News linked to both this project and an event.
According to CoinDesk, cryptocurrency platform Bullish will provide $100 million in stablecoin debt financing to USD.AI to support loans collateralized by GPUs and other high-performance computing assets, advancing AI infrastructure development.
According to Chaowang Research, JPMorgan’s August 28 research report states that OpenRouter platform token volume increased 47% month-over-month and 28 times year-over-year in August, while expenditure rose 7% month-over-month and 12 times year-over-year; the volume-weighted average price decreased 28% month-over-month, with low-priced models such as GPT-5.6 Luna accounting for approximately 99% of the incremental volume. In the GPU rental market, A100 prices remained flat at $1.65/hour, H100 rebounded to $2.73 (+1.2%), and B200 fell 1.5% month-over-month to $5.63, marking the first monthly decline since the index was published in September 2025. DRAM spot prices have risen for five consecutive months, with DDR5 16Gb reaching $50.20 (+6% month-over-month, +880% year-over-year); NAND ended a four-month downward trend, with 1Tb quoted at $30.50 (+14% month-over-month, +470% year-over-year). JPMorgan observes that AI computing demand continues to expand, yet structural shifts on the supply side are reshaping pricing dynamics. Closed-source and open-source models are growing in tandem, with lower-priced models gaining market share while higher-priced models drive the majority of revenue. The price reduction for B200 reflects increased capacity for next-generation GPUs, while the rebound in H100 pricing demonstrates sustained demand resilience for the preceding generation. With both DRAM and NAND showing strength, the ongoing crowding-out effect of HBM on DRAM capacity continues to provide positive support to semiconductor equipment suppliers.
Odaily News: SemiAnalysis posted on X that AMD middle managers are spending the time of more than 20 engineers trying to expand their sphere of influence and secure promotions through a useless side project called the "ATOM Inference Engine," rather than allocating those resources to inference engines actually being used by real customers like Meta and xAI, such as SGLang and vLLM.SemiAnalysis said that dozens of AMD engineers, including principal engineers and AMD Fellows, have privately contacted the firm, stating that due to internal office politics at AMD and support from some middle managers, they are unable to discuss their concerns internally. Middle managers are consuming the time of more than 20 full-time engineers to develop this side project with almost no customers, and the engineers involved are all "10x engineers" who should have been dedicated to developing customer-facing inference engines like vLLM and SGLang.SemiAnalysis said that middle managers will likely respond by pointing to the only customer using the project in a production environment—Alibaba, based on Qwen—but further investigation shows that this is merely a limited deployment of ATOM by Alibaba's enterprise business unit, not the main business unit behind Qwen.SemiAnalysis stated that AMD management has diverted resources and limited internal GPU R&D clusters away from engineers supporting production-grade inference engines such as vLLM and SGLang, instead using them to expand their own influence and engage in office politics, showing a profound lack of respect for AMD engineers.
According to TechCrunch, Amazon and NVIDIA have announced an expansion of their partnership, with AWS planning to deploy an additional 2 million NVIDIA GPUs between 2027 and 2028. The deployment will cover Blackwell Ultra, Rubin, and Rubin Ultra to meet the rapidly growing compute demand from startups, AI labs, enterprises, and government clients. This comes just five months after Amazon previously committed to deploying over 1 million NVIDIA GPUs. Neither party disclosed the transaction amount, but based on per-unit GPU pricing, the order is estimated to be worth tens of billions of U.S. dollars. Beyond chip procurement, AWS will also integrate NVIDIA’s networking, CPUs, open-source models, and physical AI and robotics stacks, including Omniverse and Isaac.
NVIDIA CFO announced that the company will deploy an additional 2 million GPUs within AWS's global infrastructure between 2027 and 2028 to strengthen both parties' computing power collaboration.
