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ban

BAN is the token symbol for Banano, which is a lightweight cryptocurrency based on DAG (Directed Acyclic Graph) technology, designed to provide a fast, fee-free transaction experience. Banano addresses the scalability and transaction fee issues of traditional blockchains through its unique block structure and consensus mechanism. As an experimental and community-driven cryptocurrency, Banano also has applications in education and entertainment, often used for introductory learning about cryptocurrencies and community activities.
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hot_img Circle Q2 revenue reached 701 million USD, a year-on-year increase of 7%, with USDC circulation reaching 73.3 billion USD, and obtained a license from the Federal Trust Bank

Circle Internet Group (NYSE: CRCL) announced its Q2 2026 financial report, with total revenue and reserve income of $701 million, a year-on-year increase of 7%; adjusted EBITDA of $143 million, a year-on-year increase of 8%; and net profit of $48 million, a year-on-year increase of $530 million (mainly affected by last year's IPO equity incentives). The circulation of USDC reached $73.3 billion, a year-on-year increase of 19%, with on-chain transaction volume of $14.8 trillion for the quarter, a year-on-year increase of 151%.In terms of business, Circle received approval from the Office of the Comptroller of the Currency (OCC) to establish Circle National Trust, a federal trust bank, becoming one of the first stablecoin issuers to hold a federal banking license. The Arc public blockchain will launch its mainnet on September 16, with more than ten institutions including BlackRock, DTCC, Visa, Mastercard, and Standard Chartered serving as founding third-party verification nodes. BlackRock plans to deploy the BUIDL fund on Arc, while DTCC will promote the tokenization of DTC custodial assets. The Circle Payment Network (CPN) achieved an annualized transaction volume of $14.7 billion in the past 30 days, a quarterly increase of 76%, with 175 institutions onboarded, a quarterly increase of 29%. The Agent Stack now offers over 900 paid services.

hot_img Counterpoint: If the United States bans imports of Chinese optical modules, it will backfire on domestic cloud vendors rather than just Chinese suppliers

According to Counterpoint Research analysis, if the proposed import ban on Chinese optical modules by the Federal Communications Commission (FCC) in the United States is implemented, it will primarily impact American cloud providers rather than Chinese suppliers. InnoLight leads the global data center optical module revenue with approximately 27% market share, while Coherent ranks second with about 17%. Chinese manufacturers collectively account for about two-thirds of the global unit supply and approximately 60% of the optical communication module revenue.The analysis points out that Western suppliers like Coherent and Lumentum lack sufficient cleanroom capacity, automated packaging infrastructure, and yield scale in the short term, making it impossible to fill the capacity gap left by Chinese manufacturers within 12-24 months. This could lead to delays in AI cluster deployments by several quarters and increase material costs for cloud providers. At the same time, Chinese module manufacturers rely on high-end 800G/1.6T module revenue from North American hyperscale customers for over 90%, but have achieved partial capacity relocation by establishing factories in Thailand.Counterpoint emphasizes that the optical module supply chain is a highly interdependent system. Chinese manufacturers heavily procure DSP chips from Broadcom and Marvell, as well as lasers and optical chips from Lumentum, Coherent, and Mitsubishi Electric. A forced separation would disrupt the entire ecosystem.

Marvell launches AI "memory decoupling" architecture to address the bandwidth bottleneck of Agentic AI inference

According to official news, Marvell Technology announced the launch of a new generation of memory solution portfolio for AI infrastructure, covering server-level AI storage, rack-level CXL memory expansion and pooling, as well as multi-rack optical interconnect shared memory, aimed at addressing the growing memory capacity and bandwidth bottlenecks in Agentic AI inference processes.Marvell stated that as AI model sizes increase, context windows extend, and KV Cache demand grows, traditional tightly coupled architectures of computing and memory are limiting AI inference efficiency. Through memory disaggregation, memory resources can be made more independent of computing resource expansion, improving GPU utilization and reducing data movement latency. The products released include:Bravera SC6 PCIe 6.0 SSD controller: Designed for AI inference storage scenarios, it helps cloud service providers migrate more KV Cache to high-performance SSDs, enhancing infrastructure efficiency. This product features an architecture compatible with multi-vendor NAND and is expected to begin sampling in the fourth quarter of 2026.Marvell Structera X memory expansion solution: Based on CXL technology, it supports rack-level memory expansion and resource pooling, helping data centers share and allocate memory resources more flexibly, reducing AI infrastructure costs.Marvell Photonic Fabric optical interconnect memory solution: Constructs a shared memory architecture across multiple racks using optical interconnect technology, supporting up to 32TB warm KV Cache offloading and helping AI inference clusters enhance throughput capacity.Marvell stated that the Photonic Fabric solution can achieve a 2 to 3 times increase in Token throughput under existing data center space and power consumption constraints, supporting larger scale models and longer context AI applications.Marvell executive Will Chu stated that AI infrastructure is transitioning from a single server architecture to a system where computing, memory, and connectivity operate in synergy, and in the future, memory needs to expand more independently to enhance resource utilization and Token efficiency.As the demand for AI Agents and large model inference continues to grow, memory capacity, bandwidth, and data transfer efficiency are becoming new focal points of competition in AI infrastructure, following computing power.
2026-08-04
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