News linked to both this project and an event.
According to TechFlow Research, Morgan Stanley's August Q2 earnings report indicated that CoreWeave added 500MW of net active power in a single quarter, exceeding any quarter in history, more than three times year-over-year. Management reaffirmed the target of reaching at least 8GW before 2030. FY26 revenue guidance midpoint was raised 2% to $12.4 billion to $13.2 billion, ARR midpoint was raised 3% to $18.5 billion to $19.5 billion. The company raised full-year capital expenditure guidance midpoint by 12% to $35.5 billion to $39.0 billion, Q3 capital expenditure guidance is $11.5 billion to $13.5 billion, higher than the market expectation of $10 billion. Managed Inference Platform (managed inference platform) ARR grew from $1 million to over $100 million, expected to reach at least $250 million by year-end. The research report judges that Q2 adjusted operating margin was about 8%, higher than expected, but Q3 margin guidance of 5.8% to 7.2% is lower than market expectations, Q4 margin needs to increase significantly to achieve full-year guidance. Morgan Stanley expects CoreWeave FY27 operating margin to be 15.9%, FY28 to be 22.4%, free cash flow to remain negative until 2028, and debt is expected to increase to approximately $38 billion by the end of 2026. Morgan Stanley maintains Equal-weight (in line with the market) rating and $99 price target.
: 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.
According to Reuters, Chinese AI startup DeepSeek is developing its own AI chips, three informed sources revealed. The chip is designed specifically for inference scenarios, rather than for model training. The project was launched approximately one year ago and remains in the early stages. The company has engaged with chip design, wafer foundry, and storage enterprises, and has quietly increased recruitment of chip design engineers without publicly posting job listings. If successfully developed, DeepSeek will reduce its reliance on Nvidia and Huawei Ascend chips, following the trend of global AI giants such as OpenAI and Anthropic developing their own hardware. Affected by U.S. export controls, DeepSeek previously shifted from Nvidia H800 to Huawei chips. This self-developed chip is regarded as a significant strategic transformation. Meanwhile, DeepSeek also plans to complete its first round of external financing, with a fundraising scale of approximately $7 billion, and a valuation reaching $52 billion to $59 billion.