图中未知部分是否会重新连接并遵循与以前相同的轨迹？
人类是非常了不起的生物。尽管生物进化的速度非常缓慢，但人类利用科学技术的速度却快得惊人，改变了世界。想象一下我们今天的生活与一千年前相比。尽管我们的外貌和认知能力没有太大变化，但生活水平却存在巨大差距。
然而，无论世界变化多么迅速，人类最终都受限于由有机和无机材料构成的身体和基因。财富和权力的斗争、阶级冲突、战争以及财富和债务的循环在历史上一直存在，并可能继续下去。人类对这些问题的反应和行为方式不太可能随着时间的推移而发生重大变化。
这种观点表明，通过研究人类历史上的行为和对重大事件的反应，我们可以预测未来的模式。虽然我们无法绝对确定地预测未来，但除非人类生物学发生巨大变化或我们的集体思维方式发生根本性转变，例如全世界都皈依佛教达到开悟，否则我们可以利用过去来对未来趋势做出有根据的猜测。
许多出版的书籍分析了人类社会不变的方面以及我们对历史事件的一贯反应。例如，摩根·豪瑟尔的《一如既往》从微观角度对人类思维过程的持久性提供了有见地的解释。另一方面，雷·达里奥的《应对变化中的世界秩序的原则》从宏观角度分析了帝国历史的重复性。这两本书都强烈推荐给有兴趣了解这些持久模式的读者。
在此背景下，本文旨在探讨当前人类面临的一些重大且不可避免的趋势及其对社会的潜在影响，并与历史上的类似情况进行对比。本文特别关注了美元地位的动摇和通用人工智能（AGI）的崛起，并指出它们都因为过于中心化，可能会带来重大风险。因此，我相信，区块链技术本质上促进了去中心化，将在人类社会的未来中发挥至关重要的作用。本文的每一部分都将深入探讨以比特币为首的区块链行业如何最终塑造我们的世界。
1. 绕不开的话题：货币
1.1 储备货币的崩溃是不可避免的
货币是为了促进交易而建立的社会契约。其合法性依赖于国际秩序中的力量平衡和参与者的信任。由于人类的思想和情感系统在长时间内没有发生重大变化，未来的货币体系很可能会遵循历史先例。
当今大多数人已经习惯了美元作为全球储备货币，在日常生活中毫无疑问地使用它。美国在军事、金融、科学和其他领域的主导地位巩固了美元看似永恒的地位。然而，人类往往对未亲身经历的事情过于自信。简要探讨货币的本质和历史会发现，全球储备货币的寿命通常比预期的要短。
自1944年布雷顿森林体系建立以来，美元一直是全球唯一的储备货币，至今不过80年。在评估美元的现状之前，回顾之前的全球储备货币是很有意义的。在美元之前，英镑是世界储备货币，再之前是荷兰盾。
（储备货币的历史重演）
荷兰和英国这两个大国的兴衰，以及它们作为全球储备货币持有者的任期，都遵循着非常相似的模式。它们都是在战胜衰落的大国后开始崛起的。胜利推动了资本主义的发展和工业革命的到来，这些进步增强了国家的竞争力，为它们成为储备货币国家奠定了基础。
然而，历史一再表明，全球储备货币地位带来的财富和繁荣往往为衰落埋下了种子。账户赤字增加和收入不平等扩大削弱了国家竞争力，加速了债务的积累。最终，战争造成的巨额债务和货币贬值迫使这些曾经的强国将储备货币的地位让给新兴大国。
（布雷顿森林的华盛顿山酒店，资料来源：维基百科）
美国目前是世界头号超级大国，也遵循了类似的轨迹。内战后，美国通过第二次工业革命、资本主义的发展及其地缘政治优势增强了竞争力。在第一次世界大战和第二次世界大战期间和之后，美国在财富和繁荣方面超越了衰落的欧洲，达到了新的高度。随着第二次世界大战的胜利成为必然，美国召开了一次会议，以重组战后的金融秩序，采用布雷顿森林体系，将美元确立为金本位制下的储备货币。
然而，以硬通货为基础的储备货币经济面临两难境地。要使用美元作为国际贸易的主要货币，必须有足够的美元供应，这要求储备货币国保持赤字。虽然黄金储备保持不变，但美元发行量的增加不可避免地导致货币贬值，并削弱了国际上对储备货币的信任。这个问题被称为特里芬困境。
与苏联的冷战、越南战争和石油危机加剧了贸易赤字和通货膨胀。当美国无法再满足黄金赎回需求时，理查德·尼克松总统于1971年终止了美元的黄金可兑换性。这导致黄金价格从固定的每盎司35美元急剧上涨到1980年的每盎司850美元，标志着法定货币时代的开始和高通胀时代的开始。
幸运的是，由于保罗·沃尔克实施了前所未有的高利率政策（年利率达到20%）以及石油美元体系的成功建立，美元重新升值。这种复苏为美国在1990年代迎来了一段经济繁荣时期。
（来源：FRED）
