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Project Overview
The GPU Network is a decentralized graphics processing unit on demand infrastructure that powers the next generation of Generative AI, Web3 Metaverses, High-end graphics rendering and cryptocurrency mining. GPU.Net is on a mission to create a distributed network of GPUs that would empower an efficient, accessible and cost efficient GPU resource sharing ecosystem. GPU.Net would foster advanced computations such as Training AI/ML Language models, Complex gaming, Scientific computing etc on a large scale.
JPMorgan: Tech Valuations Fully Contracted, Semiconductors Outperform Software
According to Trend Research, a JPMorgan research report dated September 28, 2026 notes that the technology and AI ecosystem stagnated for three months from June through last week, though valuation downgrades have already become highly pronounced across most sectors. Forward earnings for semiconductors continue to climb by approximately 30%, while software has seen almost no earnings upgrades. Valuations for the Tech Seven Giants have fallen to ten-year lows, trading at nearly one standard deviation below the broader market. Capital expenditures by hyperscalers are projected to grow at a 28% compound annual growth rate through 2030. JPMorgan argues that with cleaner positioning, persistent earnings momentum, and an intact capital expenditure upcycle, it advises re-entering the technology sector and reopening a semiconductor-over-software pair trade. Agentic AI is pushing the CPU-to-GPU ratio from 1:4 to 1:8 toward 1:1, providing tailwinds for CPU-related names.
Aave Founder: Solar Energy, GPUs, Robots and Other Assets Will Be Added to Lending Landscape in the Future
Odaily reports: Aave founder and CEO Stani posted on X platform that his way of measuring Aave's potential market size is "addressable collateral" — the broader the range of assets that can serve as collateral, the greater the lending market space becomes.Stani stated that Aave initially started with crypto assets, then expanded into securities through Coinbase Tokenized Stocks and Horizon RWA, and in the future will also cover assets such as solar energy, batteries, GPUs, robots, and space infrastructure. He expressed his belief that this transformation will continue through 2050, and that Aave's goal is to accelerate this process by approximately 10 years by providing financing for the assets that will drive the "Age of Abundance."
USD.AI Announces Completion of $128.9 Million in GPU Funding
According to PR Newswire, USD.AI, a stablecoin protocol facilitating AI lending, has announced a $128.9 million asset-backed GPU financing deal for an undisclosed borrower, marking the largest single loan to date on the platform. The funds will be used to deploy 32 Nvidia GB200 NVL72 systems in British Columbia, Canada. The operator is a publicly listed GPU cloud provider, and the equipment is secured under a multi-year agreement with an investment-grade counterparty. This financing surpasses the $98.1 million GPU financing project announced by USD.AI in June 2026.
USD.AI Secures $129 Million GPU Financing Facility
Odaily — The financing will be used to support an undisclosed borrower in deploying 32 NVIDIA GB200 NVL72 systems in British Columbia, Canada. USD.AI is an on-chain lending protocol.
Samsung Leads $231 Million Series A Funding Round for Dutch AI Chip Startup Euclyd
According to TechStartups.com, Dutch AI chip startup Euclyd has completed an over €200 million (approximately $231 million) Series A funding round, co-led by Samsung, Somerset Capital Partners, EQT’s Scaleup Europe Fund, and Innovation Industries. Founded in 2024 by Bernardo Kastrup and Atul Sinha, Euclyd is headquartered in Eindhoven and focuses on AI inference, aiming to replace GPU solutions with proprietary chips and memory architectures to reduce energy consumption for AI inference and lower cost per token. Former ASML CEO Peter Wennink will serve as the company's board chairman.
Biren Technology is considering a new round of stock sales to raise approximately $1 billion.
According to Bloomberg, Shanghai-based Biren Technology is considering a new round of equity sales to raise approximately $1 billion to support the expansion of its artificial intelligence business. As one of the GPU chip developers heavily backed by Beijing, the company has banks in preliminary stages, currently sounding out potential investors for interest.
