architect

NVIDIA (NVDA.O) and Meta are considering collaboration on the OpenShell reference architecture and NVIDIA Sentry.

JUST announces the official release of the new white paper. As an important ecological document following the brand upgrade, the new white paper systematically outlines the JUST ecological architecture, the positioning and collaborative relationships of the three core product lines, and provides detailed explanations of the updated JST token economics, covering key content such as governance mechanisms and buyback and burn arrangements.The new white paper helps users, developers, and the community to gain a more comprehensive understanding of the upgraded ecological layout, token mechanisms, and long-term development direction, further enhancing ecological transparency and providing a clear reference for subsequent ecological participation and development integration.

NVIDIA (NVDA.O) launched the OpenShell reference architecture, aimed at ensuring the secure operation of artificial intelligence agents.

On October 13, chip company Qualcomm announced in San Diego that a jury found Arm in violation of the long-standing architecture license agreement (ALA) with Qualcomm, failing to fulfill related commitments and deliberately disrupting Qualcomm's business.Qualcomm stated that, combined with the previous court victory, this outcome further indicates Arm's intention to harm Qualcomm and its ecosystem. Qualcomm called this result a victory for innovation and competition and will continue to develop and deliver semiconductor products, including the Oryon CPU.

Polymarket has launched the next-generation prediction market smart contract system, Polymarket Protocol V2, which reconstructs the underlying architecture of the existing protocol. The current protocol is based on the Gnosis Conditional Tokens Framework from 2019, requiring additional adapters, trading contracts, and authorization processes for each new market type; V2 unifies this by using a single ERC1155 position token contract, pUSD collateral assets, trading platform contracts, and routers.V2 adopts a modular architecture, initially supporting binary, atomic negative risk, incremental negative risk, and composite markets, and connects to UMA, Chainlink, and other future oracles through a new OracleAggregator. The protocol natively supports cross-chain positions, collateral assets, and settlement results, reserving a foundation for future multi-chain deployments; all contracts can be upgraded under a secure governance process.V2 has been audited by Cantina, Certora, Quantstamp, SigmaPrime, Zellic, and Pashov, with formal verification completed by Certora, offering a maximum bounty of $5 million for critical vulnerabilities. Polymarket will operate a limited number of grayscale markets in the production environment from October 5 to 30, with plans to switch new markets to V2 starting November 2, along with the launch of Data API V2 built on Rust and an internal on-chain indexer.

Vitalik.eth posted on Farcaster revealing that he is conducting a personal experiment to generate personalized diet and exercise recommendations using personal health and travel data by combining local models with remote cutting-edge models while protecting privacy.The system employs a three-layer privacy protection architecture:Identity Layer: A local model (Qwen 3.8B) replaces the user to construct query requests, avoiding the exposure of writing style that could reveal identity.Payment Layer: Uses zkAPI to hide payment information.Network Layer: Hides IP addresses through Tor.The system is currently operational, but Vitalik pointed out three major shortcomings: Tor is inefficient and has high latency in unlinking requests; the local model runs at only 20-30 TPS, and a smooth experience requires over 100 TPS; the stricter the data protection, the more limited the assistance that the remote model can provide. The relevant code has been submitted to the Ethereum zkAPI repository.

Vitalik posted on the X platform, stating that he attempted to briefly explain the true meaning of the plans for Ethereum that forked after Hegota. Ethereum is no longer just a blockchain; it is a hybrid architecture that combines blockchain with modern cryptography, enabling more powerful features.Related plans include FOCIL, EIP-8288, streamlined consensus, state management, formal verification, memory pool improvements with privacy features, and long-term obfuscation techniques.

According to TechCrunch, AI networking technology company Cornelis announced the completion of a $205 million financing round, led by IAG Capital Partners. The company was spun off from Intel in 2020 and develops networking technology that helps AI chips communicate more effectively. It has released a product called Active Compute Fabric, which addresses the issue of a significant amount of GPU time being wasted waiting for data to arrive by allowing chips to process and send information simultaneously.Cornelis competes with Nvidia using an open architecture, allowing customers to use various GPU and accelerator hardware on its network architecture. Although Nvidia chips can technically run on other network architectures, they are optimized for their own software, making customers more inclined to use the full Nvidia GPU stack. Cornelis has begun shipping products and is developing a new generation of products expected to be released later this year.

According to on-chain analyst @ai_9684xtpa's monitoring, 40 minutes ago, two newly created wallets received airdrop contracts for 4,276 LAPTOPs from Hunter Biden's Substack subscribers, then sold them for approximately $404,000 and $243,000 respectively, totaling a profit of over $647,000.On-chain data shows that there is an ETH transfer association between the two addresses. Among them, the address 0x8DA...4A18d has transferred the proceeds from the sale in USDC to the public tagged address of Safe architect FloB (@FloB_Safe).

NVIDIA stated that it will ship both Blackwell and Rubin architecture systems in the future, and is currently facing certain supply constraints.

The Alibaba Qwen team will release Qwen 3.8-Flash-Next on Wednesday, which is a mixture of experts (MoE) model with a total of 125 billion parameters, but only 6 billion parameters are activated for each token. The team positions it as a preview version of the next-generation Qwen 4 architecture, rather than the final flagship model.The model is described as multimodal and is built on the upcoming Qwen 4 architecture. The team stated that the early release of this version is to prepare developers for the subsequent complete Qwen series. The model weights will be hosted on the Hugging Face and ModelScope platforms.As of now, Qwen has not disclosed the benchmark results for this model, nor has it released comparative data with its own Qwen 3 series or overseas competitors. The specific figures of 125 billion and 6 billion parameters have not been officially confirmed. As an open-weight model, developers can download, fine-tune, and run it for free without sending data to a closed API, which helps reduce the cost of hosting the model.

