【研报精选】有望在下一轮牛市继续爆发?Solana可能是优秀的壳资源链

MirrorPublicado a 2022-12-23Actualizado a 2022-12-29

Resumen

数据显示Solana上的开发者贡献数量在SOL代币价格下跌95%的情况下仍然呈现年2.5倍的增长。对这个数据略持怀疑。如今Solana上的初始投资机构Multicoin等早就赚的盆满钵满,渐渐会退出Solana的主导和控制。道理也不难明白,套现走人了而已。同样的,未必是坏事。Sam的崩溃和机构的有序撤退,让Solana变得纯粹。在有优秀壳资源的前提之下,有社区化的可能性。至于下轮周期是否能突破前十,还是下一个EOS,就看运气吧。

FTX崩溃后,Solana的TVL骤减67%,遭受重创。墙倒众人推。“Sam Coin、Sam Chain”完蛋了是许多人的直觉。不过Messari最近的一篇报告表明Solana的情况没有外界想象的糟糕。即便是在Sam失势后,Solana仍然具有重要的壳资源价值。脱离Sam的Solana反倒给了自己一次凤凰涅槃的机会。

从协议层面的进展,有由Jump推出的Firedancer轻客户端。公链的轻客户端越多,网络宕机的整体性风险也就越小。包括最近A16Z自己开发的以太坊轻客户端Helios是同样的道理。

也有Jito-solana这样结合流动性质押和MEV价值索取的应用。MEV Bot在每条公链成为标配。而以太坊上的FlashBot近期也公布了计划,有计划成为一条MEV Chain。类似于Dydx从以太坊生态的应用迁移到Cosmos做独立链。

说到DyDx去Cosmos上做应用链,我会觉得诸如此类的迁移更多是“叙事先行”。打铁还需自身硬。本质上还是得看自己能否被市场接受。一个本来能力就不行的项目,迁移到哪条链都是无济于事。当然不否认公链自身的用户属性和时机对项目崛起的重要性。像Axie就经历了EOS到ETH漫长的跨越周期的迁移探索。以及GMX从BSC迁移至Arbitrum后成为Arb最核心的项目。

无论是整体链,还是应用链。无论是L1还是L2。ZK也好,Optimistic也好。以及以上的所有排列组合。一切都是技术革新上的探索 哲学层面的探讨。最终还要落实到创新性项目诞生并且被市场接受。实际上每一条链,每一条L2,每一条Rollup能诞生一个爆款应用并且围绕它产生生态,已是成功。这也符合马太聚集效应的理论。A16Z的基础堆栈和应用迭代理论是神作。

像其他优化节点和数据效率的一些进展,QUIC/QOS/Local Fee Market等等因过于技术不赘述。

作为PoS网络,去中心化的问题逃不过。尽管有2000多个节点,130多个数据中心,35个区域,网络仍然集中在少数节点/数据中心/区域中。PoS网络都逃不过这个问题,以太坊几万个节点也无可避免。追溯到五年前,十年前,PoW网络也是集中的。既然世界上的财富本就是集中的,我倒是更愿意接受PoW转PoS是为了减少环境污染的说辞。

Solana上的所有游戏,典型像Aurory/Star Atalas等等,在21/22年曾经轰轰烈烈,至今未上线主网,大概率是难产了。Eclipse and Nitro是两个有趣的项目,他们在尝试把Solana的虚拟机SVM迁移到Celestia和Cosmos这类的Rollup链上。Solana曾经让大家一度相信是一条专注于专业Trading的链,因此在订单本Dex/专业衍生品领域会有大突破。Drift,/Zeta Markets/Friktion/PsyOptions这些衍生品项目,也都是不温不火。在Serum崩溃之后,出现了几个社区主导的Sreum Fork项目OpenBook,/Ellipsis Labs/Lifinit等。这未尝不是一件坏事。也许Solana真的是一条有专业交易优势的链,只是前期过多的被Sam主导导致没有发挥出其优势。

数据显示Solana上的开发者贡献数量在SOL代币价格下跌95%的情况下仍然呈现年2.5倍的增长。对这个数据略持怀疑。如今Solana上的初始投资机构Multicoin等早就赚的盆满钵满,渐渐会退出Solana的主导和控制。道理也不难明白,套现走人了而已。同样的,未必是坏事。Sam的崩溃和机构的有序撤退,让Solana变得纯粹。在有优秀壳资源的前提之下,有社区化的可能性。至于下轮周期是否能突破前十,还是下一个EOS,就看运气吧。

