News linked to both this project and an event.
Odaily News: Oracle and quantum computing company Quantinuum have announced a multi-year partnership to connect Quantinuum's Helios quantum computer to Oracle Cloud Infrastructure (OCI). Customers will soon be able to combine quantum computing with resources such as GPUs and high-performance computing through OCI's quantum services.In addition, Oracle plans to preview its quantum computing services in the coming months and will integrate Quantinuum's development tool stack with open-source hybrid programming frameworks for developing and testing quantum-classical hybrid applications. The two parties did not disclose the collaboration amount or specific deployment dates. (Reuters)
Odaily News: Bitcoin News posted on X platform that a new technical analysis released by @KLoaec shows that some vulnerable COLDCARD Mk3 wallets may be generated from only approximately 4.5 million random number generator starting states, which can be searched in about 3 seconds on a single RTX 4090 GPU. Even accounting for additional uncertainty in each wallet's generation method, an attacker could complete the search in about 50 minutes on a single high-end GPU. More critically, this vulnerability could cause different devices to generate identical mnemonic phrases. Assuming 30,000 Mk3 devices, the analysis estimates that approximately 120 pairs of devices could generate the same random number stream. This collision estimate is theoretical but indicates that duplicate mnemonic generation across different devices may be possible.
Odaily News – River Markets, a startup building trading infrastructure for prediction markets, has announced the completion of an $8.5 million seed funding round, led by Haun Ventures with participation from Y Combinator, Coinbase Ventures, and Qube Research Technologies, among others. The new capital will primarily be used to expand the engineering team, enhance trading system speed and security, and grow institutional clientele, while also developing new tools to support large-scale capital management and cross-platform trading.In recent years, prediction markets have drawn attention from institutional investors. Data from industry platforms shows that institutional trading demand is growing rapidly. For example, prediction market platform Kalshi previously stated that its institutional trading volume increased by approximately 800% within six months. Meanwhile, market participants have begun using prediction markets for risk hedging, including building trading positions around real-world economic variables such as carbon emission allowances and GPU rental prices. (Fortune)
Nvidia is increasing its investment in open-source artificial intelligence models, aiming to further drive demand for its hardware ecosystem by building the world's leading open-source AI model series, Nemotron.According to sources familiar with the matter, Nvidia is developing a new generation of AI models called Nemotron 4, with the largest model targeting performance levels comparable to the world's top open-source AI models. The project is driven by Nvidia's internal team, as the company hopes to attract more developers and enterprises to use its GPUs, AI software platforms, and infrastructure through high-performance open-source models.In recent years, Nvidia has gradually expanded from purely providing AI computing hardware to building an AI software and model ecosystem. By releasing open-source models, the company can help developers build applications based on Nvidia's CUDA, GPU clusters, and related tools, thereby further strengthening hardware demand.However, Nvidia's self-developed AI models may also create new competitive dynamics. On one hand, open-source models can expand the influence of Nvidia's AI ecosystem; on the other hand, as its model capabilities improve, they may compete with AI models developed by some of its customers and partners.Analysts believe that as competition in the AI industry extends from "computing power competition" to "model, software, and ecosystem competition," Nvidia is attempting to replicate its ecosystem advantages in the GPU space, transforming its hardware leadership into broader influence across the AI platform landscape. (The Information)
Odaily News Nvidia CEO Jensen Huang announced that the company has partnered with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs, and KKR to establish an independent financing platform, planning to mobilize over $500 billion in third-party capital over the long term to support AI infrastructure development.Huang stated that the AI industry is transitioning from a phase where "enterprises purchase chips and build data centers project by project" to a new stage where AI factories serve as financeable productive infrastructure. AI computing power is becoming an investable asset, characterized by long-term institutional capital support, repeatable construction, and usage by diverse customers.Nvidia noted that AI factories encompass not only GPUs but also high-speed networking, system software, AI frameworks, and the CUDA ecosystem. Built on globally widely adopted architectures, AI factories can serve different customers, cloud providers, and application scenarios, while possessing strong asset liquidity and residual value.In this collaboration, Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs, and KKR will independently evaluate specific projects, including customer demand, compute utilization, cash flow, and asset value. Nvidia will provide the AI factory platform, while the financial institutions will handle long-term capital and financing capabilities.Huang indicated that in some projects, Nvidia may provide up to 25% residual value support, but this will be prudently assessed on a project-by-project basis. The mechanism is designed to supplement, not replace, the independent judgment of institutional investors.He believes that AI factories will become the "infrastructure of the intelligent era," much like how electricity, transportation, and communication infrastructure drove past industrial revolutions. Going forward, growing demand for AI computing will create a virtuous cycle where "more compute drives stronger AI, stronger AI generates more revenue, and more revenue further fuels compute demand."