HTX global advisor Sun Yuchen stated that HTX has officially upgraded its security architecture in response to the community's demand for stronger security guarantees, claiming to keep user assets 100% SAFU. The upgrade includes enabling a multi-address withdrawal system, with hot wallet assets distributed across multiple addresses; withdrawal addresses are automatically rotated regularly, with old addresses immediately deactivated and no longer controlled after new addresses are activated; single address risk exposure has been minimized.Sun Yuchen mentioned that even in the event of extreme security incidents, the potential loss limit is below $1 million, fully covered by an insurance fund, and users will not lose any funds. He also reminded that withdrawal addresses will be changed regularly as part of normal security mechanisms, and users must verify the actual on-chain receipt situation. HTX stated that it will take every user feedback and every bit of user assets seriously.

The Offchain Labs research team has released advancements in zero-knowledge proof technology, covering areas such as proof acceleration, verifiable AI, and recursive security. Among them, the vector commitment scheme has reduced the proof generation time for 64,000 data entries from about 2 minutes to 32 milliseconds, achieving a speedup of approximately 4000 times; the new proof system Zaratan has achieved native full succinct proofs for integers for the first time, which can reduce the computational overhead of operations like RSA by about 5000 times; in terms of verifiable AI, a lightweight verification protocol can shorten the inference verification time for large models from several minutes to milliseconds.Arbitrum is exploring a multi-prover architecture that combines ZK proofs with fraud proofs and TEE to eliminate single points of failure and shorten L1 settlement cycles.

According to Finsmes, AI architecture development company Pathway announced the completion of a $30 million seed round financing, with participation from Id4 Ventures, TQ Ventures, Red Bridge Ventures, Kadmos Capital, and WS Investment, an investment institution under Wilson Sonsini. Databricks Chief AI Scientist Jonathan Frankle also joined as an angel investor.Pathway is developing the "Post-Transformer" architecture called BDH (Biologically-inspired Dynamic Hierarchy), aiming to address the limitations of current Transformer models that continuously rely on more data, GPUs, energy, and capital expansion. Unlike traditional large models that require periodic retraining, BDH can continuously learn with less data and achieve ongoing adaptation.It is reported that the company has appointed former Google DeepMind Gemini product head Adam Kurzrok as Chief Product Officer, responsible for the product direction based on the BDH model, including model packaging, evaluation systems, and commercial deployment.

According to Bloomberg, former chief architect of Alibaba's flagship model, Lin Junyang, recently announced the establishment of a new company on the X platform, focusing on developing artificial intelligence agents for the digital and physical worlds.This comes less than six months after his unexpected departure from Alibaba. The company has received investment support from Tencent Holdings and several leading venture capital firms in China.

SK Hynix stated in a recent article that the competition in AI is shifting from the performance of individual chips to the design and operation of the entire infrastructure architecture. The competitiveness of AI data centers no longer depends on individual components, but on whether the five key elements of computing, memory, storage, networking, and power cooling can be seamlessly integrated.The article points out that the continuous expansion of AI model scales has led to a surge in demand for computing power and data movement. Training requires repeatedly reading massive datasets, while inference relies on quickly retrieving user request information, both of which place higher demands on the system architecture of data centers. At the memory level, HBM, server DRAM, and others have formed a hierarchical system, each undertaking different bandwidth and capacity tasks. At the networking level, as large-scale training and inference rely on multi-server parallel processing, networking has become a key factor determining the scalability of data centers. System design is shifting from single-server to whole rack and cluster-level expansion.According to Omdia's forecast, the AI data center chip market will grow from $123 billion in 2024 to $207 billion in 2025, reaching $286 billion by 2030. SK Hynix also mentioned that Microsoft's Fairwater data center in Wisconsin is about the length of five football fields, indicating that infrastructure is being deployed on a larger scale. SK Hynix emphasizes that memory is becoming a key layer connecting computing and data.

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.

According to exclusive reports from Titanium Media, ByteDance released an internal email on July 30, announcing the integration of the Feishu product team and the Doubao product team to form a new Doubao product team, which will be unified under the leadership of Doubao head Zhao Qi, while Feishu head Xie Xin will report to Zhao Qi. In terms of the GTM system, the Feishu GTM team will integrate with the Volcano Engine team to establish a new ToB GTM organization called the "Creativity Service Platform," which will be responsible for the marketing, sales, and customer service of ByteDance's MaaS and SaaS cloud services, led by Volcano Engine head Tan Dai, with Feishu sales head Lin Chan and Feishu strategy and marketing head Shi Zhijun reporting to Tan Dai.This integration is the largest adjustment to ByteDance's ToB business since it implemented business segmentation in 2021. After the reorganization, Feishu's products and services will remain unchanged, and Feishu will collaborate more deeply with Doubao on productivity scenarios. The Doubao enterprise version, developed with deep involvement from the Feishu product team, has already begun internal testing among some Feishu clients. Feishu currently covers over 10 million enterprise users, and this integration will further enhance the integrated collaborative capabilities of the ToB business.