然而，在布雷顿森林体系结束后，美元的发行方式发生了根本变化。每当需要资金时，政府就开始发行国债，美联储印钞购买这些债券，导致货币供应量迅速增加。政府债务从1971年的3910亿美元（占GDP的34%）飙升至2023年底的34万亿美元（占GDP的120%）。在2008年和2020年的金融危机期间，政府通过这一机制积累了大量债务，导致美元持续贬值。
如此庞大的政府债务能维持多久？这个问题引发了多种可能的情景。一个可能是出现像保罗·沃尔克这样的通货膨胀斗士，他可能采取严厉措施减少债务，即使以严重经济衰退为代价。或者，AI等颠覆性创新可以促进供应和生产，对经济施加持续的通货紧缩压力，从而延长美元的寿命。
（政治两极分化，资料来源：皮尤研究中心）
然而，如前所述，货币是一种社会契约。因此，当国际社会开始对美国及其货币失去信心时，美元的衰落将开始。作为储备货币不可避免的通货膨胀可能会加剧国内和国际上的收入不平等和政治两极分化等社会问题，进一步削弱对美元的信任。尽管目前还没有明确的迹象表明美元将消亡，但越来越多的问题表明，这种情况越来越有可能。
（中国爱黄金，资料来源：Investing.com）
不仅仅是通货膨胀，地缘政治问题也可能削弱美元的地位。作为对俄罗斯入侵乌克兰的回应，西方国家将俄罗斯排除在SWIFT银行系统之外，阻止其以欧元或美元结算贸易，并冻结了俄罗斯持有的半数美元外汇储备。这些行动会削弱其他国家对美元的信任。例如，自俄乌冲突开始以来，中国一直在稳步抛售美国国债并积累黄金，从而减少对美国的依赖。
历史证明，围绕货币的权力动态保持不变。除非出现前所未有的完美货币政策，否则任何储备货币最终都将失去其地位。虽然没有人能预测确切的时间，但美元总有一天会面临终结。我只能希望这一刻来得越晚越好，越平稳越好。
1.2 比特币作为硬货币
随着美元逐渐失去信誉，黄金等资产自然会受到关注。黄金因其稀缺性和不变的物理特性而一直受到重视。在重大冲突期间，黄金被公认为国际上最可靠的终极资产。因此，各国央行始终保持一定的黄金储备。
（战争期间俄罗斯人在银行排队，资料来源：美联社）
如今，个人可以通过矿业公司股票、黄金期货和黄金ETF等多种方式投资黄金。这些投资方法一般在金融市场发达的国家比较有效。但是，如果您居住在金融市场欠发达的国家，或者直接卷入战争或革命的国家，投资黄金可能会受到很大限制。这些投资途径不涉及黄金的直接所有权，在国际动荡期间会带来交易对手风险。此外，购买和储存实物黄金并非易事。
（来源：Kaiko）
在这种情况下，比特币可以充当类似黄金的优良硬资产。它的供应是有限的，不受任何单一实体的控制，而且特别容易储存和转移，即使在战时这样的危急情况下也是如此。例如，在2022年2月24日俄罗斯入侵乌克兰期间，比特币对乌克兰格里夫纳的交易量和价格激增，溢价高达6%。即使在不那么极端的情况下，国家货币不稳定的国家对比特币的需求也很高。在年通货膨胀率约为70%的土耳其，比特币的交易溢价与黄金类似。这些例子表明，比特币确实可以发挥硬资产的作用。
（来源：BlockScholes, Yahoo）
从上述例子可以看出，比特币在未来作为硬通货的巨大潜力。但这是否意味着，目前受到稳定货币体系保护的发达国家公民，就没有必要将比特币纳入其投资组合呢？即使在危机情况之外，将投资组合的一部分分配给比特币也能在多样化方面带来实质性的好处。如图所示，虽然比特币与黄金、股票和美元等其他资产的相关性会随着时间的推移而波动，但它通常会表现出明显的价格波动。这一独特性使得持有比特币等加密货币成为一种有利的选择。
（来源：K 33 Research）
事实上，美国的许多金融机构最近都在其投资组合中增加了比特币ETF。根据K 33 Research的数据，在2024年第一季度，有937家机构在其13F文件中报告持有比特币。Exchange Traded Funds (ETFs), including notable companies such as JP Morgan, UBS, and Wells Fargo, as well as the Wisconsin Investment Board, which recently acquired a BTC ETF worth approximately $160 million, are increasingly recognizing Bitcoin as a value store.