According to CNBC, Nvidia has signed a memorandum of understanding with Apollo Global Management, Blackstone, BlackRock, Brookfield Asset Management, Goldman Sachs, and KKR to jointly establish a financing platform for Nvidia customers, aiming to mobilize over $500 billion in third-party capital for hyperscale data center construction and Nvidia hardware procurement. Nvidia CEO Jensen Huang characterized this as the first time AI chips have become an "investable asset class," stating they possess revenue-generating capabilities, long service lives, and can be transferred across customers, while analogizing compute infrastructure to electricity and the internet. BlackRock CEO Larry Fink defined the project as the "next future of financial engineering" following the securitization of mortgages in the 1970s, and stated that more funds would be raised as soon as possible. Goldman Sachs CEO David Solomon revealed that this collaboration was initiated by Jensen Huang. Currently, some funds have already been raised; the parties will provide financing support for GPUs and data centers through institutional credit, insurance capital, and private capital, helping end users complete AI infrastructure construction without tapping their own balance sheets.
Odaily News Nvidia-backed AI cloud computing provider Lambda is raising $917 million through the leveraged loan market to procure AI chips. As artificial intelligence infrastructure construction accelerates, chip financing is emerging as a new avenue for capital investment in the AI industry.Lambda belongs to the rapidly growing camp of "neoclouds" in recent years, primarily offering GPU computing power and AI infrastructure services to enterprises and developers. This financing plan will be carried out through a GPU-backed loan based on GPU asset-related rights, designed to support the company in expanding its AI computing resources.According to reports, AI infrastructure companies are actively exploring new financing methods to meet the massive capital investments required to build large-scale computing clusters. Previously, AI cloud service provider CoreWeave completed the first chip financing transaction in the institutional leveraged loan market, providing a new financing model for the industry.As demand for generative AI continues to grow, Nvidia GPU supply has become a core resource for AI companies' expansion. By using GPU assets as a financing basis, AI cloud providers can rapidly scale up computing capacity without relying entirely on equity financing, while also bringing traditional credit markets into the wave of AI infrastructure investment. (Bloomberg)
Odaily News: After forking at block height 961632, the BIP-110 minority chain has only mined two blocks, 961632 and 961633, and has since stalled due to inheriting Bitcoin's difficulty of approximately 127.48 trillion while receiving extremely low SHA-256d hash power. Pre-fork miner support was approximately 0% to 2.6%. BIP-110 supporters are discussing replacing the proof-of-work algorithm to break free from reliance on Bitcoin miners and SHA-256d hash power. Luke Dashjr has proposed selecting the final algorithm from a shortlist of candidates through a deterministic random process, with options under discussion including RandomX, KT256, BLAKE3, Scrypt, as well as CPU and GPU mining. No PoW changes have been enabled or approved yet, no algorithm has been selected or activation height announced, and Bitcoin Knots has not committed to adjusting the PoW. Relevant experimental code has been ported to the recent Bitcoin Knots codebase, but the BIP-110 minority chain has still not resumed block production.
