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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.
AI Reasoning Startup General Compute Secures $400 Million Loan Backed by ASIC Chips for Inference
: AI reasoning cloud startup General Compute has obtained a $400 million loan from Upper90. This deal is the world’s first financing project to use dedicated inference chips as collateral. The company has built a proprietary AI reasoning cloud platform based on SambaNova’s self-developed ASIC chips, primarily targeting Agent-type AI computing workloads. Compared to traditional GPU clouds, it offers faster token processing speeds and lower operational latency. The hardware requires no water cooling and can be directly deployed in traditional data centers and idle cryptocurrency mining facilities.
Analysis: AI Investment Frenzy Cools Down, Market Reassesses Sustainability of Chip and Data Center Spending
the boom in AI infrastructure investment is cooling, and the market has begun to reassess the sustainability of spending on chips and data centers. As investors re-evaluate whether investment in AI infrastructure can be sustained, the "AI trade," which encompasses the semiconductor, memory chip, and data center industry chain, is showing signs of slowdown.Recently, AI-related chip stocks such as Micron Technology (MU) and SanDisk (SNDK) have come under pressure. Meanwhile, Samsung Electronics reported record-breaking second-quarter results, but its revenue fell short of market expectations. Its stock price still fell nearly 7%, dragging the entire AI chip sector lower.Market concerns are growing that as major cloud computing providers (Hyperscalers) may slow down their AI infrastructure investments, the current AI boom cycle, driven by GPUs, High Bandwidth Memory (HBM), and data center construction, could face a repricing. Concurrently, South Korean memory chip giant SK hynix's stock price has fallen about 25% from its all-time high ahead of its US listing, and its IPO is also attracting some funds away from existing chip stocks.Analysts point out that after SpaceX's massive IPO inflated valuations of AI-related assets, investors are reassessing the growth logic for the next phase of the AI rally. If the intensity of AI investment declines further, some capital might flow back from the AI industry chain to other risk assets, including crypto assets. (CoinDesk)
AI Chip Startup Oxmiq Completes $35 Million Funding, Led by Samsung Catalyst Fund and Fudomo
According to Reuters, AI chip startup Oxmiq announced the completion of a new $35 million funding round, led by Samsung Catalyst Fund and Fudomo, with participation from Taiwan's MediaTek and Pegatron Venture Capital, bringing the company's total funding to $60 million. Oxmiq was founded by former Intel Chief Architect Raja Koduri and is headquartered in Campbell, California. The company plans to integrate GPU, CPU, and tensor engine components into a single IP module for licensing, and develop an integrated computing architecture including Chiplets and memory, while positioning itself in the custom chip market to compete with Broadcom, Marvell, and MediaTek. Koduri stated that Oxmiq's goal is to become the "ARM of the next era." The funds will be used to complete the development of the first batch of IPs and bring them to market, while expanding the engineering team.
South Korean listed company K Wave Media liquidates 88 BTC, exits the Bitcoin treasury company ranks
According to BitcoinTreasuries data, South Korean listed company K Wave Media (KWM) has sold all of its remaining 88 BTC to repay $6 million in debt. Following the sale, the company's Bitcoin holdings have dropped to zero, exiting the ranks of Bitcoin treasury companies.K Wave Media announced last year that it had secured a $1 billion Bitcoin treasury financing capacity and planned to expand its Bitcoin holdings to 10,000 BTC as soon as possible. However, in May this year, the company redirected up to $485 million of its remaining financing capacity from the Bitcoin treasury strategy to AI infrastructure construction, including data centers, GPU computing power, and related acquisitions.
Venice AI completes $65 million Series A funding round, led by Dragonfly
Venice AI has announced the completion of a $65 million Series A funding round, led by Dragonfly, with participation from Coinbase Ventures, North Island Ventures, and others, at a valuation of $1 billion. The project primarily offers a platform that grants access to over 200 AI models while ensuring privacy.
Goldman Sachs Bullish on AI Infrastructure, June Trading Near $7 Billion, SMCI Order Backlog $39 Billion
According to TechFlow Research, Goldman Sachs' June 30 AI Project Pulse Monthly Report shows that 7 major transactions tracked in June totaled nearly $7 billion. Argentum AI signed a $4.1 billion contract to deploy 27,000 GB300 GPUs for a leading AI company, supported by a 300MW Poland data center, going online in phases in 2026; India's Yotta Sovereign Cloud procured $2 billion worth of 20,736 B300s and 5,120 B200s, subsequently expanding to six Southeast Asian countries. Crypto mining farm AiOnX acquired 77% equity of Genesis Digital Assets for $500 million, converting 1.3GW of power from 15 mining farms to AI computing power. CoreWeave and Dell built the world's first fully validated Vera Rubin NVL72 rack, with 72 Rubin GPUs plus 36 Vera CPUs; NVDA confirmed mass production in the second half of 2026. SMCI raised $7 billion to address approximately $39 billion in backlog orders, covering more than 20 clients, with funds used to lock in upstream components in advance. Goldman Sachs simultaneously raised its global server market size forecast.