Odaily News Nvidia will release its fiscal 2026 second-quarter earnings after the U.S. market close. According to analyst estimates compiled by LSEG, the company's quarterly earnings per share are expected to be $2.10, with revenue projected to reach $92.17 billion.The market expects Nvidia's revenue to nearly double from $46.7 billion in the same period last year, continuing the rapid growth driven by the wave of artificial intelligence infrastructure investment. As a core supplier of AI computing power, Nvidia's GPUs are widely used to train and run advanced AI models, and the company is also involved in advancing the construction of next-generation AI data centers through financing support and other means.However, after nearly three years of significant gains, investor expectations for Nvidia have become more cautious. As of Tuesday's close, Nvidia has risen approximately 14% year-to-date, slightly outperforming the Nasdaq index. Market concerns include competitive pressure from rivals such as AMD and Google, as well as rising costs stemming from the global memory chip shortage.Currently, Nvidia is in a new product cycle, with its latest Vera Rubin AI system already being delivered to customers including Microsoft and OpenAI. Investors will focus on sales progress and supply conditions for the Rubin and Blackwell chip families, as well as the company's outlook for future AI computing power demand.Nvidia CEO Jensen Huang has previously stated that he expects the current product cycle based on the Blackwell and Vera Rubin architectures to generate cumulative sales of $1 trillion by 2027. The company will hold its earnings conference call at 5:00 PM ET. (CNBC)
Odaily News: Qualcomm Technologies announced the launch of the Qualcomm Intelligent Multimedia SDK (IMSDK) 2.0, providing a unified development framework for AI and multimedia application development based on the Qualcomm Dragonwing platform.Qualcomm stated that IMSDK 2.0 is designed to help developers build intelligent applications on edge devices that integrate generative AI, multimedia processing, and real-time analytics capabilities, consolidating AI model inference, cameras, audio, video, sensors, and cloud connectivity into a single development environment, covering scenarios such as intelligent cameras, industrial robots, drones, and IoT devices.The new SDK introduces a Pipeline API and application building tools for Python and C++, reducing developers' reliance on underlying multimedia frameworks. Additionally, IMSDK 2.0 supports multiple AI inference paths, including the Qualcomm AI Runtime SDK (QAIRT), ONNX Runtime, and TensorFlow Lite, and can run models on CPU, GPU, or NPU as needed.Furthermore, IMSDK 2.0 introduces Coding Agent Skills for AI programming assistants, Documentation as Code, and containerized microservices capabilities, helping developers complete application building, debugging, deployment, and optimization through natural language instructions.
Bitdeer released its July 2026 Production and Operations Update: The company has signed a 16-year, $4.7 billion artificial intelligence data center (AIDC) colocation lease agreement for its Tydal site in Norway, configured with 121 MW of IT capacity to operate Nvidia GPUs.
Enflame Technology (688801.SH), one of China's "Four Little Dragons" in the domestic GPU sector, announced that it will launch its initial public offering and list on the STAR Market, planning to issue 43.035173 million shares, accounting for 10% of the post-issuance total share capital of 430 million shares.
Bitcoin News posted on X platform, stating that Simon Males has launched Krackpot, a browser-based game that allows anyone to use GPU to attempt cracking the private key of Bitcoin Puzzle 71. The prize is 6 BTC. The probability of cracking depends on the number of GPUs: a single gaming GPU would take approximately 830,000 years, 1 million GPUs would take 1 year, and simultaneous participation from all Steam players would take 1 week. The game runs locally in the browser via WebGPU. If a user finds the private key, 6 BTC will be sent to their designated Bitcoin address, with the remainder going to the developer.
According to TechFlow Research, the frontier AI data tracking report released by Bank of America Securities on August 17 shows that Anthropic leads comprehensively in three major AI benchmarks, with Claude Opus 5 ranking first in the Intelligence Index, Agent Index, and Coding Agent Index, GPT-5.6 Sol following closely behind, Meta MuseSpark 1.2 entering the top ten, and Google Gemini 3.6 Flash ranking outside the top ten. In terms of usage, DeepSeek leads with approximately 30% of the Vercel platform token share, Anthropic accounts for 25% and OpenAI accounts for 16%; but in terms of payment amount, Anthropic leads far ahead with 65%, while OpenAI accounts for only 11%. In terms of pricing, the AI Token Price Index decreased 9% month-over-month in August to $2.21, but still increased 87% year-over-year; GPU rental rates remain strong, with H100 increasing 33% year-over-year to $2.77/hour, DRAM increasing 483% year-over-year, and NAND increasing 432% year-over-year. The research report judges that AI infrastructure demand remains healthy, with open-source model usage growing but payment share still highly concentrated on top closed-source models. BofA believes that the Meta "Watermelon" and Google Gemini 4 releases, token pricing trends and GPU rental trends are
According to Cryptopolitan, former Bitcoin mining company IREN announced the completion of the first milestone of its $9.7 billion, five-year contract with Microsoft — the official delivery of the Horizon 1 facility located in Childress, Texas. The facility is 50 megawatts in scale, equipped with Nvidia GB300 systems and direct chip-level liquid cooling technology, and has received the Exemplar Cloud certification awarded by Nvidia. Under the contract terms, Microsoft will complete GPU acceptance verification within five days; upon approval, IREN can commence monthly billing, with expected annualized revenue of approximately $1.94 billion after all four Horizon facilities go online. IREN plans to complete the deployment of all four phases totaling 200 megawatts by 2026, expand AI cloud computing power to 1.2 gigawatts by 2027, simultaneously exit the Bitcoin mining business, and target a full-year AI cloud revenue run rate exceeding $4 billion.