With the inflationary impact of quantitative easing policies in the COVID-19 era still lingering, the United States has once again increased liquidity in response to the upcoming presidential election. The US Treasury is expanding fiscal expenditure and planning its first bond repurchase in over 20 years starting May 29. Meanwhile, the Federal Reserve is slowing down its pace of quantitative tightening.
As a result, the US dollar will continue to face inflationary pressures and a significant increase in issuance during major economic recessions. Unless the United States can sustain innovation and maintain its leadership position in the military, scientific, and industrial sectors, the value of the US dollar will inevitably decline over time. Conversely, this will naturally increase the attention and value of Bitcoin.
However, in order for Bitcoin to become a hard asset like gold, it faces a crucial challenge: the scale of network security and profitability. The fundamental element of Bitcoin’s value is the security of its network. The more miners there are, the more secure the network becomes, and the more stable the value of Bitcoin.
Bitcoin miners primarily earn income through two methods: block rewards and transaction fees. Block rewards are the Bitcoin miners’ earnings for successfully mining a block, and the quantity is halved every four years. Transaction fees, on the other hand, are the fees paid by users for transactions on the Bitcoin network and are unrelated to block rewards.
In order for miners to continue participating in the Bitcoin network, their mining income must exceed their costs. As block rewards decrease every four years, mining income gradually decreases, and the shortfall must be compensated by increasing transaction fee income. However, unlike networks like Ethereum and Solana, the Bitcoin network has limited applications and low scalability, resulting in decreased transaction volume and lower transaction fee income. Recently, new token standards such as Ordinals and Runes temporarily increased activity on the Bitcoin network, but it remains uncertain whether these standards can significantly increase transaction fee income in the long term.
As of now, mining income generally exceeds mining costs. However, due to future halvings, block rewards will continue to decrease, and miners may exit the network unless 1) the price of Bitcoin significantly increases or 2) increased network activity brings in more transaction fee income. This would reduce the security of the Bitcoin network, weaken its intrinsic value, and potentially trigger a vicious cycle of further miner exits and declining security.
This highlights the key difference between gold and Bitcoin. The intrinsic value of gold is unrelated to profitability, while the intrinsic value of Bitcoin directly depends on it. Therefore, ensuring profitability is a long-term challenge that the Bitcoin network must address. Although the Bitcoin community currently lacks a clear solution, innovations such as Ordinals, Runes, and OP_CAT suggest that transaction fee income may increase in the long run.
2. Different from the Past: AI
2.1 The Impact of AGI on Humanity
Throughout history, technological innovations such as AI have always brought significant changes to society, unlike currencies. The steam engine, electricity, and internet revolutions have changed the global industrial landscape and profoundly influenced human work and lifestyle. While these technological revolutions brought various social problems during the transition period, they ultimately provided humanity with a more prosperous life. The steam engine and electricity freed humans from most physical labor, while digital and internet technologies freed them from simple mental labor.
Since the 1900s, people have been researching AI technology, but there have been few breakthroughs. However, since the publication of the paper “Attention Is All You Need” in 2017, which introduced the Transformer theory, the pace of AI development has significantly accelerated. This breakthrough has made it easier to develop Large Language Models (LLMs) and brought humanity closer to General AI (AGI). Similar to previous industrial revolutions, the development of AGI is expected to significantly increase productivity and have a major social impact. However, due to several reasons, I believe its impact will be different.
Firstly, AGI will free humans from almost all forms of labor. Previous industrial revolutions freed humans from physical labor and simple mental labor, allowing more people to engage in more complex tasks. However, AGI is capable of handling advanced mental labor, including creative activities such as art and music. Coupled with advanced robotics technology, this will significantly reduce the space for human contributions in the field of productivity.