Odaily News: SK Hynix's stock price has recently seen a pullback. On August 3, the stock fell 8.79%. Although it rebounded slightly by 0.64% and 5.77% on August 4 and 5 respectively, it plunged another 10.37% on August 6, closing at 1.495 million KRW; on August 7, it dropped a further 4.88%, closing at 1.422 million KRW.Against the backdrop of heightened market volatility, SK Group released an advertisement quoting founder Choi Jong-gun’s famous saying: "Despair and hope are two sides of the same coin; you can turn despair into hope as easily as flipping your palm," and adapted it to: "Unease and anticipation in the AI era are also two sides of the same coin; you can turn unease into anticipation," thereby conveying confidence in the long-term development of the AI industry.Securities institutions believe that short-term stock price fluctuations have not changed SK Hynix's fundamentals, and the market should focus on its HBM4 technology leadership and the earnings stability brought by long-term supply agreements (LTAs). Specifically:1. Hyundai Motor Securities expects SK Hynix's DRAM and NAND bit growth to reach 9.7% and 1.5% respectively in the third quarter. As HBM4 sales contributions expand, even with a higher proportion of LTAs, DRAM average selling prices (ASP) are still expected to rise 19.9% quarter-over-quarter. Companies such as OpenAI and Anthropic are advancing plans to build their own hyperscale AI data centers and intend to raise funds for related construction through IPOs. Even if some large tech companies adjust capital expenditures (Capex) in the future, this could be offset by demand from other AI infrastructure. Additionally, regarding competitive concerns over China's CXMT, given the U.S. continued tightening of semiconductor equipment export restrictions, as well as Micron's expansion of domestic U.S. investment, the likelihood of major companies like Apple adopting Chinese memory chips is relatively low.2. SK Securities is also bullish on SK Hynix's competitive advantages, believing that with its leading position in HBM, partnerships with major North American GPU companies, and AI-driven LTA demand, SK Hynix's market position remains solid. Currently, the HBM supply-demand fulfillment rate is below 70%, and the core value of LTAs lies in ensuring profit sustainability and earnings stability through a "mutual binding structure" between customers and suppliers. With value-reassessment initiatives such as an ADR listing progressing, along with dividend income from the sale of SPC assets related to Kioxia, the company's goal of achieving net cash of 100 trillion KRW may be reached earlier than expected. As shareholder return policies gradually become clearer, this will help the market re-evaluate the value of the LTA model and drive a further re-rating of SK Hynix. (Daum)
To address HBM memory supply shortages, NVIDIA is considering reducing the specifications of the next-generation Rubin Ultra GPU. According to sources cited by The Information, NVIDIA has internally tested at least three versions of the Rubin Ultra GPU with lower HBM configurations over the past few weeks, requiring HBM capacity lower than the initially announced specifications. Possible downgrade paths include scaling down from HBM4E to HBM4, and from 12Hi HBM to 8Hi HBM. This move aims to advance product launch plans under supply constraints.
Western Digital Chief Product Officer Ahmed Shihab published a long article pointing out that as AI infrastructure expands rapidly, the core competition in the storage field should not be simply reduced to a contest between Flash and Hard Disk Drives (HDD), but lies in whether an AI storage architecture with long-term economic scalability can be built. The AI industry is currently facing a key question: whether the storage architecture chosen this year can support future data scale growth to the PB level or even the EB level. Many AI infrastructure designs do not fail due to insufficient performance, but fall into cost dilemmas after data scale expands. Ahmed Shihab added that Flash and HDD are not in a competitive relationship, but are complementary technologies for different workloads. High-performance scenarios, such as model weights, GPU spillover, KV cache, etc., require low-latency Flash support; while long-term storage needs such as training datasets, logs, checkpoints, compliance records, and large-scale historical data are more suitable for adopting HDDs with cost advantages. Storage architecture in the AI era will be more layered, rather than relying on a single storage medium. "Flash handles performance at critical moments, HDD handles data lifecycle. The direction of future AI storage development is not 'Flash replacing HDD', but precise layering based on different data lifecycles and business requirements." "True infrastructure is not about pursuing dazzling performance, but a reliable foundation capable of supporting long-term AI growth." US stock market trends show, Western Digital
