声称目前有 5200 万美国成年人持有加密货币,占美国成年人口的 20%,是否真的如此?推荐文章:


20% 的美国人拥有加密货币?别太乐观,还没那么多

SDCPC 发现,2022 年,9.6% 的美国成年人拥有加密货币,高于 2021 年的 9.1%,也远高于 2015 年调查的 0.6%。不过,这远低于 Coinbase 声称的 20%。这些数字中只有一个是正确的,是哪一个呢? SDCPC 的历史调查结果如下表所示。


「Shark Tank」投资人和达拉斯独行侠队的老板 Mark Cuban(马克·库班),1999 年以近 60 亿美元的价格将自己的网络电台创业公司卖给了雅虎。而他目前认为 Alexa 和 ChatGPT 是商机,加密货币需要杀手级应用,并表示看好 NFT。推荐文章:


马克·库班:Crypto 需要「奶奶也想用的应用」,NFT 终将「王者归来」

「NFT 市场确实糟透了,但你知道有多少其他行业也很糟糕吗?互联网股崩溃后,亚马逊曾一度以每股 5 美元的价格出售,微软的售价只有现在的几百分之一。我不会告诉你该做什么或不该做什么,我只想说,对于 NFT 而言,最好的购买时机是当你是一个收藏家并且你喜欢 NFT 的时候。」
「不要为了投机而购买。投机者的下场大多都很惨。总有一天,你会回头对自己说,『我应该在 NFT 快变成什么都不是的时候买下那些 NFT』。」

Пов'язані матеріали

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

Silicon Valley investor and "Godfather of Startups" Steve Hoffman warns that combining Web3 with AI is likely a trap, not a promising venture. In an interview, Hoffman argues that while AI is a foundational technology touching all industries, Web3 adds complexity, friction, and regulatory risk without solving mainstream consumer or business needs. He advises founders to focus on deep, specialized applications where startups can out-iterate giants, rather than on generic features easily replicated by large tech companies. Hoffman observes that Silicon Valley will lead foundational AI research, while China excels at rapid, large-scale application and commercialization, particularly in robotics. He stresses that AI-driven autonomous agents capable of collaborative, multi-step tasks are 2-4 years away, which will cause significant job displacement. The solution is not to slow AI but to redesign business models around human-AI collaboration and reform social systems like education and retraining. For startups, Hoffman recommends focusing on vertical, expertise-heavy domains to build defensibility. He sees major opportunities in AI fraud detection and cybersecurity. Key founder mindsets include systemic thinking over feature-focus, relentless customer centricity, building adaptive teams, and deeply understanding AI's capabilities and limits. Hoffman is also leading a non-profit initiative to establish university centers aimed at training future leaders in responsible, human-value-aligned AI innovation.

marsbit1 год тому

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

marsbit1 год тому

Token Inefficient, Economy Tokenless

The article "Tokens Aren't Economical, Economics Aren't Tokenized" analyzes a pivotal shift in the AI industry from a technology-driven narrative to one dominated by capital efficiency. It highlights two concurrent trends: a severe capital shortage due to the exorbitant and recurring costs of compute (e.g., OpenAI's high burn rate) and a wave of corporate spin-offs where major tech companies are separating their AI units (like Kuaishou's Kling and Baidu's Kunlunxin). The core argument is that AI's "anti-internet" business model, where user growth increases costs rather than profits, has created a disconnect between high valuations and actual cash flow. Spin-offs address this by allowing AI assets to be valued independently. Within a parent company, they are seen as cost centers, but as standalone entities, they are priced based on their growth potential and scarcity in the primary market, leading to massive valuation premiums (e.g., Kling's estimated value tripling post-spin-off). The industry is at an inflection point, moving from "model worship" to "value realization." The competition is evolving from a pure compute (GPU) race to a broader focus on systemic efficiency and full-stack engineering (involving CPUs and orchestration) to achieve viable commercialization. The year 2026 is framed as a critical moment where the industry must definitively answer how to economically translate AI capability into tangible business value, reshaping the sector's future power structure.

