以太坊的低天然气费用可能推动16亿美元的供应增长

币界网Published on 2024-08-22Last updated on 2024-08-22

币界网报道:

匿名加密货币分析师Ember CN表示,以太坊天然气费用的下降可能会使其年供应量增加近16亿美元。这是因为近几个月来ETH供应量逐渐增加,以及对价格潜在影响的担忧。

根据Ultrasoundmoney的数据,在过去的四个半月里,ETH的供应量增加了228717 ETH,从4月份的120063605 ETH增加到约120292322 ETH。许多人认为,这一增长表明ETH已成为一种通胀资产,扭转了其先前的通缩状态。

以太坊网络每天生产1600多个ETH

ETH供应量的增加是由于其燃烧率低,而燃烧率低又是由于Dencun升级导致的网络费用低。虽然许多人认为低费用有利于以太坊的使用,但他们也降低了网络上的烧钱率,导致发行的ETH多于销毁的ETH。

Ember CN分析了升级以来ETH供应的增长率,指出平均每天增加1652个ETH。按年计算,以太币供应量将增长60万ETH,按当前价格计算为15.9亿美元。

他写道:

“根据这一产出数据,如果随后的ETH链活动继续疲软,年通货膨胀率将为60万枚硬币,按当前价格计算价值15.9亿美元,通货膨胀率为0.5%。”

因此,他指出,解决这个问题的唯一方法是以太坊活动增加。然而,考虑到Arbitrum、Optimism和Base等二层网络现在主导着以太坊交易,这可能不太可能。部分原因是这些网络的费用更低。

ETH通胀没什么大不了的

尽管ETH供应出现了通货膨胀,但分析师认为这不是一个大问题。他指出,这仅占其供应量的0.5%左右,这意味着它可能不会对价格产生太大影响。超声波货币的数据还显示,目前的通货膨胀率为每年0.62%。考虑到以太坊的供应和市值,这相对可以忽略不计。

Coinbase分析师认为,ETH的通胀不是由于第二层网络,而是由于以太坊主网的费用降低和ETH质押率的增加。分析师指出,ETH质押比率的增加将导致更多的发行,这将加快ETH的通胀速度。

Coinbase的机构研究分析师David Han写道:

“然而,我们不认为这是一个主要由L2扩展驱动的问题。虽然L2交易费用确实缺乏EIP-1559燃烧机制,但用于L2的总费用相对无关紧要。也就是说,即使100%的L2费用被燃烧,ETH仍将保持通货膨胀。”

然而,他们不认为ETH会因为通货膨胀而失去价值。相反,他们认为ETH的价值主张是基于应用的效用,而不是作为价值储存的价值。因此,他们预计会出现更多基于应用程序的实用程序,具有更高的可扩展性和更低的费用。

ETH供应增长PoS v PoW——超货币

尽管一些批评者质疑以太坊作为超声波货币的价值,因为它已经变成了通货膨胀,但在PoS共识下,ETH的供应增长实际上更好。根据Ultrasoundmoney的工作量证明模拟,ETH的供应量在过去30天内增加了61721个代币。根据PoW,它将增加389529个代币,每年的通货膨胀率接近4%。