Suspected Drug Cartel Cryptocurrency Mining Farm Discovered in Mexican Mountains, Possibly Used for Money Laundering Through Mining
According to Reuters, Mexican police discovered a clandestine cryptocurrency mining operation in the mountainous regions of Puebla state, seizing 300 GPUs, 80 medium-voltage power terminals, and eight satellite dishes. Four similar operations have been uncovered in the area since early last year. Authorities are investigating whether the site illicitly siphoned electricity from a nearby hydroelectric plant. Security analysts noted that the technical expertise and funding required for the facility point to the involvement of well-capitalized criminal syndicates. A Chainalysis Latin America expert stated that regional drug trafficking organizations are increasingly utilizing cryptocurrency transfers and mining operations for money laundering. Data shows that globally, crypto addresses associated with criminal activity received approximately $154 billion in 2025, more than double the $59 billion recorded in the previous year.
AMD middle managers accused of diverting multiple engineers to ATOM inference engine project with almost no customers
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.
Silicon Data Secures $30.5 Million Series A Funding, Led by Valor Atreides AI Fund
Odaily News: GPU market data infrastructure company Silicon Data has announced the first closing of its $30.5 million Series A funding round, led by Valor Atreides AI Fund, with participation from CME Ventures, DRW, Samsung Next, VanEck, Jump Trading, Wintermute, and others. The funds will be used for GPU benchmark pricing, performance measurement, institutional and alternative data, as well as risk infrastructure for derivatives, insurance, and credit markets.Silicon Data currently collects data from approximately 100 GPU rental platforms across more than 40 countries worldwide, processing over 150,000 verified price records daily. CME Group plans to adopt Silicon Data's benchmarks as the reference price for its proposed cash-settled GPU futures contracts, pending regulatory approval.
South Korean Public Institution Employee Fired for Unauthorized Mining, Court Dismisses Wrongful Dismissal Lawsuit
According to Yonhap News Agency, a former department head surnamed A at the Korea Food Research Institute filed an administrative lawsuit after being fired for privately mining cryptocurrency in the institution's warehouse, but was ruled to have lost the case by the Seoul Administrative Court on the 3rd of last month. According to the investigation, between February and September 2023, A unauthorizedly installed 2 GPU servers in the idle Promotion Hall warehouse of the institute and used institutional budget to complete air conditioning, network, and electrical renovation projects, cumulatively illegally mining approximately 71 million altcoins. After the incident was discovered, A also forged approval documents attempting to retrieve the GPU servers to destroy evidence. In addition, between August 2023 and May 2024, A used an unauthorized VPN to clock in in violation of regulations a total of 117 times, indirectly causing important scientific research data of the institute to be illegally leaked. The Audit Committee of the National Research Council for Science & Technology launched a special audit on A in 2024, subsequently reported to the police, and requested the institute to impose a dismissal penalty. After A's internal appeals and relief applications to the Local Labor Relations Commission and the Central Labor Relations Commission were all rejected, A resorted to the administrative court, but still ended in defeat. The court ruled that the dismissal "did not involve any circumstances clearly violating social common sense or abuse of discretion." In the criminal case, A was charged with crimes such as theft, violation of the Information and Communications Network Act, and forgery of private documents, sentenced to 1 year in prison in the first instance, and the second instance upheld the original verdict in April this year, formally finalizing the sentence.
