nvidia

Reuters reported that Anthropic plans to raise $100 billion to set an IPO record, with a valuation potentially reaching $2 trillion. Nvidia is considering participating in a $10 billion investment.

According to sources, Anthropic is in talks to bring in NVIDIA as its anchor investor for its IPO, which is expected to be the largest in history.It is reported that NVIDIA is considering investing up to $10 billion in this IPO.

NVIDIA co-founder and CEO Jensen Huang stated on Thursday at the Goldman Sachs Technology Conference in San Francisco that cybersecurity is likely to become the next major use case for artificial intelligence.Huang mentioned that cybersecurity is the next big market for artificial intelligence, and advancements in this technology will disrupt an industry aimed at protecting computer systems.

On September 11, it was reported that the Nvidia Grace Blackwell platform's shipment volume recently increased by 27% month-over-month, reflecting the strong demand from cloud service providers and AI infrastructure companies for high-end AI computing chips. Nvidia had previously stated that the demand for Blackwell products exceeds its supply capacity.

NVIDIA CEO Jensen Huang responded to external doubts regarding its involvement in financing arrangements for data center and AI infrastructure projects at the Goldman Sachs conference. Huang stated that these investments are a "very smart strategy" aimed at promoting the market application of NVIDIA's technology architecture, rather than just a simple capital cycle.

Piper Sandler initiated coverage on Intel with a neutral rating and a target price of $110; gave Qualcomm a neutral rating with a target price of $190; and assigned an overweight rating to NVIDIA with a target price of $300.

Cisco announced a collaboration with Palantir and NVIDIA to establish a secure artificial intelligence factory to streamline the deployment of artificial intelligence.

NVIDIA collaborates with Palantir to bring sovereign artificial intelligence into the supply chain.

Rackspace announced its participation in the NVIDIA Cloud Partner Program and launched NVIDIA Blackwell-based AI infrastructure for regulated enterprises and governments.

According to industry news, NVIDIA is considering adjusting the high bandwidth memory solution for the next-generation Rubin Ultra artificial intelligence accelerator from a 12-layer stack to an 8-layer stack.Against the backdrop of rising storage costs, NVIDIA is placing greater emphasis on unit bandwidth costs and overall system economics.

The supply chain reports that the capacity for high-end testing interfaces for AI chips is tight. NVIDIA has significantly raised prices to secure the capacity of mainstream testing interface vendors' probe cards and test sockets, causing some R&D and engineering validation demands to be squeezed out.Including wafer foundry TSMC and chip manufacturers, multiple supplier validations have been initiated to cope with the supply pressure after capacity has been locked.

The research institution Sage Road Research released an executive summary of "The AI Trade," stating that since the beginning of this year, the Magnificent Seven has underperformed the Russell 3000 index by about 8 percentage points and the MSCI ACWI by nearly 9 percentage points. In July, the CBOE NDX volatility index relative to the VIX reached its highest point since the internet bubble, and after entering a correction, the Nasdaq index saw a 5% rebound over four days. As of the writing of the report, AI company stock prices have dropped 20% from their 52-week highs in June.Companies are struggling to achieve returns on investment amid soaring AI costs, with Uber, Amazon, Meta, and Walmart implementing restrictions on employee AI usage. Model homogenization limits pricing power, and Chinese open-source models have become a cheap alternative to OpenAI and Anthropic. AI capital expenditures have exceeded expectations, with the consensus for 2026 rising from $527 billion at the end of 2025 to about $800 billion by mid-year. Capital expenditures for hyperscale cloud providers in 2027 are expected to account for 3% of U.S. GDP, more than double the peak of 1.2% during the late 1990s telecom fiber construction. Allianz Research calculates that there is nearly a 46% growth gap between AI investment and sales, worse than the 32% during the 2001 telecom bubble.As of June, hyperscale cloud providers and related entities like Nvidia issued $225 billion in bonds, a year-on-year increase of 973.7%. The off-balance-sheet liabilities of tech giants have increased eightfold over four years to $1.65 trillion.

According to the New York Times, regulators are investigating the licensing agreement reached between Nvidia and Groq.

Pantera Capital Junior Partner Jay Yu published an article titled "The Rise of Compute Markets," stating that computing power and data center spending have become a trillion-dollar category, but GPU procurement is still mainly done through group chats, over-the-counter brokers, and bilateral agreements. He noted that the financialization of computing power is still in its early stages, constrained by SKU, time, and location, but could become a commodity asset similar to electricity or oil in the next 5 to 10 years. Jay Yu believes that the computing power market may form a "hardware-supplier-cluster" structure similar to the electricity "grid-operator-node," with new cloud vendors being structural shorts on GPUs, while on-demand platforms and application layers are longs.He mentioned that for every $100 spent on inference at the application layer, about $45 flows to the on-demand layer, about $50 flows to the new cloud or GPU layer, and about $5 flows to routing layers like OpenRouter. NVIDIA can be seen as the "central bank" of computing power, having announced support for up to 25% residual value. He also stated that physical delivery has a more enduring moat, and indices, cash-settled exchanges, and financing tools will subsequently emerge, with participants including SF Compute, Vast AI, Runpod, Compute Exchange, and others. The computing power market does not have mandatory price transparency requirements, and basis risk may be greater.

NVIDIA (NVDA.O) announced a collaboration with the Australian data center ecosystem to expand its artificial intelligence infrastructure capabilities.

Pequity Research cited FundaAI stating that the training computing power used by GPT-6 is approximately 10 times that of GPT-5.FundaAI indicated that based on industry discussions, the total computing power consumed by experiments, reinforcement learning, synthetic data generation, and supporting infrastructure could be several times that of the main pre-training run, potentially reaching up to ten times. Once TPU 8t and Vera Rubin are shipped on a large scale, the next round of pre-training acceleration can begin, with large-scale interconnection and optics benefiting the most during this cycle.

Director Mark Stevens of NVIDIA (NVDA.O) reported the sale of 1.02 million shares of NVIDIA common stock between September 3 and September 4, with a sale price range of $227.25 to $234.04 per share.

ASML stated that it plans to collaborate with its major customers to develop new solutions capable of producing advanced chip manufacturing equipment to meet the demand for large data center chips designed by companies like NVIDIA.Currently, the extreme ultraviolet (EUV) lithography machines produced by ASML, which are widely used, can manufacture chips with a maximum area of about 800 square millimeters. The next-generation "high numerical aperture" EUV lithography machine that ASML is about to launch will be able to produce finer chips. However, due to its use of smaller mask sizes, it is currently limited in the area of chips it can manufacture.ASML plans to showcase a pilot production line using larger mask sizes by 2031 and aims to enable this new technology for mass production by 2033.

NVIDIA CEO Jensen Huang shared data from the computing power market Ornn. Ornn stated that the H100 has been a training GPU for several years, but the rental price has increased by 22% in the past month, now reaching $3.28 per hour per unit. Jensen Huang emphasized that NVIDIA's computing power can continuously generate rental income, making it a revenue-generating asset.Ornn's H100 index is calculated based on actual rental transaction prices. The daily settlement price on September 7 was $3.17 per hour, and the latest displayed price further rose to $3.28. NVIDIA stated in its latest earnings report that GPUs can be redeployed across different customers and workloads.