Core Scientific Pays $41.9 Million to Terminate Block Bitcoin Mining Contract, Shifts Focus to AI Infrastructure
data center operator Core Scientific disclosed in its second-quarter regulatory filing that it paid $41.9 million to terminate the Bitcoin mining machine contract with Block and its Proto division, with related losses amounting to $41.9 million. Both the agreement and future equipment deliveries have been canceled. The agreement, announced in July 2024, originally called for Proto to supply 3nm mining chips, corresponding to approximately 15 EH/s in hashrate, and included options for additional purchases. Core Scientific stated that it will no longer invest in new mining machines to maintain or expand hashrate, will generate cash flow from existing mining machines, and will sell or retire machines as appropriate. Core Scientific's second-quarter hosting revenue increased from $10.6 million in the same period last year to $137 million, accounting for 83% of total revenue; self-mining revenue fell 66% year-over-year to $21.5 million, representing 13% of total revenue. The company stated that quarterly Bitcoin production decreased by 53% year-over-year, and it continues to shift power from mining equipment to high-density computing systems such as GPUs.
Microsoft Expands AI Partnership with Mistral, Signs Multi-Billion Dollar European AI Infrastructure Agreement
Odaily, July 21 - Microsoft and French AI startup Mistral AI announced an expansion of their strategic partnership on July 21, signing a multi-billion dollar agreement centered on European AI infrastructure to enhance AI computing capabilities in the region. Under the agreement, Microsoft will leverage Mistral's expanded European GPU infrastructure to support its cloud computing and AI services. This infrastructure will be based on thousands of Nvidia Vera Rubin GPUs.In terms of products, the Mistral Medium 3.5 and OCR 4 models are now available on the Microsoft Foundry platform, and Mistral Medium 3.5 has also been integrated into Microsoft Copilot Studio for agent applications, document processing workflows, and industry-customized workflows. Additionally, the two parties will expand AI deployment options through Azure and Azure Local, supporting cloud, cloud-connected, and fully offline environments, targeting industries with high data compliance requirements such as finance, healthcare, and manufacturing.
Bernstein: Crypto-style derivatives have already entered the AI compute market, while CME and ICE futures still await approval.
According to The Block, Bernstein stated that before the compliant computing power futures planned by CME Group and Intercontinental Exchange are approved, AI computing power derivatives adopting crypto market mechanisms have already launched. Currently, Architect's offshore trading platform AX has launched GPU perpetual futures, while Kalshi has listed GPU rental price event contracts regulated by the U.S. Commodity Futures Trading Commission.
Nansen CEO: AI infrastructure may be repriced, bubble could burst after enterprises adopt Chinese models
Odaily News Alex Svanevik, CEO of on-chain analytics platform Nansen, stated that when enterprises begin effectively using Chinese large language models, the bubble in the AI industry may burst. While the U.S. regulatory environment could limit this process, the overall trend remains that Chinese models are continuously becoming more efficient, capable of running on non-cutting-edge hardware, while global GPU supply (including non-Nvidia chips) is increasing.Alex Svanevik also pointed out that the recent decline in H100 and H200 GPU rental prices reflects a shift in the supply-demand structure of computing power. He raised the question of how to interpret the market signal of declining GPU rental prices. As model efficiency improves alongside expanding computing power supply, the AI infrastructure market may be entering a phase of repricing.