"Unease and anticipation are just two sides of the same coin": SK Hynix stock pulls back but remains favored by institutions, market focuses on HBM4 technology moat
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)
Western Digital: AI Storage Competition Is Not "Flash vs. HDD", Economic Scalability Is the Key
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
Upbit 将上线 Dolphin（POD），支持韩元、BTC 及 USDT 交易对
据 Upbit 公告，Upbit 将上线 Dolphin（POD），支持 KRW、BTC 和 USDT 三个交易市场，预计于北京时间今日 15:00 开放交易。POD 仅支持通过 Base 网络充值和提现，充提服务将在公告发布后 2 小时内开放。 Dolphin 是一个 AI DePIN 项目，通过整合全球闲置 GPU 资源分布式处理 AI 推理任务，并提供 Web Chat、Telegram Bot 等产品。POD 代币主要用于网络质押及 Bonding。
Goldman Sachs Expects Nvidia Revenue to Grow 70% by Fiscal 2028, AI Chip Demand Remains Strong
Odaily News: Goldman Sachs analyst Jim Schneider stated that Nvidia's revenue growth prospects remain strong over the next few years, with the company's fiscal 2028 revenue expected to increase approximately 70% from current levels.Earlier, Nvidia reported better-than-expected fiscal second-quarter results and provided revenue guidance above market expectations, driving its stock price up approximately 4%. The market is closely watching Nvidia's continued ability to benefit from AI infrastructure development.Jim Schneider said in an interview with CNBC that Nvidia's strong performance and future growth expectations are primarily driven by sustained enterprise investment in AI computing demand and the expansion of its data center business.As the generative AI boom continues, Nvidia's GPUs, AI servers, and related ecosystem remain a key focus in the capital markets, with investors continuously assessing its long-term growth potential. (CNBC)
Nvidia Earnings Preview: Q2 Revenue Expected to Nearly Double to $92.17 Billion, Market Focus on AI Chip Demand and Supply Chain Pressures
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)
SK Hynix's Optical Interconnect Memory Roadmap: Connecting Larger Shared Memory Pools via Localized HBM
Odaily News, Citrini analyst jukan stated on the X platform that at first glance, SK Hynix's CPO technology roadmap appears to have one axis pointing toward HBM and another toward optical communication. However, the underlying logic is that AI competition is shifting from individual chip performance to data transfer efficiency across the entire system.Over the past few years, HBM has addressed the problem of GPUs being unable to receive data fast enough. By vertically stacking multiple layers of DRAM and placing them next to the GPU, HBM delivers extremely high bandwidth. Yet, as more HBM stacks are placed around each GPU, packaging area, interposer edge space, power supply, and thermal dissipation capabilities are all approaching their limits. Meanwhile, AI clusters have expanded to thousands or even tens of thousands of GPUs. No matter how fast a single GPU computes, the entire system will still be constrained by the "bandwidth wall" if data cannot be efficiently transferred between GPUs and racks.SK Hynix's vision is to extend optical interconnect to memory. Low-latency, high-bandwidth local HBM will remain next to the GPU, while optical fibers connect it to a larger shared memory pool. This approach avoids limiting all memory capacity within a single GPU package and enables horizontal scaling at the rack level.From an investment perspective, this does not mean HBM will be replaced in the near term. What is more likely to emerge is a new memory hierarchy: frequently accessed data remains stored in local HBM, while larger-scale, less frequently accessed data is stored in optically interconnected memory pools, HBF, or SSDs.SK Hynix is repositioning its business, shifting from selling standardized memory chips to co-designing HBM, controllers, advanced packaging, and system-level memory architectures with customers. If this roadmap comes to fruition, SK Hynix could strengthen customer stickiness, increase product added value, and enhance its ability to secure long-term contracts. At the same time, the company may also more proactively address the potential impact of future memory disaggregation on traditional HBM business models.At the supply chain level, areas that may benefit in the long term include silicon photonics chips, optical engines, lasers, fiber coupling technology, and advanced 2.5D and 3D packaging.However, this concept is still in its very early stages and essentially remains just a roadmap. jukan noted that a person involved in TSMC's packaging business whom he interviewed today was completely unaware of this plan.
Citrini analyst questions SanDisk's HBF demonstration: Possible deliberate underestimation of HBM performance
Odaily News, Citrini analyst Zephyr posted on X platform questioning that SanDisk's HBF vs. HBM performance comparison at its Investor Day may contain parameter configuration bias, arguing that the company deliberately underestimated HBM performance in its demonstration.Zephyr pointed out that SanDisk set total bandwidth for both HBM and HBF at 12.8TB/s, while running the Qwen3-480B-A35B model with bfloat16. Current model inference more commonly uses FP4 or FP8, requiring approximately 240GB to 480GB of capacity.Zephyr also noted that SanDisk fixed HBM capacity at 192GB per GPU, but 16-layer HBM4E in an 8-stack configuration can reach 512GB capacity with approximately 32TB/s bandwidth—roughly three times the parameters used in SanDisk's demonstration. Zephyr believes these parameter choices result in the company's claim that "HBF requires only 1 to 4 GPUs, while HBM requires 8 GPUs" failing to adequately represent actual performance under higher-spec HBM configurations.