Of course, this does not mean that all jobs will disappear. Even in the 21st century, there are still a portion of the population engaged in agriculture and fishing, although the proportion is much lower than in the past. While most types of work will still be preserved with the emergence of AGI, the number of people required to perform these jobs will drastically decrease. For example, one person in the future may be able to accomplish the work of ten people today, leading to a significant increase in unemployment. It is worth noting that leaders in the AI field, such as Elon Musk and Sam Altman, believe that AI and robots will handle global productivity, resulting in widespread unemployment among humans.
Some may argue that it is possible to maximize efficiency while maintaining the existing level of employment, but this is a misconception. To achieve this, demand must increase in proportion to the significant increase in productivity provided by AGI. However, this is almost impossible for most fields. New job opportunities must arise in new areas untouched by AGI, but as mentioned earlier, AGI’s capabilities extend beyond physical and mental tasks, making this possibility highly unlikely.
Secondly, AI is inherently a highly centralized technology. Even before achieving AGI, the AI industry has been highly concentrated among large tech companies. This is due to the rapid development of AI technology. Since the introduction of the Transformer theory, the scale of language models has increased by 10^4 between 2018 and 2022. Therefore, there is a significant technological gap between the core industries of AI.
Semiconductor Design: In contrast to the consumer GPU market, NVIDIA almost monopolizes the data center GPU market used for AI model training and inference. This dominance is partly attributed to its CUDA toolkit, which is widely used by AI developers. The demand for NVIDIA H100 GPUs has surged, leading to extended delivery cycles. With this advantage, NVIDIA enjoys a profit margin of up to 78%, and the upcoming release of the Blackwell GPU by the end of 2024 is expected to further solidify its dominant position. Although AMD Xilinx and Intel Altera are expanding their FPGA business, and tech giants like Microsoft, Google, and Meta are developing their own AI semiconductors (ASICs), these solutions still lag behind GPUs in terms of market maturity and readiness.
Semiconductor Manufacturing: The foundry industry responsible for manufacturing designed semiconductors also shows significant imbalances. NVIDIA’s A100 production requires a 7nm process, while H100 requires a 4nm process. These sub-10nm processes are almost monopolized by TSMC, Samsung, and Intel, with TSMC mainly producing A100 and H100. TSMC has committed to manufacturing NVIDIA’s H100 for at least the next three years, and given various factors, the leading position of the foundry industry and the gap between other companies are expected to continue to widen.
Computing Power: AI companies require a large amount of computing power for the training and inference processes. This requires a significant number of AI semiconductors, such as H100, large data centers, and substantial electricity. According to Huawei, AI data centers are expected to account for 13% of global electricity consumption and 6% of carbon footprint by 2030. The costs are also considerable. As Huang Renxun pointed out in his keynote speech at NVIDIA GTC 2024, training the GPT-MoE-1.8T (GPT-4) model requires 8,000 H100 GPUs and 90 days. Therefore, due to the need to protect AI semiconductors and bear significant electricity costs, centralization in this industry is inevitable. Cloud service providers such as AWS and Azure also offer computing power based on H100 and are inevitably centralized.
AI Models: While some AI models, such as Meta’s Llama and Google’s BERT, are open source, many other models are closed source. Closed-source models like OpenAI’s GPT and Anthropic’s Claude generally offer system development and better customer support compared to open-source models, but their centralization brings disadvantages in terms of cost and transparency.
Data: Training AI models like LLMs requires massive datasets. Legal arrangements, such as Google paying $60 million annually to use Reddit’s data, exist, but there have also been numerous lawsuits regarding unauthorized data used for AI model training, increasing people’s interest in data sovereignty.
In conclusion, centralization is inevitable in the AI industry due to the importance of achieving economies of scale. As the AI industry becomes more centralized, micro-level issues such as excessive profit-seeking by enterprises, unethical data usage, single points of failure such as server downtime, and opacity of AI models may arise. At the macro level, as the boundary between humans and AI becomes blurred, we may face social chaos and a significant loss of jobs for many people. I believe that blockchain technology, which inherently pursues decentralization, can serve as a counterbalance to the centralization-related challenges in AI. Let us explore how blockchain can be applied to the AI industry.The demand for computing power and hardware in training and inference AI models is significant. Large tech companies, such as NVIDIA H 100, continuously purchase GPUs for model training, exacerbating the global hardware supply shortage. While services like AWS and Azure provide data centers for cloud-based AI model training and inference, they operate in a monopolistic manner, resulting in high profits for users. To address these challenges, new services that offer decentralized computing power through blockchain technology have emerged.
