Crypto mining stock Cipher Mining Inc (NASDAQ:CIFR) is up 33% at $24.82, despite missing third-quarter earnings and revenue estimates, on news of a $5.5 billion, 15-year lease agreement with Amazon.com (AMZN). Cipher will provide space and power for AI workloads to Amazon Web Services (AWS), with the 300 megawatts of computing capacity to be delivered next year.Today's pop has CIFR trading at record highs after gapping past the $22 level, which rejected two October rallies. Up 314% in just the last three mo ...

Core Insights - Cango Inc. has established itself as a significant player in the Bitcoin mining industry, achieving a computing power of 50 EH/s by the end of Q2 2025, representing 6% of the global Bitcoin network [1][2] Financial Performance - For the three months ending June 30, 2025, Cango mined 1,404.4 Bitcoin at an average mining cost of $83,091 per Bitcoin, with all-in costs at $98,636, aligning with industry averages [2] - Revenue for Q2 2025 was reported at $139.8 million, with Bitcoin mining contributing $138.1 million; despite a loss due to one-off factors, adjusted EBITDA improved to $99.1 million [4] Strategic Transformation - The company underwent a strategic transformation over the past nine months, including a governance overhaul and a $352 million divestiture from operations in China, shifting to an "asset-light" operational model [3][4] - Cango's leadership restructuring has brought in a team with expertise in digital-asset infrastructure, finance, and energy investments, aimed at executing the next growth phase [5] Growth Initiatives - In August, Cango acquired a 50 MW mining site in Georgia, expected to reduce power costs and enhance operational stability [6] - The company is focused on maximizing the value from its 50 EH/s capacity and plans to implement efficiency upgrades while exploring renewable energy storage projects for near-zero-cost mining operations [7] Future Outlook - Cango aims to build a computing platform that balances Bitcoin mining and AI workloads, indicating a long-term vision for growth and diversification [7][8]

Key Points Oracle’s cloud investments are paying off big time. Oracle has set clear five-year expectations. If it delivers, it’s reasonable to assume the stock could more than double from here. 10 stocks we like better than Oracle › Oracle (NYSE: ORCL) surged a mind-numbing 36% on Wednesday to close the session at a market cap of $922 billion. Five years ago, Oracle's market cap was under $200 billion. Now, there's reason to believe it can surpass $2 trillion by 2030. If that prediction comes tru ...

AI Workload Challenges & Requirements - AI workloads differ from traditional cloud workloads due to the need for high throughput and low latency, especially in large language model training involving thousands of GPUs communicating with each other [2][3][4] - Network glitches like packet drops, congestion, or latency can slow down the entire training process, increasing training time and costs [3][5] - Networks must support small to large-sized clusters for both inference and training workloads, requiring high performance and reliability [8] - Networks should scale up within racks and scale out across data halls and data centers, while being autonomous and resilient with auto-recovery capabilities [9][10] - Networks need to support increasing East-West traffic, accommodating data transfer from various sources like on-premises data centers and other cloud locations, expected to scale 30% to 40% [10] OCI's Solution: Backend and Frontend Networks - OCI addresses AI workload requirements by implementing a two-part network architecture: a backend network for high-performance AI and a frontend network for data ingestion [11][12] - The backend network, designed for RDMA-intensive workloads, supports AI, HPC, Oracle databases, and recommendation engines [13] - The frontend network provides high-throughput and reliable connectivity within OCI and to external networks, facilitating data transfer from various locations [14] OCI's RDMA Network Performance & Technologies - OCI utilizes RDMA technology powered by RoCEv2, enabling high-performance, low-latency RDMA traffic on standard Ethernet hardware [18] - OCI's network supports multi-class RDMA workloads using Q-cure techniques in switches, accommodating different requirements for training, HPC, and databases on the same physical network [20] - Independent studies show OCI's RDMA network achieves near line-rate throughput (100 gig) with roundtrip delays under 10 microseconds for HPC workloads [23] - OCI testing demonstrates close to 96% of the line rate (400 gig throughput) with Mi300 clusters, showcasing efficient network utilization [25] Future Roadmap: Zeta-Scale Clusters with AMD - OCI is partnering with AMD to build a zeta-scale Mi300X cluster, powering over 131,000 GPUs, which is nearly triple the compute power and 50% higher memory bandwidth [26] - The Mi300X cluster will feature 288 gig HBM3 memory, enabling customers to train larger models and improve inferencing [26] - The new system will utilize AMD AI NICs, enabling innovative standards-based RoCE networking at peak performance [27]