CoreWeave and Nebius Earnings Reveal AI Cloud Computing Trends: Supply Shortage Persists, CSPs Move Toward "AI Infrastructure Operating Systems"
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-
Starkware completes quantum-resistant transaction on Bitcoin mainnet without soft fork
: Blockchain technology company Starkware stated that on August 26, a transaction using researcher Avihu Levy's Quantum-Safe Bitcoin (QSB) scheme was mined on the Bitcoin mainnet, without requiring a soft fork, hard fork, or modification of consensus rules.The transaction consumed 10,000 sats and was processed through MARA Foundation's Slipstream service, as the non-standard format typically cannot propagate through Bitcoin's public mempool. The test consumed several hours of GPU computation, costing approximately $150 to $200.QSB employs hash-based quantum-resistant spending conditions and reduces quantum attack risks through signature trial mining, but still requires users to proactively migrate funds and cannot protect assets whose public keys have already been exposed. Starkware CEO Eli Ben-Sasson still supports introducing a protocol-level solution via a soft fork. (Bitcoin.com News)
Different COLDCARD Mk3 devices may generate the same mnemonic phrase, with approximately 4.5 million possible starting states searchable within 3 seconds
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.
Aethir Prevents Cross-Chain Bridge Vulnerability Attack and Promises Compensation
Decentralized GPU cloud computing infrastructure platform Aethir confirmed that its Ethereum-related bridge contract was attacked. The team promptly disconnected the affected contract and, in collaboration with major exchanges, blacklisted the hacker’s wallet, limiting losses to under $90,000. Earlier, blockchain security firm PeckShield estimated losses at $400,000. The attacker exploited Aethir’s cross-chain smart contract, AethirOFTAdapter, to transfer stolen funds from BNB Chain to Tron. Aethir stated that its Ethereum mainnet ATH token supply remains unaffected. It plans to release a detailed compensation plan and incident analysis next week and will collaborate with exchanges including Binance, Upbit, and Bithumb to freeze funds. Web3 security platform ZeroShadow is assisting with the investigation. In 2025, Aethir achieved $127.8 million in revenue and deployed over 440,000 GPU containers globally.
Upbit 将上线 Dolphin（POD），支持韩元、BTC 及 USDT 交易对
据 Upbit 公告，Upbit 将上线 Dolphin（POD），支持 KRW、BTC 和 USDT 三个交易市场，预计于北京时间今日 15:00 开放交易。POD 仅支持通过 Base 网络充值和提现，充提服务将在公告发布后 2 小时内开放。 Dolphin 是一个 AI DePIN 项目，通过整合全球闲置 GPU 资源分布式处理 AI 推理任务，并提供 Web Chat、Telegram Bot 等产品。POD 代币主要用于网络质押及 Bonding。
USD.AI Announces Completion of $128.9 Million in GPU Funding
According to PR Newswire, USD.AI, a stablecoin protocol facilitating AI lending, has announced a $128.9 million asset-backed GPU financing deal for an undisclosed borrower, marking the largest single loan to date on the platform. The funds will be used to deploy 32 Nvidia GB200 NVL72 systems in British Columbia, Canada. The operator is a publicly listed GPU cloud provider, and the equipment is secured under a multi-year agreement with an investment-grade counterparty. This financing surpasses the $98.1 million GPU financing project announced by USD.AI in June 2026.
USD.AI Secures $129 Million GPU Financing Facility
Odaily — The financing will be used to support an undisclosed borrower in deploying 32 NVIDIA GB200 NVL72 systems in British Columbia, Canada. USD.AI is an on-chain lending protocol.
CoinW has listed the AINVDA perpetual contract, supporting up to 25x leverage.
Global-leading digital asset exchange CoinW has launched perpetual contracts for the popular Meme token AINVDA, supporting up to 25x leverage. AINVDA is an animal-themed token focused on the convergence of artificial intelligence, NVIDIA, and on-chain culture. Featuring an Artificial Inu dog as its mascot, the project’s core narrative revolves around the growing demand for AI computing power, GPUs, and NVIDIA-related infrastructure. Risk Warning: Meme tokens are highly volatile, and contract trading may result in the loss of principal. Please participate rationally and bear all risks independently. CoinW has no affiliation whatsoever with any publicly traded companies mentioned herein. This service may not be available in certain jurisdictions.
Zhipu GLM Unveils Recursive Self-Improvement Practice, GLM-5.3-Flash Released
The Zhipu GLM team has disclosed its first engineering implementation of recursive self-improvement. An Infra Agent driven by GLM-5.3 completed the design, debugging, and optimization of the GLM-5.3-Flash inference infrastructure. The practice was executed on a domestic 100,000-GPU cluster, which the team describes as the first recursive self-improvement practice for large models in China.