For example, platforms like Akash and io.net allow users to contribute their hardware’s computing power in exchange for incentives. There are also protocols that specialize in specific services, such as Gensyn, which is dedicated to training AI models. While general decentralized computing services can reduce costs by utilizing idle hardware, executing stateful computations like AI model training in a decentralized manner poses challenges. Gensyn addresses this issue by leveraging concepts like probabilistic learning proofs and graph-based precise point protocols. Gensyn focuses on training AI models, while Bittensor specializes in AI model inference. Users can submit tasks, and Bittensor’s decentralized nodes compete to provide the best results.
zkML, which combines zero-knowledge (zk) cryptography and machine learning (ML), has the potential to enhance the privacy and transparency of AI models. Currently, many AI models operate in a closed-source manner, leaving users uncertain about the correct weights and execution of the models. By applying encryption techniques like ZK-SNARK (Zero-Knowledge Succinct Non-Interactive Argument of Knowledge) to ML models, it is possible to prove that AI models correctly execute inference without revealing their weights, ensuring privacy and computational integrity.
ZK-SNARK is a powerful encryption technology that can prove the validity of arbitrary computations without revealing input data. To illustrate this, consider the real-world example of proving someone’s age online. Typically, this requires complex KYC verification, involving the disclosure of personal information like name and ID. With ZK technology, this process can be simplified and made more private. Once a user has verified their age through an official entity, they can generate and submit a ZK proof when required to prove they are over 18. This proof does not contain any personal information but still assures verifiers of the user’s age, making the identity verification process more secure and straightforward.
Applying the same concept to ML models, consumers using closed-source ML models cannot determine if the models faithfully execute computations for given inputs. By integrating ZK-SNARK, ML providers can guarantee to consumers that computations are performed correctly without revealing inputs or weights. ZKP (Zero-Knowledge Proof) for ML inference can be generated and verified through smart contracts on a neutral blockchain protocol, ensuring trust in the results.
Despite the appealing concept of zkML, there are significant challenges. Verifying specific computations with ZKP is relatively simple, but generating these proofs requires more computational power than the actual computations. According to Modulus Labs, generating a ZKP for an 18M-parameter ML model based on Plonky 2 takes approximately one minute. Considering that GPT-3 has 175B parameters and GPT-4 has 1.76T parameters, substantial progress is needed before zkML can be widely adopted.
As the AI industry continues to develop, the importance of data grows exponentially. However, this surge in data has led to increased violations of data sovereignty. Through blockchain technology, individuals can manage their identity-related information through self-sovereign identity, providing data only when necessary through digital signatures. Additionally, blockchain enables transparent data provisioning or sales through incentive systems or markets accessible to everyone. Reddit exemplifies a data sovereignty approach similar to blockchain, offering long-term users the opportunity to participate in its IPO while signing contracts to provide data to Google. This demonstrates a new path for data sovereignty.
While slightly different from data sovereignty, blockchain also has the potential to address issues in the data labeling industry. Data labeling is crucial for improving the accuracy and ethics of AI models. Currently, this task often falls on low-wage workers, becoming a new social problem. For example, China’s AI industry exploits students from vocational schools, and OpenAI outsources this work to low-wage workers in Kenya. Integrating blockchain into data labeling can democratize participation and ensure fair compensation.
Decentralized computing, zkML, data sovereignty, and data labeling solutions address some challenges in the AI industry. However, identity proof and universal basic income (UBI) are necessary to maintain human sovereignty in a society fundamentally transformed by AGI. Let’s explore how blockchain supports human sovereignty in such profound social changes.
With advancements in AI models, AI-generated content in various forms (text, images, videos) becomes increasingly common. Differentiating between human-made and AI-generated outputs becomes challenging. Digital acceleration is inevitable, and with the proliferation of AI-generated content, related social issues undoubtedly increase.
These issues are not mere speculation; they are already happening. Fraudulent activities using deepfakes, which imitate individuals’ faces and voices, have become widespread, resulting in significant economic losses. The existence of deepfakes has led to intense debates over the authenticity of videos online.