Sources: NVIDIA plans to pitch Vera AI CPU to Chinese clients, some cloud providers eyeing test deployment
sources say NVIDIA has begun pitching its first independent central processing unit (CPU) product, Vera, to Chinese clients. Designed specifically for Agentic AI systems, the chip has entered mass production, marking NVIDIA's attempt to further expand its presence in the Chinese market with a CPU offering.According to sources, some Chinese clients have already shown interest in Vera. One major Chinese cloud computing company plans to procure over 300 servers equipped with dual Vera CPUs for testing, and will decide whether to expand procurement after the tests are completed.Built on the Arm Holdings architecture, Vera is NVIDIA's first independent CPU product. NVIDIA has previously stated that Vera's performance in AI agent-related computing tasks is 1.8 times that of comparable competitor products, and expects the product to contribute approximately $20 billion in revenue by the end of this fiscal year (ending January next year).The report notes that as the AI industry's focus gradually shifts from model training to inference computing, CPUs and custom chips are gaining more attention. Vera also positions NVIDIA to directly compete with Intel and Advanced Micro Devices (AMD), which have long dominated the server CPU market.Sources indicate that due to strict U.S. export restrictions on high-end GPUs, CPUs face relatively smaller regulatory hurdles in the Chinese market compared to GPU products. Currently, some Chinese clients plan to first deploy Vera chips for testing in overseas data centers. Meanwhile, software ecosystem compatibility and existing domestic AI chip deployment frameworks may still impact the subsequent large-scale adoption of Vera. (Reuters)
Alpha Compute Acquires Majority Stake in GAMEE for Approximately $11 Million
Nasdaq-listed Alpha Compute has announced the completion of its acquisition of a majority stake in GAMEE, a gaming and digital rewards platform, securing a 60% controlling interest. The transaction has now met all regulatory and closing conditions.According to the agreement, Alpha Compute acquired GAMEE from Animoca Brands for a consideration of approximately $11 million, implying an enterprise valuation of roughly $18 million. The transaction structure includes cash, stock, and future performance-based earnouts, along with an EBITDA milestone incentive clause over two years. Additionally, approximately 878 million GMEE tokens associated with Animoca are also included in the transaction arrangement.Following the transaction, Alpha Compute will establish a new AI gaming division named Alpha Games, with GAMEE founder Bozena Rezab serving as Executive Vice President. GAMEE will be integrated into Alpha Compute's AI infrastructure system, working in synergy with its GPU computing platform.
Analyst: Kimi K3 Ultra-large Model to Be Open-Sourced Soon, AI Infrastructure Platforms May Be the Biggest Beneficiaries
analyst KawzInvests stated that Moonshot AI's upcoming Kimi K3 could become a significant event in the open-source AI space, and the infrastructure demand behind it may drive growth for AI cloud service platforms. Kimi K3 has approximately 2.8 trillion parameters, making it one of the ultra-large-scale open-source models. According to Moonshot's official evaluation, the model's performance is only slightly behind frontier models like Claude Fable 5 and GPT 5.6 Sol, and the full model weights are expected to be released on July 27.KawzInvests pointed out that a model of this scale cannot run on an ordinary laptop or even a single server; users need a computing cluster composed of a large number of GPUs to complete model loading and inference. When top-tier open-source models are made available for free, the biggest beneficiaries might not be ordinary users, but rather platforms that offer model hosting and inference services. For example, $DOCN (DigitalOcean) already supports serverless inference services for models like Kimi K2.6. Developers do not need to deploy hardware; they can call the model via API and pay per Token. Additionally, the platform hosts over 70 models and covers GPU leasing, model fine-tuning, and AI Agent development tools.As more large-scale open-source models are released, developers' demand for low-barrier AI infrastructure will continue to increase. Model hosting, inference services, and GPU cloud platforms may become key beneficiaries in the open-source AI wave.
South Korean listed company K Wave Media liquidates 88 BTC, exits the Bitcoin treasury company ranks
According to BitcoinTreasuries data, South Korean listed company K Wave Media (KWM) has sold all of its remaining 88 BTC to repay $6 million in debt. Following the sale, the company's Bitcoin holdings have dropped to zero, exiting the ranks of Bitcoin treasury companies.K Wave Media announced last year that it had secured a $1 billion Bitcoin treasury financing capacity and planned to expand its Bitcoin holdings to 10,000 BTC as soon as possible. However, in May this year, the company redirected up to $485 million of its remaining financing capacity from the Bitcoin treasury strategy to AI infrastructure construction, including data centers, GPU computing power, and related acquisitions.
Micron (MU) is More Important Than Nvidia! Citrini Analyst States AI Model Inference Performance Depends More on Memory Than GPU
: In response to the community debate over "Micron VS Nvidia," Jukan, an analyst at Citrini Research, posted on platform X, stating, "MU (Micron) may not be Nvidia, but its future importance could surpass Nvidia. Inference is now directly tied to revenue, but improvements in inference performance cannot be achieved simply by adding more Nvidia GPUs. In inference, GPUs are often underutilized and idle due to memory bottlenecks. For inference, increasing memory provides higher value. The return on investment for inference ultimately depends on memory, not GPU. Therefore, why are people still fixated on obtaining Micron through Nvidia's framework? One must think more comprehensively. Inference is memory."