Biren Technology is considering a new round of stock sales to raise approximately $1 billion.
According to Bloomberg, Shanghai-based Biren Technology is considering a new round of equity sales to raise approximately $1 billion to support the expansion of its artificial intelligence business. As one of the GPU chip developers heavily backed by Beijing, the company has banks in preliminary stages, currently sounding out potential investors for interest.
Related news
Upbit 将上线 Dolphin（POD），支持韩元、BTC 及 USDT 交易对
据 Upbit 公告，Upbit 将上线 Dolphin（POD），支持 KRW、BTC 和 USDT 三个交易市场，预计于北京时间今日 15:00 开放交易。POD 仅支持通过 Base 网络充值和提现，充提服务将在公告发布后 2 小时内开放。 Dolphin 是一个 AI DePIN 项目，通过整合全球闲置 GPU 资源分布式处理 AI 推理任务，并提供 Web Chat、Telegram Bot 等产品。POD 代币主要用于网络质押及 Bonding。
JPMorgan: Tech Valuations Fully Contracted, Semiconductors Outperform Software
According to Trend Research, a JPMorgan research report dated September 28, 2026 notes that the technology and AI ecosystem stagnated for three months from June through last week, though valuation downgrades have already become highly pronounced across most sectors. Forward earnings for semiconductors continue to climb by approximately 30%, while software has seen almost no earnings upgrades. Valuations for the Tech Seven Giants have fallen to ten-year lows, trading at nearly one standard deviation below the broader market. Capital expenditures by hyperscalers are projected to grow at a 28% compound annual growth rate through 2030. JPMorgan argues that with cleaner positioning, persistent earnings momentum, and an intact capital expenditure upcycle, it advises re-entering the technology sector and reopening a semiconductor-over-software pair trade. Agentic AI is pushing the CPU-to-GPU ratio from 1:4 to 1:8 toward 1:1, providing tailwinds for CPU-related names.
Google Adds Advanced Colab Benefits for Google AI Subscribers
Google has announced new premium Google Colab benefits for its Google AI subscription members. Eligible subscribers will receive Colab compute units and gain access to higher-performance cloud computing resources, such as GPUs and TPUs. Google Colab is a hosted Jupyter Notebook service that requires no installation, allowing users to directly write and run Python code.
Aave Founder: Solar Energy, GPUs, Robots and Other Assets Will Be Added to Lending Landscape in the Future
Odaily reports: Aave founder and CEO Stani posted on X platform that his way of measuring Aave's potential market size is "addressable collateral" — the broader the range of assets that can serve as collateral, the greater the lending market space becomes.Stani stated that Aave initially started with crypto assets, then expanded into securities through Coinbase Tokenized Stocks and Horizon RWA, and in the future will also cover assets such as solar energy, batteries, GPUs, robots, and space infrastructure. He expressed his belief that this transformation will continue through 2050, and that Aave's goal is to accelerate this process by approximately 10 years by providing financing for the assets that will drive the "Age of Abundance."
StarkWare: Quantum-Safe BTC Transaction Cost Estimates Can Drop to $66, Cutting Costs by Approximately 79%
According to CoinDesk, StarkWare stated that the estimated GPU computing cost required to prepare a quantum-secure Bitcoin transaction has decreased from approximately $320 to $66 (a cost reduction of about 79%). Previously, the relevant transaction was mined on the Bitcoin network in August. The preparation process utilized approximately 100 GPUs and accumulated around 3,100 hours of computing time. The $320 figure referred only to the pre-on-chain computing costs, excluding Bitcoin network fees.
USD.AI Announces Completion of $128.9 Million in GPU Funding
According to PR Newswire, USD.AI, a stablecoin protocol facilitating AI lending, has announced a $128.9 million asset-backed GPU financing deal for an undisclosed borrower, marking the largest single loan to date on the platform. The funds will be used to deploy 32 Nvidia GB200 NVL72 systems in British Columbia, Canada. The operator is a publicly listed GPU cloud provider, and the equipment is secured under a multi-year agreement with an investment-grade counterparty. This financing surpasses the $98.1 million GPU financing project announced by USD.AI in June 2026.