A recent event involving Caitlyn Jenner vividly illustrates this. She announced the launch of a memecoin on the Solana network through the platform X. Given the unusual nature of this announcement, many suspected her account had been hacked. Although Caitlyn herself posted a video, there is still considerable controversy over whether it is a deepfake.
It wasn’t until Caitlyn’s manager also released a video that the controversy subsided slightly.
As we enter the AI era, one of the most critical challenges will be proving one’s humanity in the digital domain. This concept, known as “identity proof,” aims to prevent witch attacks and false information in the digital world. Currently, most applications rely on government-issued identity systems like passports or credit cards to verify identity. However, these methods come with privacy risks and the possibility of single points of failure. Therefore, a genuine digital identity system is essential. Blockchain technology provides a solution, allowing individuals to prove their humanity and the authenticity of the content they create, potentially mitigating issues like deepfakes.
The most common method of digital identity verification is biometric systems that verify specific body parts. Sam Altman, the CEO of OpenAI, is advancing a project called Worldcoin, which combines blockchain technology with iris scanning. Users install an application on their mobile devices and receive private keys (accounts) on the blockchain. By using an iris scanning device called Orb, users can verify their human identity in the digital world. Orb ensures that users are indeed human and that the iris has not been registered before, granting digital identity securely.
Orb only transmits the hash value of iris data to the server and subsequently destroys the actual iris data. Users can later prove their human identity without revealing their account address through ZK-SNARK, solving privacy concerns. However, potential issues like hardware backdoors still need to be addressed. The importance of human identity proof extends beyond content authenticity; it also plays a crucial role in the concept of universal basic income (UBI), which we will explore in the next section.
As previously mentioned, the emergence of AGI is expected to bring an unprecedented leap in human productivity. However, this revolutionary progress will inevitably lead to a significant loss of jobs. To maintain social stability, the concept and necessity of universal basic income (UBI) are gaining increasing attention. The concept of UBI predates AGI and can be traced back to Thomas More’s “Utopia” in the 16th century. UBI entails providing regular, unconditional financial support to all members of society. An existing example of UBI can be found in Alaska, where the Alaska Permanent Fund Dividend offers a form of UBI, demonstrating positive results in poverty, employment, and health.
However, the focus here is not merely on UBI that improves the quality of life. It is about providing UBI sufficient to support individuals who become unemployed due to AGI, ensuring they can live fulfilling lives without employment. Elon Musk refers to this as “universal high income.” Similarly, Sam Altman shows a strong interest in UBI and conducts research through OpenResearch. He presents innovative ideas such as providing UBI in the form of assets and means of production, such as equity or computing power, rather than just cash.
Worldcoin, discussed in the “identity proof” section by Sam Altman, is also closely related to UBI. A crucial aspect of UBI distribution is ensuring that only genuine individuals receive it and preventing multiple claims by the same person. Therefore, preventing Sybil attacks is vital for implementing UBI. Worldcoin achieves this through iris recognition. Currently, users undergoing iris recognition through the Worldcoin application receive regular WLD tokens, which serve as a form of UBI. While I resonate with the vision of Worldcoin, there are still some concerns about the distribution of WLD tokens.
Even beyond Sam Altman’s Worldcoin, blockchain technology is essential for establishing a comprehensive UBI system. Blockchain not only improves transparency and efficiency for recipients through identity proof but also enhances transparency and efficiency in the distribution process, ensuring more effective and transparent UBI delivery.
In any case, humans will need blockchain technology. Despite experiencing unprecedented crises like the collapse of Terra and FTX, the blockchain market has quickly recovered its scale. However, looking back at the previous and current market booms, the industry’s vision has undergone a noticeable transformation. In 2021, many protocols were driven by a decentralized grand vision, capturing the imagination and excitement of many. Now, despite similar market sizes, there seems to be widespread uncertainty within the industry and community regarding the direction of blockchain development. This is not due to any failures on our part or inherent flaws in blockchain technology itself; instead, it is simply that the current era has not yet presented an urgent need for blockchain technology.
While observing the application of blockchain in niche markets is interesting, the industry must aim for higher goals. As the long history of humanity demonstrates, we will continue to experience cyclical monetary systems and revolutionary technological innovations. In these grand trends, blockchain will be the key technology for maintaining human sovereignty.