Nansen CEO: AI infrastructure may be repriced, bubble could burst after enterprises adopt Chinese models
Odaily News Alex Svanevik, CEO of on-chain analytics platform Nansen, stated that when enterprises begin effectively using Chinese large language models, the bubble in the AI industry may burst. While the U.S. regulatory environment could limit this process, the overall trend remains that Chinese models are continuously becoming more efficient, capable of running on non-cutting-edge hardware, while global GPU supply (including non-Nvidia chips) is increasing.Alex Svanevik also pointed out that the recent decline in H100 and H200 GPU rental prices reflects a shift in the supply-demand structure of computing power. He raised the question of how to interpret the market signal of declining GPU rental prices. As model efficiency improves alongside expanding computing power supply, the AI infrastructure market may be entering a phase of repricing.
Goldman Sachs and JPMorgan Explore "Computing Power Financialization," Plan to Launch GPU Rental Futures to Hedge AI Risks
sources familiar with the matter have revealed that Goldman Sachs and JPMorgan are exploring trading methods based on the cost of computing power, including futures contracts linked to GPU rental prices. As one of the scarcest resources amid the AI boom, related futures for GPUs are expected to be listed on exchanges later this year.Industry insiders stated that this move reflects how the influx of hundreds of billions of dollars into data centers and the chip sector is reshaping the financial market landscape. For banks financing the construction of AI infrastructure, such innovative instruments could become a new means of risk management. (The Information)
“New Stock God” Serenity: Stock Price Rises Don’t Necessarily Create Value; Avoid Companies with “Toxic” Financing Structures or Crushing Debt
"New Stock God" Serenity posted on X platform, reminding investors to pay attention to financing structures and the dynamics of outstanding shares, as these are crucial for investment returns, and provided examples:IREN: The financing method approaches infinite dilution, with each rebound met by selling pressure—essentially a "bad stock."NBIS: Up 153% year-to-date, thanks to an optimized financing structure (such as direct offerings, convertible bond combinations, etc.).CRWV: High debt interest; the company uses usurious loans for GPU financing, which erodes free cash flow over the long term.Serenity pointed out that if a company has strong fundamentals, one could consider going long after the original shareholding has been diluted to near zero. However, for equity value appreciation, one should stay away from companies with "toxic" financing structures or crushing debt. The risk is especially high for small-cap companies, such as $SLNH adding a $500 million ATM while its market cap is only $250 million; $BKKT continuously diluting stock for executive compensation. Essentially, these companies are transferring investor funds to the enterprise, masked by media hype or influencer promotion.Serenity emphasized that investors must carefully analyze equity structure, dilution risk, and hidden costs when screening targets, to avoid focusing solely on profits while seeing their actual equity shrink.
HIVE fiscal year revenue up 158% to $298 million, AI GPU hourly revenue approximately 24 times that of mining equipment
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.
Morgan Stanley: AI Infrastructure ROIC Can Reach Up to 46%, Maintains Overweight Rating on Hyperscalers
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".
韩国国家 AI 计算中心 8月 3 日正式开工，三星 SDS 联合体主导建设
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 Secures $1.5 Billion AI Infrastructure Customer Contract, Bringing Total Contract Value Signed in 2026 to Over $3 Billion
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.
Anthropic technical staff member satirizes tech giants embracing open source: Looking forward to Microsoft open-sourcing Windows, Nvidia open-sourcing CUDA
: Julian Schrittwieser, a technical staff member at Anthropic, recently posted on social media, joking about the shift in attitude some tech giants have shown towards "open source" in recent years. He expressed anticipation for Nvidia and Microsoft to further open up their core technologies, stating: "It's great to see Jensen Huang become a supporter of open source. Looking forward to the open-source release of CUDA and GPU drivers. Also looking forward to Satya Nadella supporting open source, hoping to see Windows and Microsoft Office open-sourced in the future."Julian Schrittwieser also responded to external speculations that he opposes open weight models, indicating that this interpretation is inaccurate. He believes that open models can actually play an important role in many scenarios. However, Schrittwieser pointed out that what is interesting is that some companies, which have long been very cautious or even opposed to open source in the past, are now rapidly shifting towards supporting open ecosystems.In recent years, with the intensification of competition in artificial intelligence, open-source models, open weights, and developer ecosystems have become critical areas of competition in the tech industry. Companies including Nvidia and Microsoft have continuously emphasized their support for open ecosystems. However, the definition of "open" remains controversial within the industry—some companies open up model interfaces, toolchains, or ecosystems, while their core commercial assets remain closed source.Julian Schrittwieser's remarks have also sparked discussion, focusing on whether the "selective open sourcing" promoted by tech giants represents genuine openness or a new ecological competitive strategy.