Odaily News - Digital infrastructure company HIVE Digital Technologies' high-performance computing division, BUZZ High Performance Computing, has signed a five-year AI cloud services contract worth approximately $350 million with an undisclosed investment-grade enterprise client. The contract is expected to generate approximately $70 million in additional annual revenue, bringing BUZZ HPC's annualized revenue to approximately $180 million. BUZZ HPC will deploy 2,016 NVIDIA Blackwell Ultra GPUs, utilizing the GB300 NVL72 system, NVIDIA Quantum-X800 InfiniBand networking, and VAST Data storage. The cluster is expected to become operational later this year at Bell's AI Fabric facility in Merritt, British Columbia, Canada, which runs on renewable hydroelectric power and closed-loop liquid cooling technology. HIVE estimates the project's capital expenditure at approximately $185 million, which will be funded through previously announced financing and new equipment debt. The company expects daily revenue of approximately $500,000 from its HPC and AI business once the cluster is fully operational, and plans to achieve $200 million in annualized GPU cloud services revenue by year-end. The company holds approximately 400 megawatts of capacity in Canada, which can support over 120,000 GPUs over the next two years. (Bitcoin.com News)
Odaily News "White-Haired Stock God" Serenity shared insights on the AI industry chain on the X platform, noting that AI infrastructure demand is driving multiple sectors—including storage, advanced packaging, computing power financing, optical communications, power supply, and electronic components—into a long-term expansion cycle. The AI supply chain remains in a phase of rapid growth.In the storage sector, Serenity cited UBS forecasts indicating that traditional DRAM manufacturers (such as Micron) could see gross margins reach an unprecedented 95% by 2027, potentially even surpassing the gross margin levels of HBM products. Additionally, SanDisk's long-term agreements already cover approximately two-thirds of its 2028 production capacity, with minimum contracted revenue reaching $93 billion. Given its current market cap of around $239 billion, this suggests its future revenue targets could persist for years, making it difficult to simply classify the company as a traditional cyclical stock.On the cloud computing infrastructure front, CoreWeave has signed agreements to use Nvidia A100 GPUs through 2029. This is a positive development for emerging cloud computing companies such as Nebius and Iren, and it also weakens some investors' bearish thesis centered on the rapid depreciation of older GPUs.AI model companies are also continuing to grow at a pace that exceeds expectations. Frontier AI labs are still maintaining extremely rapid growth rates, and a slowdown in growth would actually be a cause for concern. The market projects that Anthropic's 2028 revenue could reach $190 billion to $200 billion.However, advanced packaging and semiconductor infrastructure remain core bottlenecks. The head of advanced packaging at TSMC has stated that in the coming years, the industry may face not only memory shortages but also tight supply of ABF substrates.Serenity concluded that the AI infrastructure supply chain is continuously expanding. From GPUs, storage, and advanced packaging to power, optical communications, and electronic components, every segment is showing a long-term demand growth trend. The AI supply chain is still in a high-speed development stage.
Odaily News - AMD has announced "Day 0" support for Qwen3.8 27B, the latest-generation model from Alibaba's Tongyi Qianwen (Qwen) series, enabling developers to run this large-scale open-source AI model locally on AMD hardware on the very day of its release.AMD stated that Qwen3.8 27B is a 27B-parameter intensive model suited for local AI development, continuing the Qwen series' optimization focus on code generation, practical work tasks, scientific research, and long-context AI applications. The model can run via the open-source inference framework llama.cpp on AI PCs and workstations powered by AMD processors, or on a single AMD 32GB graphics card, while also supporting AMD hardware platforms with over 24GB of variable graphics memory (VGM) or VRAM capacity.AMD's preliminary tests show that Qwen3.8 27B delivers strong local inference performance on AMD platforms: up to 24.5 tokens/second on the AMD Ryzen AI Max+ 395 processor, and up to 51.8 tokens/second on a single Radeon AI PRO R9700 GPU. The tests were conducted on Windows systems using the llama.cpp Vulkan backend with multi-token prediction (MTP) optimization enabled. AMD noted that actual performance still has room for improvement as further software and model optimizations are rolled out.
SanDisk announced the latest progress on High Bandwidth Flash (HBF) at an investor meeting. The first product has completed tape-out, with plans to provide initial samples in 2027 and mass production in 2028. HBF combines HBM-level read bandwidth, achieving 8-16 times the capacity. According to SanDisk's internal data, when running large AI models, 4 GPUs can achieve the token output of 8 GPUs in an HBM system. The first version of HBF supports up to 512GB capacity, offering three bandwidth tiers, covering 0.4TB/s to 3.0TB/s.