Odaily News: AI research startup Mirendil has entered into a multi-year partnership agreement with Google Cloud to secure large-scale computing resources in support of its "Self-Improving AI" research and development. Under the agreement, Mirendil will gain access to TPU and NVIDIA GPU computing resources provided by Google Cloud, as well as managed AI training clusters, to develop AI systems capable of continuously optimizing their own capabilities. It is reported that Mirendil is focused on advancing "Recursive Self-Improvement" AI, in which AI systems enhance their own performance through iterative refinement, self-learning, and optimization. This direction is also a research area of interest among some of the top AI laboratories today.Benham Neyshabur, co-founder and CEO of Mirendil, revealed that the total value of the agreement exceeds $100 million, roughly equivalent to half of the $1 billion valuation seed funding round the company completed at the end of June. (TechCrunch)
Odaily News AMD, the semiconductor giant, announced the launch of its enterprise-grade AI programming platform, AMD Instinct Coder. The platform combines AMD chips, Supermicro servers, and Spectro Cloud software, aiming to help enterprises deploy AI coding assistants locally, reduce the cost of cloud-based AI models, and protect code and data security.AMD stated that Instinct Coder is an "out-of-the-box" end-to-end AI development platform, integrating AMD EPYC processors, AMD Instinct GPUs, Supermicro AI servers, Spectro Cloud PaletteAI Inference Launchpad software, and the AMD-optimized GLM-5.2 model. It can be used for software development scenarios such as code generation, application modernization, automated testing, and code review.AMD said that compared to relying on cutting-edge cloud-based AI models, Instinct Coder can help enterprises reduce total cost of ownership (TCO) by up to 70%, with the fastest payback period shortened to 6 months.AMD noted that more and more enterprises are looking to leverage AI to improve development efficiency, but face two major challenges: on one hand, the cost of invoking top-tier cloud models continues to rise; on the other hand, entrusting enterprise source code, intellectual property, and sensitive data to third-party services poses security and compliance risks.Through a local deployment model, Instinct Coder allows enterprises to maintain control over their data and code while providing more predictable infrastructure costs. The platform supports development tools such as Claude Code, OpenAI Codex, Visual Studio Code, and Cursor, with each node supporting up to 50 users (30 concurrent users).Additionally, the PaletteAI Inference Launchpad provided by Spectro Cloud enables AI workload management, model routing, request auditing, and cost monitoring, and supports invoking external models such as Anthropic, OpenAI, Google, or xAI when needed.AMD stated that Instinct Coder aims to help enterprises break free from the high costs of cloud-based AI services, accelerate AI-driven software development processes while ensuring data security and autonomous control.
Odaily News: Bitdeer announced that its subsidiary Tydal Data Center AS has signed a 16-year data center hosting and services agreement with Volta Tydal AS, which will provide 121 MW of IT load capacity (approximately 133 MW total power) at the Tydal AI/HPC campus in Norway, all to be deployed with NVIDIA GPUs to serve a leading AI laboratory. The total expected contract payments during the base term are approximately $4.7 billion, with an 8-year renewal option attached, bringing the potential total contract value after renewal to approximately $8 billion. (Stocktitan)
Odaily News: SK Hynix and SanDisk have unveiled the first standard specification for High Bandwidth Flash (HBF), a next-generation storage technology based on NAND flash. SK Hynix presented the specification at FMS 2026, held from August 4 to 6 in Santa Clara, California, USA.HBF stacks NAND flash vertically in a manner similar to High Bandwidth Memory (HBM) to enhance capacity and data transfer speeds. The specification defines two stacked configurations—8-layer and 16-layer NAND dies—with a maximum capacity of 512GB and bandwidth offered in three tiers, supporting 0.4TB to 3.0TB per second.HBF connects to processors using the industry-standard UCIe interface, enabling compatibility with different processor types such as GPUs and CPUs. The specification has been released through the Open Compute Project (OCP), and the HBF Consortium currently includes Google and AI semiconductor company Tenstorrent.SK Hynix will also showcase its in-development 10th-generation (V10) 375-layer 4D NAND wafers and products for the first time at this event, with plans to begin mass production of high-performance, high-capacity enterprise SSDs (eSSD) utilizing this technology early next year.
KIOXIA officially announced its first GP series SSD, the KIOXIA GP1, supporting GPU direct access to high-speed flash memory. This product achieves ultimate random read performance of 100M IOPS. KIOXIA stated that the KIOXIA GP1 series aims to support emerging AI storage architectures that incorporate high-speed flash media into video memory systems. This method enables AI systems to access larger datasets at a cost far lower than adding HBM, while improving GPU utilization.
