Джереми Эллайр: «Стейблкоины должны стать массовым экспортным продуктом США»

cryptonews.ruPubblicato 2024-07-19Pubblicato ultima volta 2024-12-19

Генеральный директор и соучредитель Circle Джереми Эллайр заявил в интервью телеканалу CNBC, что стейблкоины, привязанные к доллару, должны стать массовым экспортным продуктом США.

Джереми Эллайр (Jeremy Allaire) выразил мнение, что власти Соединенных Штатов должны конструктивно регулировать и максимально поддерживать рост и инновации цифровых активов. Особенно тех, которые способствуют сохранению стоимости доллара США и поддержанию его доминирования на международной арене.

Глава Circle добавил, что в отличие от биткоина, который благодаря фиксированному предложению может позиционироваться как резервный актив, стейблкоины могут стать настоящими цифровыми деньгами.

По его словам, если в рамках федерального законодательства будет принято решение, которое классифицировало бы стейблкоины, обеспеченные долларом, как законные электронные деньги в финансовой системе США, то данная форма расчетов получила бы массовое принятие как на территории страны, так и за рубежом.

«Каждая компания, финансовое учреждение и публичная корпорация по всему миру могли бы рассматривать стейблкоины как цифровые деньги, что значительно расширило бы их сферу применения. Стейблкоины могли бы стать массовым экспортным продуктом Соединенных Штатов», — заявил Эллайр.

Ранее гендиректор Circle выразил мнение, что у частных стабильных монет гораздо больше преимуществ для международного распространения доллара США в сравнении с государственной цифровой валютой центробанка.

Letture associate

Founder of Baixing.com: The Notion That Large Language Models Will Devour Everything, I Believe Half of It

Founder of Baixing.com: I Only Half-Believe the Saying “Large Language Models Will Devour Everything” Author: Wang Jianshuo, Founder of Baixing.com Many proclaim that large models are everything, but the author is skeptical. He argues that such sweeping claims often stem from a limited understanding of the future. Drawing parallels to past technologies like electricity and the internet—which were predicted to “devour everything” but didn’t—he suggests that large language models (LLMs) are better seen as a foundational base. Like electricity, this base is essential for modern development, but its real value emerges only when applied to specific scenarios through various “machines” or “tools” (e.g., Claude Code for programming, Claude Design for design). The author acknowledges that LLMs may indeed replace many existing software systems built on rigid rules, workflows, and forms (e.g., CRMs, SaaS tools), as these are precisely what LLMs excel at processing. However, he emphasizes that beyond software, elements like customer data, execution capabilities (e.g., booking a flight), trust, and physical-world interactions will not be “devoured.” Instead, he foresees that after streamlining existing software, LLMs will open up a larger space for innovative, next-generation applications. These new tools will likely feature fluid interfaces and rely less on fixed rules, unleashing greater creativity. The author cautions against short-sightedness, recalling how in 2004 many believed internet giants like Sina, Sohu, and NetEase would monopolize the market—only to be proven wrong by subsequent disruptions. In conclusion, while LLMs are a crucial foundation and a current focal point, the true mainstream of this wave lies in the diverse applications built atop them to solve concrete problems. The phrase “devour everything” is imprecise; the real opportunity lies in identifying and leveraging the areas where LLMs do bring transformative change.

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Founder of Baixing.com: The Notion That Large Language Models Will Devour Everything, I Believe Half of It

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Founder of Baixing.com: I Only Half Believe in the Notion that Large Language Models Devour Everything

The founder of Baixing Wang states that while large language models (LLMs) are an extremely important foundational technology—akin to electricity or the internet—he only "half believes" the notion that they will "consume everything." He argues that LLMs provide a base layer of intelligence, but real-world value and transformation come from integrating this intelligence into specific applications and devices designed for particular scenarios—like how electricity powers various appliances from washing machines to TVs. He agrees LLMs will likely consume or replace a significant portion of existing rule-based, workflow-driven software (e.g., many SaaS systems, CRMs), as these are precisely what LLMs excel at handling. However, numerous other elements—such as customer data, execution capabilities (e.g., booking a flight), trust, and physical-world interactions—will not be consumed. Wang emphasizes that after LLMs absorb certain software layers, they will open up a much larger space for innovation: new types of "streaming" software with less rigid interfaces, where fixed rules are managed by AI. This next wave of applications built on top of the stable LLM foundation is where the true mainstream opportunity lies. He cautions against the short-sightedness of declaring any technology as all-consuming, drawing parallels to past premature predictions about internet giants monopolizing the web. The key is to find opportunities within the areas LLMs do transform.

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Founder of Baixing.com: I Only Half Believe in the Notion that Large Language Models Devour Everything

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