marsbit1 год тому

Token Inefficient, Economy Tokenless

marsbit1 год тому

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

In 2026, a historic shift occurred in AI as major cloud providers' inference spending surpassed training spending for the first time, signaling a move from "building large models" to "using large models." This shifts the core challenge from computing power to the "memory wall"—the bottleneck of data movement (model weights, activations, KV Cache) between external DRAM and processors, where energy and latency from data transfer far exceed computation itself. Companies like Nvidia face GPU idle time due to bandwidth limits. In contrast, Cerebras Systems adopts a radical "wafer-scale" approach with its Wafer-Scale Engine (WSE). Instead of cutting a silicon wafer into many chips, Cerebras uses almost the entire wafer as one massive chip (WSE-3). This design provides 44GB of on-chip SRAM, delivering memory bandwidth thousands of times higher than traditional HBM (e.g., 21 PB/s vs. Nvidia B200). For LLM inference, weights are streamed layer-by-layer from external MemoryX storage to the chip, avoiding HBM bottlenecks. This results in token generation speeds 1.5–5 times faster than Nvidia's B200 in some models and significant advantages in first-token latency and long-context tasks. Additionally, Cerebras's architecture offers much lower interconnect power consumption (0.15 pJ/bit vs. GPU's ~10 pJ/bit). However, Cerebras faces challenges: SRAM scaling has slowed with advanced nodes, limiting future capacity gains; the chip requires specialized liquid cooling and custom software stacks; and its external I/O bandwidth (150 GB/s) is low compared to NVLink, hindering multi-system scaling for very large models. Competition is intensifying. Major players are pursuing three paths: 1) Developing proprietary inference ASICs (e.g., Google TPU, Microsoft Maia), 2) Leveraging advanced packaging (e.g., TSMC's SoW) to democratize wafer-scale-like integration, potentially eroding Cerebras's process advantage within a few years, and 3) Exploring optical interconnects for ultimate bandwidth. Commercially, Cerebras is transitioning from a hardware vendor to a service provider, facing the immense challenge of building high-power, specialized data centers to meet large contracts (e.g., 250MW/year from 2026–2028). In conclusion, the AI inference era presents a fundamental architectural trade-off. Cerebras opts for extreme physical optimization for low-latency, single-task performance, while Nvidia prioritizes versatility and massive cluster throughput. The path forward remains uncertain, with technology and business models still evolving in the race toward advanced AI.

marsbit1 год тому

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

marsbit1 год тому

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

**Title: Has Bitcoin's Rebound Ended, Entering the Late Bear Market Phase?** **Summary:** Bitcoin's price has declined by 13% this week, signaling a potential return to late-stage bear market conditions. The price fell to around $67k, positioned between the Realized Price and Realized Cap Weighted Average. For the first time since early 2022, the Short-Term Holder cost basis has dropped below this key average, confirming a hallmark of late-cycle bear markets. Profitability metrics have collapsed sharply. The 7-day average of the Realized Profit/Loss ratio plummeted from a local high of 3.16 to 0.29, mirroring the February panic sell-off. Critically, the 90-day average never breached the threshold of 2, indicating the recent rally to $82k was a bear market bounce, not a structural shift. Realized losses surged to $1.35 billion daily, with $770 million coming from Long-Term Holders selling at a loss. This accelerating redistribution of supply from weak to strong hands is a necessary but ongoing process for a market bottom. The rally stalled almost precisely at the aggregate cost basis (~$83k) of US spot Bitcoin ETF investors, turning that level into strong resistance and leaving the average ETF holder underwater again. Spot market flows have turned decisively negative, showing sellers are dominating order books despite the price drop. While a significant futures long liquidation event cleared over $400 million in leverage, providing a potential reset, sustained spot demand is yet to materialize. Options markets continue to price in higher future volatility (Implied Volatility) than recent price action (Realized Volatility) has shown, with a persistent skew towards put options, indicating ongoing demand for downside protection. In conclusion, multiple metrics point to a fragile market structure. Resistance at the ETF cost basis, accelerating realized losses, dominant spot selling, and cautious options pricing all suggest the bear market trend persists. A sustainable recovery likely requires a resurgence of spot demand, ETF holders returning to profit, and a clear reduction in selling pressure.

marsbit1 год тому

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

marsbit1 год тому

TechFlow Intelligence Agency: Anthropic Calls for Global Pause in AI Development While Preparing for Trillion-Dollar IPO; SpaceX IPO Roadshow Heats Up, But S&P 500 Rejects Fast-Track Inclusion

In today's TechFlow Intelligence Briefing, several major tech stories highlight a growing theme of trust and credibility gaps across AI, crypto, and finance. AI company Anthropic has publicly called for a global pause in AI development, citing risks from Claude's "recursive self-improvement." Ironically, this coincides with reports the company is preparing for a massive IPO targeting a near $1 trillion valuation. This perceived hypocrisy, coupled with widespread user complaints about Claude's declining performance, is sparking debate over whether the safety warning is genuine or a competitive tactic. Meanwhile, in a substantive security move, Anthropic open-sourced a framework for AI-powered vulnerability discovery. In the crypto market, Bitcoin's price drop below $61,000 triggered over $1.16 billion in liquidations, flipping the market into a state where more BTC is held at a loss than at a profit, a historical bearish signal. On the corporate front, SpaceX's highly anticipated IPO is generating immense Wall Street excitement, with Goldman Sachs projecting 100x revenue growth by 2030. However, the S&P 500 has refused to fast-track the company's inclusion post-IPO, potentially limiting immediate institutional demand. Separately, ByteDance's AI app Doubao lost over 6 million monthly active users after introducing a subscription model, highlighting the challenges of AI monetization. Other notable developments include Nvidia certifying HBM4 memory from Samsung, SK Hynix, and Micron; Cloudflare's acquisition of front-end tooling company VoidZero; and its CEO warning that bot traffic now exceeds human traffic online. The underlying narrative connects these events: a trust crisis. From AI firms' contradictory actions and crypto volatility to the clash between SpaceX's hyped narrative and institutional rules, a pattern is emerging where stated intentions and actual practices are increasingly misaligned.

marsbit1 год тому

TechFlow Intelligence Agency: Anthropic Calls for Global Pause in AI Development While Preparing for Trillion-Dollar IPO; SpaceX IPO Roadshow Heats Up, But S&P 500 Rejects Fast-Track Inclusion

marsbit1 год тому

Торгівля

Спот
Ф'ючерси
活动图片