的应用迁移到Cosmos做独立链。

说到DyDx去Cosmos上做应用链,我会觉得诸如此类的迁移更多是“叙事先行”。打铁还需自身硬。本质上还是得看自己能否被市场接受。一个本来能力就不行的项目,迁移到哪条链都是无济于事。当然不否认公链自身的用户属性和时机对项目崛起的重要性。像Axie就经历了EOS到ETH漫长的跨越周期的迁移探索。以及GMX从BSC迁移至Arbitrum后成为Arb最核心的项目。

无论是整体链,还是应用链。无论是L1还是L2。ZK也好,Optimistic也好。以及以上的所有排列组合。一切都是技术革新上的探索 哲学层面的探讨。最终还要落实到创新性项目诞生并且被市场接受。实际上每一条链,每一条L2,每一条Rollup能诞生一个爆款应用并且围绕它产生生态,已是成功。这也符合马太聚集效应的理论。A16Z的基础堆栈和应用迭代理论是神作。

像其他优化节点和数据效率的一些进展,QUIC/QOS/Local Fee Market等等因过于技术不赘述。

作为PoS网络,去中心化的问题逃不过。尽管有2000多个节点,130多个数据中心,35个区域,网络仍然集中在少数节点/数据中心/区域中。PoS网络都逃不过这个问题,以太坊几万个节点也无可避免。追溯到五年前,十年前,PoW网络也是集中的。既然世界上的财富本就是集中的,我倒是更愿意接受PoW转PoS是为了减少环境污染的说辞。

Solana上的所有游戏,典型像Aurory/Star Atalas等等,在21/22年曾经轰轰烈烈,至今未上线主网,大概率是难产了。Eclipse and Nitro是两个有趣的项目,他们在尝试把Solana的虚拟机SVM迁移到Celestia和Cosmos这类的Rollup链上。Solana曾经让大家一度相信是一条专注于专业Trading的链,因此在订单本Dex/专业衍生品领域会有大突破。Drift,/Zeta Markets/Friktion/PsyOptions这些衍生品项目,也都是不温不火。在Serum崩溃之后,出现了几个社区主导的Sreum Fork项目OpenBook,/Ellipsis Labs/Lifinit等。这未尝不是一件坏事。也许Solana真的是一条有专业交易优势的链,只是前期过多的被Sam主导导致没有发挥出其优势。

数据显示Solana上的开发者贡献数量在SOL代币价格下跌95%的情况下仍然呈现年2.5倍的增长。对这个数据略持怀疑。如今Solana上的初始投资机构Multicoin等早就赚的盆满钵满,渐渐会退出Solana的主导和控制。道理也不难明白,套现走人了而已。同样的,未必是坏事。Sam的崩溃和机构的有序撤退,让Solana变得纯粹。在有优秀壳资源的前提之下,有社区化的可能性。至于下轮周期是否能突破前十,还是下一个EOS,就看运气吧。

Lecturas Relacionadas

Ethereum Q1 2026 Report: Fees Decline, Users and Transaction Volume Hit New Highs

Ethereum Q1 2026 Report: Fees Down, Users & Transactions Hit New Highs Token Terminal's Q1 2026 report on Ethereum presents a pivotal development: the network achieved record highs in monthly active users (13.2M, +85.9% YoY), total transactions (200.4M, +81.5% YoY), and throughput (25.78 TPS), while transaction fees on the mainnet plummeted by 47.9% quarter-over-quarter. This shift is attributed to the network's strategic move into a "low fees for scale" phase, exemplified by the Fusaka upgrade which increased data capacity and lowered block space costs, releasing pent-up demand (a manifestation of Jevons's Paradox). The report highlights a core narrative shift for Ethereum: from a DeFi-centric blockchain to a global financial settlement layer. It maintains a dominant position in tokenized assets, holding majority market shares among top chains in stablecoins (61.8%), tokenized funds (73.0%), and tokenized commodities (84.0%). Growth in tokenized funds (+73.1% YoY) and commodities (+325.9% YoY) was particularly strong, driven by institutions like BlackRock and JPMorgan entering the space. Contrasting these usage gains, several USD-denominated value metrics declined in Q1: fully diluted market cap fell 30.3% QoQ, total value locked (TVL) dropped 11.0%, and ecosystem transaction volume decreased 24.0%. The report interprets this as Ethereum prioritizing long-term network expansion and cementing its role as the default settlement layer for finance over short-term fee capture. The commentary from Etherealize argues that, much like the early internet, Ethereum's open, permissionless model is poised to win over closed alternatives as institutional tokenization accelerates.

marsbitHace 49 min(s)

Ethereum Q1 2026 Report: Fees Decline, Users and Transaction Volume Hit New Highs

marsbitHace 49 min(s)