HIVE Executive Chairman Frank Holmes stated that the company's cluster of 504 NVIDIA B200 GPUs at Bell Canada's Manitoba AI fabric generates approximately $2.90 per GPU per hour in revenue; by comparison, HIVE's Bitcoin mining equipment generates approximately $0.12 per hour. HIVE's total revenue for fiscal year 2026 reached $298 million, up 158% year-over-year; digital currency revenue from Bitcoin mining grew 164%. During the same period, average hash rate stood at 22.2 EH/s, up 290% year-over-year, accounting for approximately 3% of the Bitcoin network's total hash rate, and the company mined 2,885 BTC. HIVE's BUZZ HPC division, which houses its AI and high-performance computing business, generated revenue of $19.5 million, up 94% from $10 million in the prior fiscal year. The company also signed GPU cloud agreements worth approximately $220 million with Bell and AI company Cohere, and raised $75 million through a note issuance to fund AI infrastructure expansion. HIVE is building a 320-megawatt AI data center in the Greater Toronto Area, with plans to eventually house more than 100,000 GPUs. The company stated that if the facility becomes fully operational in the second half of 2027, it could generate approximately $360 million in annualized recurring revenue.
According to TechFlow Research, Morgan Stanley released a research report on July 27, quantifying for the first time the Incremental Return on Invested Capital (ROIC) of Generative AI investments. The report constructed three estimation frameworks: the ROIC for hyperscale cloud service providers' GPU leasing business is approximately 31%, the ROIC for proprietary infrastructure model API business is approximately 46%, and the ROIC for third-party compute API business is approximately 25%. Under base case assumptions, a single 1 gigawatt (GW) data center is configured with approximately 410,000 NVIDIA GB300 GPUs, with a utilization rate of 75% and an hourly leasing price of $8.5. The combined capital expenditure of the three major cloud giants is expected to exceed $1.4 trillion. Morgan Stanley maintains an Overweight rating on Microsoft, Amazon, Meta, and Google. The report points out that as AI moves from the training phase to the inference phase, demand for GPU compute power will continue to grow. Providers with self-built compute infrastructure will achieve considerable profits by leveraging their pricing power in an ecosystem where compute is scarce. If Morgan Stanley's calculations hold true, the hundreds of billions of dollars in AI capital expenditure will shift from being perceived as "costs" to "growth assets".
据韩联社报道，韩国国家 AI 计算中心将于 8月 3 日在全南光州海南市溔라시도企业城市举行开工典礼，正式启动建设。该项目由三星 SDS 联合体（成员包括三星 SDS、NAVER Cloud、三星物产、Kakao、三星电子、KT 等）承建，总投资 2.4 万亿韩元，规划用地面积约 4.9 万平方米。中心计划 2028 年前完成 1.5 万张 GPU 部署，2030 年前进一步扩展至 5 万张，供电规模最终将达 80MW。全南光州特别市预计该项目将带动 6.4 万亿韩元经济效益及 1.95 万个就业岗位。
Axe Compute Inc. (Nasdaq: AGPU) today announced a new five-year contract with a customer valued at over $1.5 billion to deploy a large-scale dedicated AI infrastructure cluster in the United States based on the NVIDIA Blackwell architecture. Secured through Axe Compute's Build program, the contract will provide over 9,200 NVIDIA Blackwell B300 GPUs to construct a dedicated cluster designed, deployed, owned, and operated by Axe Compute.Combined with previously announced Build agreements, this new contract brings the total value of contracts signed by Axe Compute in 2026 to over $3 billion. Axe Compute expects to receive over $534 million in customer prepayments related to this agreement and previously announced contracts within the next 30 days. These payments are expected to cover most of the associated GPU and infrastructure capital expenditures.The Axe Build program is expected to start generating monthly revenue this quarter, with additional clusters becoming operational in the fourth quarter of 2026. It is anticipated that this agreement, along with previously announced contracts, will bring the annualized run rate to over $696 million after deployment is complete, nearly double the $385 million run rate the company reported earlier this month.It is reported that Axe Compute Inc. is an artificial intelligence infrastructure platform based on a new cloud architecture.