Axe Compute Signs Over $1.3 Billion AI Infrastructure Contract, ARR Expected to Exceed $384 Million After Deployment
Axe Compute (NASDAQ: AGPU) announced that the company has signed new customer contracts totaling over $1.3 billion in the United States and Europe, exceeding the full-year 2026 signing target of $1 billion ahead of schedule. The relevant contracts were secured through the Axe Compute Build program, under which the company will design, deploy, hold, and operate dedicated AI infrastructure for customers, who can independently select GPU types, deployment regions, and infrastructure configurations.
Related news
HIVE fiscal year revenue up 158% to $298 million, AI GPU hourly revenue approximately 24 times that of mining equipment
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.
Polymarket odds of "AI bubble bursting within the year" drop to 19%, down 5% in 24 hours
Monitoring from the PPP Prediction Market Tool shows that on Polymarket, the probability of the "AI bubble bursting within the year" has dropped to 19%, a 5% decrease in 24 hours.According to the resolution rules, the market will only resolve to "Yes" if the AI industry experiences at least three major negative events within a specified period, all occurring within the same 90-day window. Trigger conditions include: Nvidia (NVDA) stock falling 50% from its all-time high, the SOXX semiconductor ETF falling 40% from its all-time high, OpenAI or Anthropic filing for bankruptcy, OpenAI being acquired, H100 GPU rental prices dropping below $1 for five consecutive days, and major AI hardware suppliers such as TSMC, ASML, Broadcom, Arista Networks, or Super Micro Computer seeing their stocks fall 50% from all-time highs.Previously reported, the fund Situational Awareness, managed by AI stock guru Leopold Aschenbrenner, sold off its entire public stock portfolio due to liquidity pressure, with Citadel as the buyer. However, the market believes this forced liquidation could accelerate the deleveraging of AI trades and serve as a signal for some investors that short-term risks in the AI sector have been released, potentially stabilizing the market.Join the PPP Signal Push Community to stay ahead and seize opportunities.
Dragonfly Partner: The current AI boom may not have emerged without the development of the crypto industry
Dragonfly Partner Haseeb posted on X platform, stating that the current AI boom might not have occurred without the development of the crypto industry. He noted that over the past decade, Bitcoin miners accumulated expertise in power acquisition, site selection, and large-scale infrastructure construction in remote areas, which has laid an important foundation for the expansion of AI data centers today. Additionally, the demand for crypto mining helped NVIDIA transition from a gaming GPU manufacturer to a supplier of AI computing chips.Furthermore, the core teams of several emerging AI cloud service providers, including CoreWeave, Crusoe, Together AI, and Nscale, all have backgrounds in the crypto industry.
Core Scientific Pays $41.9 Million to Terminate Block Bitcoin Mining Contract, Shifts Focus to AI Infrastructure
data center operator Core Scientific disclosed in its second-quarter regulatory filing that it paid $41.9 million to terminate the Bitcoin mining machine contract with Block and its Proto division, with related losses amounting to $41.9 million. Both the agreement and future equipment deliveries have been canceled. The agreement, announced in July 2024, originally called for Proto to supply 3nm mining chips, corresponding to approximately 15 EH/s in hashrate, and included options for additional purchases. Core Scientific stated that it will no longer invest in new mining machines to maintain or expand hashrate, will generate cash flow from existing mining machines, and will sell or retire machines as appropriate. Core Scientific's second-quarter hosting revenue increased from $10.6 million in the same period last year to $137 million, accounting for 83% of total revenue; self-mining revenue fell 66% year-over-year to $21.5 million, representing 13% of total revenue. The company stated that quarterly Bitcoin production decreased by 53% year-over-year, and it continues to shift power from mining equipment to high-density computing systems such as GPUs.
Former OpenAI Researcher's AI Fund Situational Awareness Seeks New Capital Injection After Market Crash
According to the UK Financial Times, Situational Awareness, an AI-themed hedge fund founded by 25-year-old former OpenAI researcher Leopold Aschenbrenner, is seeking new capital injections following significant losses caused by a sharp pullback in AI-related stocks. In recent communications, Aschenbrenner acknowledged heightened market volatility while describing it as a new investment opportunity, encouraging investors to commit new capital before August 1. The fund's heavily weighted positions in AI data centers, power, storage, and GPU cloud-related assets declined significantly during this retreat in AI capital expenditure trades.
Morgan Stanley: AI Infrastructure ROIC Can Reach Up to 46%, Maintains Overweight Rating on Hyperscalers
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".