晚间必读5篇 | Solana 的流动性质押概况

币界网Published on 2024-07-18Last updated on 2024-07-18

币界网报道：

1.Grayscale：Crypto x AI项目一览 Crypto如何实现去中心化AI

AI是本世纪最有前途的新兴技术之一，它有潜力成倍提高人类生产力并推动医学突破。尽管AI在今天可能很重要，但它的影响力只会越来越大，普华永道估计，到 2030 年，它将发展成为一个价值 15 万亿美元的产业。点击阅读

2.Galaxy：以太坊再质押的成本与收益

业界通过模块化来扩展区块链的实验导致了许多新协议和支持中间件的创建。然而，这些网络中的每一个都需要建立自己的安全护城河，通常是通过权益证明 (PoS) 共识的变体，这是一个资源和时间密集型的过程，导致了许多孤立的安全池。点击阅读

3.Vitalik：我为何反对根据“是否支持加密”进行政治投票

在过去的几年里，“加密货币”已经成为政治政策中越来越重要的话题，各个司法管辖区都在考虑出台法案，以各种方式规范各种参与者从事区块链事务。这包括欧盟的加密资产市场监管 (MiCA)、英国对稳定币的监管努力，以及我们在美国看到的美国证券交易委员会复杂的立法和执法监管尝试。在我看来，这些法案中的许多都是合理的，尽管有人担心政府会尝试采取极端措施，比如将几乎所有的货币都视为证券或禁止自托管钱包。在这些担忧之后，加密货币领域越来越倾向于更加积极地参与政治，并且几乎完全根据政党和候选人是否愿意对“加密货币”宽容和友好来决定他们是否支持这些政党和候选人。点击阅读

4.深度解析RGB → RGB++ → RGB++Layer之间的演进到底发生了什么？

RGB++协议近日完成了RGB++ Layer升级，可以将无桥跨链和智能合约扩展到BCH、BSV、Dogecoin这些所有UTXO链，并支持Runes、BRC20等其他Layer 1资产协议，RGB++ Layer的首个DEX UTXOSwap也同步上线主网，根据计划后续生态还会继续推出单独的浏览器、IBO等平台，再来聊聊RGB++以及这轮牛市的大黑马CKB吧，探讨RGB++与RGB之间的关系，以及为什么要将RGB++升级为RGB++ Layer。点击阅读

5.Bankless：Solana 的流动性质押概况

质押，即锁定资本以换取网络安全，从而获得收益，是 DeFi 的重要组成部分，也是链上经济中最强大的部门之一。质押要求因链而异；以太坊要求在个人节点上进行 32 ETH 的原生质押，或者用户可以选择 Lido 或 Rocket Pool 等流动质押提供商。在 Solana 上，任何人都可以通过其委托的权益证明系统进行原生质押，方法是委托给验证者，而不是运行自己的节点。点击阅读

Trending Cryptos

ctr
CitreaCTR
wstusdt
wrapped stUSDTWSTUSDT
apr
aPrioriAPR
audio
AudiusAUDIO
mantra
MantraMANTRA
xvs
VenusXVS
waxl
AxelarWAXL
bill
Billions NetworkBILL
pyth
PYTH (Pyth)PYTH
rune
THORChainRUNE
velodrome
Velodrome FinanceVELODROME
brev
BrevisBREV
zrx
ZRX（0X）ZRX
cake
PancakeSwapCAKE
jst
JUSTJST

Related Reads

Ethereum down 45% YTD – So why do SharpLink and whales keep buying?

Despite Ethereum (ETH) being down 20-45% year-to-date amid broader crypto weakness, institutional and whale buying activity suggests growing long-term conviction. SharpLink, after an eight-month pause, purchased 5,000 ETH and later added $45.54 million in LSETH, increasing its total holdings significantly despite substantial unrealized losses. Similarly, a new whale wallet accumulated over 18,000 ETH worth $28.9 million in nine days, indicating strategic positioning for future price movements rather than short-term trading. However, this accumulation contrasts with spot Ethereum ETFs, which saw net outflows of $12.85 million recently, highlighting a divergence between direct treasury/whale buyers and ETF investors. While the persistent buying from these large holders may gradually ease selling pressure, a sustained recovery for Ethereum still depends on a reversal in ETF flows and a broader improvement in network demand and market sentiment.

ambcrypto3h ago

Ethereum down 45% YTD – So why do SharpLink and whales keep buying?