事实上,自近两年前的合并以来,ETH的供应量已经减少了0.10%。该网络已消耗228696 ETH,比同期生产的ETH多。

Trending Cryptos

Related Reads

You Use Claude and Codex Every Day, but Meta Has Restricted Internal Use

In May, Meta imposed internal restrictions on its engineers regarding the use of Claude Code and Codex, two widely used AI programming tools. Despite being a major client, Meta's guidelines, still in effect, prohibit these external models from being used for specific tasks to prevent potential "escalations with partners." The core concern is "distillation"—the risk that outputs from Claude or Codex could inadvertently contaminate the training data and evaluation processes for Meta's in-house AI coding assistant, MetaCode. If MetaCode is trained or evaluated using data generated by these external models, it risks learning their capabilities rather than developing its own, blurring the line of intellectual origin. The restrictions are precise: engineers cannot use the external models to generate test questions, debug source code, or suggest test cases. AI-generated content is also barred from environments accessible to MetaCode. However, AI can still assist with peripheral tasks like workflow setup and code organization, provided all outputs are manually reviewed. This caution reflects a broader industry dilemma. While distillation is a common technique, using a competitor's model output for training raises legal and ethical questions about the ownership of derived capabilities. Contractual terms from companies like OpenAI and Anthropic explicitly forbid using their outputs to build competing products, putting enforcement power in the hands of rivals. The move is also financially motivated, as Meta seeks to reduce its hefty internal AI spending, estimated in the billions this year. Meta's policy illustrates the delicate balance companies must strike: leveraging powerful external AI tools while safeguarding the integrity and independence of their own AI development. As AI systems increasingly help build other AIs, distinguishing the origin of capabilities becomes a fundamental challenge for the entire industry.

marsbit1h ago

You Use Claude and Codex Every Day, but Meta Has Restricted Internal Use

marsbit1h ago

Why Do We Need an AI Content Perspective Today?

The article "Why Do We Need an AI Content Perspective Today?" explores the complex and often contentious integration of AI into the cultural and creative industries, particularly film and television. It begins with the cancellation of Amazon's AI-generated animation "Punky Duck," highlighting the ethical debates surrounding AI content. AI's rapid advancement is transforming video production, enabling cost-effective, full-length AI films (e.g., "RAPHAEL," "Dreams of Violets") while sparking industry resistance over issues like "synthetic actors." The core debate has shifted from whether to use AI to how to use it responsibly. The article analyzes why AI's entry into film is uniquely unsettling. It distinguishes between "cultural fast food" (short-form, fast-paced content like micro-dramas) and "cultural main courses" (traditional, long-form film/TV). AI currently excels at the former, matching its fragmented narratives, shallow emotional needs, and free-to-consumer models. However, venturing into the latter challenges the human-centric essence of storytelling—creativity, emotional depth, and the unique value of human labor and experience. While AI can generate massive volumes of content and lower costs, it risks devaluing human creativity, leading to homogenized output, and creating unfair competition through potential intellectual property infringement. Its efficiency also amplifies content safety risks, making preemptive governance crucial. To counter these risks, the article proposes establishing clear boundaries guided by a human-centered AI content perspective. It outlines four principles: 1) Amplify, rather than displace, human creative space; 2) Respect and protect human creative output; 3) Ensure human creative control and responsibility remain paramount; and 4) Guarantee transparency and traceability in AI creation. The conclusion emphasizes that humans must act as the "helmsmen" of technology, steering AI development to enhance, not replace, the core human values at the heart of cultural expression.

marsbit1h ago

Why Do We Need an AI Content Perspective Today?

marsbit1h ago

Planck Retracted? The Father of Quantum Tripped by an Algorithm

The recent discovery that two articles (published in 1940 and 1942) by Max Planck, the Nobel laureate and founder of quantum theory, are marked as "retracted" on Springer's digital platform highlights a curious clash between historical publishing practices and modern automated systems. An investigation suggests these retractions are algorithmic errors, not due to fraud or misconduct. The papers, philosophical reflections on science published in *Die Naturwissenschaften*, were likely flagged by the platform's systems. One article, a republished lecture, may have been mistaken for duplicate publication. Another, sharing a title with a prior article by a different author (a common practice for continuing debates at the time), may have triggered a similar automated check. The digital versions have even been replaced with blank pages, contrary to normal practice of preserving retracted texts. This incident underscores how contemporary digital infrastructure, built around concepts like "self-plagiarism" and strict copyright, can misclassify and obscure legitimate historical scholarly communication. It serves as a warning that digital archives are not neutral mirrors of the past but are filtered by platform rules, potentially distorting the scientific record. As AI systems increasingly rely on such databases, such erroneous metadata could propagate, affecting how future tools interpret and access historical knowledge.

marsbit1h ago

Planck Retracted? The Father of Quantum Tripped by an Algorithm

marsbit1h 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 ETH (ETH) are presented below.

活动图片