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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

Behind the collapse of the "AI Stock God" Leopold Fund: abandoning the sale of Anthropic equity and turning to discounted sales of public stocks

According to Wall St Engine, "AI stock god" Leopold Aschenbrenner's Situational Awareness fund faced liquidity pressure during the market crash in July, with behind-the-scenes details revealed.The report states that after the market rapidly cooled in mid-July, the decline in stocks held by Situational Awareness triggered margin monitoring by banks such as Goldman Sachs and Morgan Stanley, leading to margin calls.Insiders said that other hedge funds began shorting related stocks after learning about its positions, creating a cycle of "price drop → margin call → forced selling → further price decline."In late July, while Leopold was hosting a wedding in Carmel, he continued negotiations with his team to maintain fund operations. On the evening of July 29, he reached a preliminary agreement with a consortium led by Greenoaks and Sequoia Capital to sell approximately $3.5 billion in Anthropic equity.However, in the early hours of July 30, before the U.S. stock market opened, Leopold changed his decision, opting to retain the private equity portfolio and instead sell publicly traded stocks. Subsequently, Citadel and Millennium entered negotiations with the fund team, and Citadel ultimately acquired most of the fund's public stock investment portfolio at a discount of more than 10% below market value before Thursday's opening.This transaction helped Situational Awareness meet margin requirements and avoid formal default. After the deal was completed, related AI and semiconductor stocks rebounded on Thursday, benefiting Citadel.As of around July 31, Situational Awareness disclosed to investors that the fund had a net loss of about 67% in July, but was still up about 80% for the year. Leopold stated that he "takes full responsibility" for the incident, and the fund has removed bank leverage, planning to continue operations and invest in the public market while adjusting its portfolio management and risk control systems.

Polymarket will upgrade the settlement rules for the cryptocurrency rise and fall market: abandoning the single price snapshot and switching to a time-weighted average price

According to official news, the prediction market Polymarket announced a significant adjustment to its settlement mechanism for cryptocurrency price fluctuation markets starting from August 7, to protect market integrity. From midnight UTC on that day, the affected markets will no longer settle based on a single price snapshot at a specific time but will instead use a time-weighted average price.Markets of different durations correspond to different TWAP windows: all cryptocurrency 5-minute markets will use a 30-second TWAP, 15-minute markets will use a 60-second TWAP, and 4-hour markets will also use a 60-second TWAP. The previous single snapshot settlement method was prone to price manipulation during periods of low liquidity, and this change is a proactive reinforcement of the market integrity system by Polymarket after facing regulatory scrutiny.To support this transition, Polymarket will inject $1 million in liquidity rewards into all affected markets throughout August. On the technical side, Chainlink TWAP testnet data streams are now available, and mainnet data streams along with Polymarket real-time data stream services will go live on August 4, at which point developers can access TWAP prices directly through Chainlink Data Streams or Polymarket's public WebSocket.

Ondo abandons the independent blockchain route and launches a new execution network: creating an architecture with "exchange-level performance on-chain."

Ondo Finance announced the launch of the new Ondo Network, positioned as a high-performance execution layer, aimed at combining the trading speed of centralized exchanges (CEX) with the non-custodial and secure settlement capabilities of blockchain. Ondo CEO Ian De Bode stated that the Ondo Network is an "evolutionary version" of the previous Ondo Chain plan, and the company will not operate two networks simultaneously, but will adjust its original plan of building a complete blockchain to focus on the execution layer architecture.According to reports, Ondo initially planned to fully bring real-world assets on-chain through Ondo Chain, but after developing the Ondo Perps perpetual contract trading platform and communicating with users, it was found that the current market's core bottleneck is not asset settlement, but trading execution efficiency. The Ondo Network adopts a separated architecture for execution, validation, and settlement, using secure hardware to isolate the execution environment, which enhances trading speed while maintaining user asset self-custody, verifiable transactions, and permissionless blockchain characteristics.Currently, Ondo Perps has become the first application built on this network, supporting 24-hour trading of stock and commodity perpetual contracts, and allowing the use of tokenized real assets as collateral. Ondo stated that in the future, the network will also support applications requiring high performance, privacy protection, and verifiable execution, such as spot trading, lending, and structured products. In addition, the launch of the Ondo Network will not change the positioning of the ONDO token. The CEO stated that ONDO will still serve as the governance and incentive token for the Ondo RWA ecosystem and market infrastructure, and as the network gradually decentralizes, ONDO will be used to coordinate the incentive mechanisms for validation nodes, observers, and ecosystem participants.
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