He Just Raised 2.7 Billion, and Li Fei-Fei Also Invested

Pete Florence, a former senior research scientist at Google DeepMind and a key contributor to the Vision-Language-Action (VLA) model architecture, is deliberately distancing his startup, Generalist AI, from the trendy "world model" label. He argues that the industry should prioritize concrete goals over buzzwords. His goal is to create robots that can perform a vast range of unseen tasks with high speed and success rates, without needing task-specific training data. Recently, his company raised $400 million (¥2.7 billion) at a $2 billion valuation. Notable investors include NVIDIA's NVentures, Bezos Expeditions, NFDG, as well as Xiaomi co-founder Lin Bin, Zoom founder Eric Yuan, and renowned AI scientist Fei-Fei Li. Florence's approach stems from his academic background at MIT under Professor Russ Tedrake, focusing on understanding the physical world. After joining DeepMind, he developed models like Transporter Network and co-created the VLA framework. He left in 2025 to found Generalist AI. The company has launched two models: GEN-0, which demonstrated that scaling laws apply to physical motion, and GEN-1. GEN-1 was trained on over 500,000 hours of physical interaction data collected via a specialized wearable device. It achieves a 99% success rate on precise mechanical tasks like folding boxes and maintains performance three times faster than its predecessor. Florence believes GEN-1 is reaching a commercial utility threshold similar to the GPT-3 inflection point. The substantial funding round, following GEN-1's release, signifies strong investor confidence in Generalist AI's practical, goal-driven path to creating versatile, useful robots, regardless of the "world model" terminology.

marsbitHace 56 min(s)

He Just Raised 2.7 Billion, and Li Fei-Fei Also Invested

marsbitHace 56 min(s)

Two Legends Lost in Three Days: Is Google's AI Talent Dam Cracking?

In three days, Google lost two AI legends. On June 18, Noam Shazeer, co-author of the seminal "Attention is All You Need" paper and Gemini co-lead, left for OpenAI. Just 48 hours later, John Jumper, 2024 Nobel laureate and AlphaFold lead, departed DeepMind for Anthropic. This follows Andrej Karpathy joining Anthropic in May. These moves highlight a structural trend: top AI talent is concentrating at mission-driven, pre-IPO firms like OpenAI and Anthropic, while Google becomes a primary source. The exodus stems from a core mission mismatch. Google's ad-centric model often subordinates AI research to product and revenue goals, creating friction for pioneers like Shazeer, who returned in 2024 only to leave again. In contrast, OpenAI and Anthropic offer singular focus on pushing AI boundaries, whether towards AGI or safety-aligned models, which deeply appeals to top researchers like Jumper. Financial incentives amplify the pull. With both OpenAI and Anthropic nearing IPO, employees stand to gain immensely from equity, an upside Google's mature stock cannot match. Furthermore, the 2023 merger of Google Brain and DeepMind, intended to consolidate strength, has instead created cultural tension and slowed the path from research to product, as evidenced by Gemini's pace. This talent redistribution is reshaping the AI landscape. While Google retains vast data and compute resources, its true crisis is the quiet, continuous loss of the people who define the field's future. The real moat in AI is not infrastructure, but the concentration of brilliant minds—a battle Google is currently losing.

marsbitHace 2 hora(s)

Two Legends Lost in Three Days: Is Google's AI Talent Dam Cracking?

marsbitHace 2 hora(s)

Behind the AI Report Card, Lies a Chinese 'Exam Setter'

Beyond the familiar performance charts like MMLU-Pro and MMMU, which major AI models strive to ace, stands a key "examiner": Chinese-Canadian researcher Wenhu Chen. An assistant professor at the University of Waterloo and founder of TIGERLab, Chen addresses the crucial need for more rigorous AI evaluation. As models like GPT-4 began scoring near-perfect results on older benchmarks like MMLU, it became difficult to distinguish their true capabilities. In response, Chen introduced MMLU-Pro in 2024, featuring harder, more reasoning-focused questions with more answer choices, successfully reintroducing meaningful performance gaps. His work extends to multi-modal evaluation with MMMU and its enhanced version, MMMU-Pro. These benchmarks test a model's ability to understand and reason with complex information from images, charts, and text across diverse academic subjects, exposing the significant challenges even top models face in genuine comprehension. Chen's background in complex QA, table reasoning, and his experience at Google DeepMind on projects like Gemini inform his approach. He understands that effective benchmarks must anticipate how models might "cheat" by memorizing data or avoiding visual analysis. His lab also actively researches video understanding and generation models (e.g., UniVideo, Vamba), ensuring his evaluation work is grounded in practical model-building challenges. Now at Meta's Super Intelligence Lab, Chen continues his focus on multi-modal data and evaluation, representing the deep yet often unseen contributions of Chinese talent in shaping the fundamental tools of the AI industry.

marsbitHace 3 hora(s)

Behind the AI Report Card, Lies a Chinese 'Exam Setter'

marsbitHace 3 hora(s)

Trading

Spot
Futuros
活动图片