Odaily News - Analyst qinbafrank posted on X platform, stating that the latest earnings reports from CoreWeave (CRWV) and Nebius show the AI cloud computing (CSP) industry is entering a phase of rapid expansion. The competitive focus is shifting from simply providing GPU leasing to building AI infrastructure platforms that encompass computing power, software, data, and operational capabilities.Currently, AI computing demand still significantly exceeds short-term deliverable supply. Meanwhile, pricing power for AI computing is strengthening, but price increases are mainly concentrated on high-value resources. CoreWeave stated that prices for various GPU computing SKUs rose by approximately 25% on average in July; Nebius disclosed that prices for previous-generation GPUs increased by over 30% compared to Q1, with new contracts signed in Q2 averaging over $20 million in annualized revenue per MW, some projects reaching $20 million to $25 million, and short-term emergency capacity prices even reaching $40 million to $50 million per MW.However, price increases are mainly occurring in short-term capacity, next-generation GPUs, large-scale clusters, and production-grade AI inference scenarios. Traditional low-priority, long-term locked-in bare computing power has not seen concurrent price increases. From a profitability model perspective, project-level returns on AI computing are becoming clearer, but overall corporate return on invested capital (ROIC) still needs time to be validated. Nebius has for the first time disclosed relatively clear project payback periods, while CoreWeave is reducing GPU investment pressure through long-term contracts and asset-level financing. However, both companies remain in a high-capital-expenditure phase, with depreciation and financing costs continuing to compress profit margins.Nevertheless, an increasing number of individual projects are achieving closed-loop economic models, indicating that the AI infrastructure business model is gradually maturing. Additionally, both CoreWeave and Nebius are upgrading toward becoming "AI infrastructure operating systems." Future CSP competition will no longer be just about renting out GPU hours but will cover complete service systems including AI training, inference, storage, networking, model deployment, monitoring, security governance, and Agent runtime environments.In terms of capital models, the two companies are also taking different paths: Nebius leans more toward an asset-light model, building AI data centers through capital partners while providing AI infrastructure operations and software capabilities itself; CoreWeave, on the other hand, is promoting a hybrid cloud model through its Omni strategy, deploying complete AI cloud platforms to customers' own data centers and GPU resources, placing greater emphasis on enterprise-level and sovereign AI delivery.Overall, the AI cloud computing industry is evolving from "GPU rental providers" to "AI infrastructure platforms." Short-
Odaily News: AI architecture development company Pathway has announced the completion of a $30 million seed funding round, with participation from Id4 Ventures, TQ Ventures, Red Bridge Ventures, Kadmos Capital, and WS Investment, the investment arm of Wilson Sonsini, among others. Databricks' Chief AI Scientist Jonathan Frankle has joined as an angel investor.Pathway is developing a Bio-inspired Dynamic Hierarchical architecture (BDH), a "post-Transformer" architecture designed to overcome the limitations of current Transformer models, which continue to rely on ever-increasing data, GPUs, energy, and capital expansion. Unlike traditional large models that require periodic retraining, BDH enables continuous learning and ongoing adaptation with significantly less data.The company also announced the appointment of Adam Kurzrok, former product lead for Google DeepMind's Gemini, as Chief Product Officer. He will oversee the product direction of BDH models, covering areas such as model packaging, evaluation systems, and commercial deployment. (Finsmes)
NVIDIA CEO Jensen Huang stated that A100 GPU clusters will remain available from 2020 to 2029, emphasizing that the core value of the NVIDIA computing platform lies not only in the chips themselves, but more in CUDA providing a unified platform for developers and NVIDIA engineers, enabling Ampere, Hopper, and Blackwell architectures to continue receiving upgrades throughout their lifecycle.
According to TechFlow Research, a Bernstein research report on August 10 pointed out that Microsoft's current lease liabilities increased 33% year-over-year to $114.4 billion, future lease obligations surged 255% year-over-year to $329.1 billion, and fiscal 2027 procurement commitments reached $169 billion. The report believes the market has misread these figures: existing leases are spread over a 13-year period, with rent expiring in 2027 at approximately $13.2 billion; the $329.1 billion future leases will commence sequentially between 2027 and 2033, assuming an average lease term of 12 to 15 years, the annualized rent growth rate is approximately 12% to 16%, roughly in line with Microsoft's commercial cloud revenue historical growth rate; among the $169 billion procurement commitments, GPU servers account for only a portion and are concentrated within 12 months, with only $25 billion for fiscal 2028 and beyond. The report maintains Microsoft's "Outperform" rating, with the price target raised from $647 to $660 and the P/E multiple raised from 26.5x to 27x. Bernstein believes that data center designs support hybrid deployment of CPU and GPU, and if AI demand slows down, capacity can be shifted to traditional cloud business. AI accounts for approximately 16% to 17% of Microsoft's commercial cloud revenue, but since AI gross margin is approximately 27%, far lower than traditional cloud business, AI accounts for approximately 40% of commercial cloud cost of sales. Management stated at the Q4 earnings call that current demand still far exceeds available supply.