漳龙集团发行全国首单数字人民币“一带一路”公司债券

币界网Опубліковано о 2024-08-21Востаннє оновлено о 2024-08-21

币界网报道:

央广网北京8月21日消息(记者 孙汝祥)近日,福建漳龙集团有限公司在上海证券交易所成功发行2024年面向专业机构投资者非公开“一带一路”公司债券(第一期)(债券简称“24漳龙05”),本期债券发行规模10亿元,期限为10年期,主体和债项评级均为AAA,由中银证券担任独家主承销商,票面利率为2.62%。本期债券为全国首单数字人民币“一带一路”公司债券,同时也是福建省首单十年期私募债券。

日前,党的二十届三中全会明确提出“加快培育外贸发展新动能”与“高质量共建一带一路”的指导方针,本期债券募集资金主要用于支持与“一带一路”沿线国家和地区的贸易业务。此次长期限低成本债券的成功发行,不仅充分体现了广大机构投资者对漳龙集团产业布局的十足信心,而且进一步为企业多元化战略部署长期赋能,为推进高水平对外开放提供了新的强劲动能。

值得一提的是,本期债券以数字人民币形式发行,由中国银行、兴业银行担任数字人民币运营机构,是福建省首单数字人民币公司债。数字人民币具有安全性高、支付即结算、无手续费等优势,有效助力数币应用场景在债券领域的加速拓展,谱写数字金融新篇章。

漳龙集团始终积极响应福建省和漳州市政府的号召,持续推动形成更加开放、包容、共赢的经贸合作新格局,并深入贯彻中菲“两国双园”合作倡议,为高质量共建“一带一路”贡献出不可或缺的漳龙智慧和力量。(央广资本眼)

更多精彩资讯请在应用市场下载“央广网”客户端。欢迎提供新闻线索,24小时报料热线400-800-0088;消费者也可通过央广网“啄木鸟消费者投诉平台”线上投诉。版权声明:本文章版权归属央广网所有,未经授权不得转载。转载请联系:[email protected],不尊重原创的行为我们将追究责任。

Пов'язані матеріали

Gensyn AI: Don't Let AI Repeat the Mistakes of the Internet

In recent months, the rapid growth of the AI industry has attracted significant talent from the crypto sector. A persistent question among researchers intersecting both fields is whether blockchain can become a foundational part of AI infrastructure. While many previous AI and Crypto projects focused on application layers (like AI Agents, on-chain reasoning, data markets, and compute rentals), few achieved viable commercial models. Gensyn differentiates itself by targeting the most critical and expensive layer of AI: model training. Gensyn aims to organize globally distributed GPU resources into an open AI training network. Developers can submit training tasks, nodes provide computational power, and the network verifies results while distributing incentives. The core issue addressed is not decentralization for its own sake, but the increasing centralization of compute power among tech giants. In the era of large models, access to GPUs (like the H100) has become a decisive bottleneck, dictating the pace of AI development. Major AI companies are heavily dependent on large cloud providers for compute resources. Gensyn's approach is significant for several reasons: 1) It operates at the core infrastructure layer (model training), the most resource-intensive and technically demanding part of the AI value chain. 2) It proposes a more open, collaborative model for compute, potentially increasing resource utilization by dynamically pooling idle GPUs, similar to early cloud computing logic. 3) Its technical moat lies in solving complex challenges like verifying training results, ensuring node honesty, and maintaining reliability in a distributed environment—making it more of a deep-tech infrastructure company. 4) It targets a validated, high-growth market with genuine demand, rather than pursuing blockchain integration without purpose. Ultimately, the boundaries between Crypto and AI are blurring. AI requires global resource coordination, incentive mechanisms, and collaborative systems—areas where crypto-native solutions excel. Gensyn represents a step toward making advanced training capabilities more accessible and collaborative, moving beyond a niche controlled by a few giants. If successful, it could evolve into a fundamental piece of AI infrastructure, where the most enduring value in the AI era is often created.

marsbit3 год тому

Gensyn AI: Don't Let AI Repeat the Mistakes of the Internet

marsbit3 год тому

Why is China's AI Developing So Fast? The Answer Lies Inside the Labs

A US researcher's visit to China's top AI labs reveals distinct cultural and organizational factors driving China's rapid AI development. While talent, data, and compute are similar to the West, Chinese labs excel through a pragmatic, execution-focused culture: less emphasis on individual stardom and conceptual debate, and more on teamwork, engineering optimization, and mastering the full tech stack. A key advantage is the integration of young students and researchers who approach model-building with fresh perspectives and low ego, prioritizing collective progress over personal credit. This contrasts with the US culture of self-promotion and "star scientist" narratives. Chinese labs also exhibit a strong "build, don't buy" mentality, preferring to develop core capabilities—like data pipelines and environments—in-house rather than relying on external services. The ecosystem feels more collaborative than tribal, with mutual respect among labs. While government support exists, its scale is unclear, and technical decisions appear driven by labs, not state mandates. Chinese companies across sectors, from platforms to consumer tech, are building their own foundational models to control their tech destiny, reflecting a broader cultural drive for technological sovereignty. Demand for AI is emerging, with spending patterns potentially mirroring cloud infrastructure more than traditional SaaS. Despite challenges like a less mature data industry and GPU shortages, Chinese labs are propelled by vast talent, rapid iteration, and deep integration with the open-source community. The competition is evolving beyond a pure model race into a contest of organizational execution, developer ecosystems, and industrial pragmatism.

marsbit4 год тому

Why is China's AI Developing So Fast? The Answer Lies Inside the Labs

marsbit4 год тому

3 Years, 5 Times: The Rebirth of a Century-Old Glass Factory

Corning, a 175-year-old glass company, is experiencing a dramatic revival as a key player in AI infrastructure, driven by surging demand for high-performance optical fiber in data centers. AI data centers require vastly more fiber than traditional ones—5 to 10 times as much per rack—to handle high-speed data transmission between GPUs. This structural demand shift, coupled with supply constraints from the lengthy expansion cycle for fiber preforms, has created a significant supply-demand gap. Nvidia has invested in Corning, along with Lumentum and Coherent, in a $4.5 billion total commitment to secure the optical supply chain for AI. Corning's competitive edge lies in its expertise in producing ultra-low-loss, high-density, and bend-resistant specialty fiber, which is critical for 800G+ and future 1.6T data rates. Its deep involvement in co-packaged optics (CPO) with partners like Nvidia further solidifies its position. While not the largest fiber manufacturer globally, Corning's revenue from enterprise/data center clients now exceeds 40% of its optical communications sales, and it has secured multi-year supply agreements with major hyperscalers including Meta and Nvidia. Financially, Corning's optical communications revenue has surged, doubling from $1.3 billion in 2023 to over $3 billion in 2025. Its stock price has risen nearly 6-fold since late 2023. Key future catalysts include the rollout of Nvidia's CPO products and the scale of undisclosed customer agreements. However, risks include high current valuations and potential disruption from next-generation technologies like hollow-core fiber. The company's long-term bet on light over electricity, maintained even through the telecom bubble crash, is now being validated by the AI boom.

marsbit5 год тому

3 Years, 5 Times: The Rebirth of a Century-Old Glass Factory

marsbit5 год тому

Торгівля

Спот
Ф'ючерси
活动图片