ambcrypto3h ago

Just now, DeepSeek V4 updates with DSpark, improving inference speed by 80%

DeepSeek has updated its DeepSeek V4 model with the DSpark speculative decoding framework, achieving a significant 60-85% speedup in generation for Flash models and 57-78% for Pro models while maintaining the same overall throughput. This engineering-focused update, rather than a core architectural change, introduces DSpark to address latency and throughput bottlenecks in high-concurrency production environments. DSpark combines high-throughput parallel generation with adaptive load-aware verification. Its key innovations include a semi-autoregressive generation architecture to model dependencies within token blocks and a hardware-aware confidence-scheduled verification system. This system uses a confidence head to predict token acceptance probabilities, allowing it to dynamically optimize verification length per request and allocate compute only to tokens with the highest expected payoff. The asynchronous scheduler is designed for real-world deployment, ensuring zero-overhead scheduling and continuous CUDA graph replay while preserving the target model's output distribution. In tests across mathematical reasoning, code generation, and daily dialogue, DSpark outperformed state-of-the-art models like Eagle3 and DFlash, increasing average acceptance length by 26.7%-30.9% and 16.3%-18.4% respectively on Qwen3 target models. DeepSeek also open-sourced DeepSpec, a full-stack codebase for training and evaluating speculative decoding draft models, providing a standardized toolkit that includes data preparation tools, model implementations, training code, and evaluation scripts.

marsbit4h ago

Just now, DeepSeek V4 updates with DSpark, improving inference speed by 80%

marsbit4h ago

Can Aavenomics 3.0 sustain AAVE’s recovery rally amid Kraken buyout talks?

Aave Labs CEO Stani Kulechov has dismissed reports of a potential stake sale to Kraken, clarifying that Aave would not sell at a significant discount. He highlighted Aave's substantial annualized revenue and its focus on a broad financial market. Kulechov also announced plans for Aavenomics 3.0, featuring a new automated buyback mechanism. Following these updates, the AAVE token price surged 12%, extending its June recovery rally to over 50% from its recent lows. The rally is partly attributed to reduced selling pressure and positive sentiment from the announced tokenomics plan, despite the token remaining significantly below its all-time high.

ambcrypto5h ago

Can Aavenomics 3.0 sustain AAVE’s recovery rally amid Kraken buyout talks?

ambcrypto5h ago

BIT Research: The 2028 Halving Is Not the End, the Real Shake-Up of the Bitcoin Mining Industry Is Just Beginning

The Bitcoin mining industry is undergoing its most complex structural adjustment since inception. Despite Bitcoin's price holding near $61,000 and the network hash rate approaching a record 1 ZH/s, miner profitability is deteriorating. The industry is operating close to its breakeven point, with the 2028 halving expected to accelerate consolidation. The challenges extend beyond the halving's subsidy reduction; the industry's revenue model has yet to successfully transition towards a fee-driven structure. Increasingly, mining companies are evolving from simple Bitcoin producers into infrastructure and energy operators, including providers of AI/HPC computing power. Competition is shifting from pure hash rate expansion to business model upgrades. Economic pressure is evident. The theoretical daily mining revenue at current prices is around $78 million, yet the actual figure is only about $33 million—a 136% gap. Transaction fees remain low at roughly $220k daily, far below historical implied levels. With a current estimated industry-wide breakeven price near $65,000, mining alone is struggling to generate ideal profits. The 2028 halving is projected to push the fundamental production cost floor to approximately $93,289. This will likely accelerate a shift towards consolidation among larger, well-capitalized miners with diversified revenue streams. Competitive advantage will belong to institutionalized players with access to low-cost energy, AI/HPC hosting operations, and stronger balance sheets. In essence, Bitcoin mining is transitioning from a "mining business" to an "infrastructure business." Future profitability and resilience will depend less on block rewards and more on diversified income sources like energy management and computational infrastructure services. For investors, the key question is not the halving itself, but which miners can successfully navigate this business model transformation.

marsbit5h ago

BIT Research: The 2028 Halving Is Not the End, the Real Shake-Up of the Bitcoin Mining Industry Is Just Beginning

marsbit5h ago

This is How God Karpathy Uses Claude?

Andrej Karpathy, a prominent figure in AI, has reportedly joined Anthropic, leading to a noticeable decrease in his open-source contributions and social media activity. A document claiming to be his personal "CLAUDE.md" file—a set of instructions for the Claude AI to follow within a specific codebase—has been circulating online. While its authenticity is unverified, the content aligns closely with Karpathy's publicly shared principles on effective AI-assisted programming. The document outlines key rules for AI coding assistants, emphasizing the importance of reading existing code thoroughly before writing new code to maintain consistency. It advises against over-engineering, advocating for simple, surgical modifications that match the project's existing style. Other guidelines include clarifying assumptions upfront, writing meaningful tests, thoughtful debugging, and carefully considering dependencies. The core message is that these principles help prevent common AI coding failures, such as introducing unnecessary abstractions, style drift, or making invisible architectural decisions. The community has noted that even experts like Karpathy require detailed instructions to guide AI effectively, akin to managing a junior developer. A related GitHub repository, "andrej-karpathy-skills," which encapsulates these ideas, is reported to significantly reduce Claude's code error rate. Ultimately, the advice stresses that the best CLAUDE.md is tailored to one's own tech stack and coding practices.

marsbit5h ago

This is How God Karpathy Uses Claude?

marsbit5h ago

Trading

Spot

Hot Articles

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of SOL (SOL) are presented below.

活动图片

Top Questions