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Nvidia recently announced plans to establish over one million square feet of manufacturing space in Arizona and Texas for the production and testing of AI chips. This represents a significant move by Nvidia to bring some of its manufacturing back to the United States. Nvidia's Blackwell chip is already in production at TSMC's Arizona facility. Additionally, Nvidia is establishing "supercomputer" manufacturing plants in Texas, partnering with Foxconn in Houston and Wistron in Dallas. In Arizona, Nvidia is collaborating with Amkor and others.

nEye Systems Inc., a silicon photonics startup, announced today that it has closed a $58 million Series B funding round. The investment was led by CapitalG, the growth equity investment arm of Alphabet Inc., Google's parent company. Other participants include Microsoft's M12, Micron Ventures, Nvidia, and Socratic Partners. This brings nEye's total funding to over $72 million.

In a recent annual letter to shareholders, Amazon CEO Andy Jassy highlighted the company's significant investment in artificial intelligence (AI). He noted that while the development and deployment costs of AI remain high, future AI usage costs are expected to decrease significantly as technology advances. Image Note: Image generated by AI, image licensing provider Midjourney. Jassy revealed that Amazon plans to invest up to $100 billion in capital expenditures in 2025.

In today's rapidly expanding AI landscape, many businesses face high hardware costs, particularly the need for advanced computing chips. To address this challenge, Indian AI startup Ziroh Labs, in collaboration with researchers from top technical institutes in the country, has launched a novel, affordable system capable of running large AI models without relying on high-end computing chips from companies like Nvidia. This innovative system marks a significant step towards democratizing AI access by expanding device options.

Japan's state-backed Rapidus Corp. has begun adjusting its chipmaking equipment and is expected to start test production of advanced semiconductors by the end of this month. This is a crucial step for Rapidus as it pushes to enter the artificial intelligence (AI) components market. The two-year-old startup aims for mass production of 2nm semiconductors by 2027, aiming to rival Taiwan Semiconductor Manufacturing Company (TSMC), a leading semiconductor manufacturer. Image Caption: Image

Faster data transfer speeds are crucial for advancements in AI. Lightmatter, a Mountain View-based startup valued at $4.4 billion, has announced two new technologies to accelerate connections between AI chips. Having raised $850 million in venture capital, Lightmatter is part of the burgeoning silicon photonics trend in Silicon Valley. Their innovation lies in using optical fiber to transmit data via light signals instead of traditional electrical signals.

Bloomberg, citing sources, reports that Ant Group has made a significant breakthrough in AI, reducing AI model training costs by 20% using chips from Alibaba and Huawei. This injects new momentum into China's drive for technological self-reliance. The report further indicates that Ant Group's internal tests show these Chinese-made AI chips rival Nvidia's offerings in performance. Widespread validation and adoption of this could significantly alter the global AI landscape.

SoftBank Group Corp., the Japanese technology investment firm, announced it will acquire server-class chip designer Ampere Computing for $6.5 billion. This move marks another significant step in SoftBank's push into artificial intelligence (AI) and high-performance computing. Ampere Computing's major investors, including Oracle and Carlyle Group, also divested their stakes in the deal. Ampere focuses on multi...

According to Bloomberg, OpenAI is making a massive investment in its first infrastructure project, dubbed "Stargate," with an estimated cost of $100 billion. The project's first data center complex, located in the small Texas town of Abilene, is planned to house up to 400,000 powerful Nvidia AI chips. Once fully operational, it will be one of the world's largest AI computing centers. Image Note: Image generated by AI, image licensing service Midjourney.

Recently, Professor Zhai Jidong's team from the Institute of High Performance Computing at Tsinghua University, in collaboration with Tsinghua-affiliated innovative enterprise, Qingcheng Extreme Intelligence, announced the open-sourcing of Chitu, a groundbreaking large model inference engine. This innovative technology marks another significant breakthrough for China in the AI field, particularly in inference engine development. A core highlight of the Chitu engine is its ability to natively run FP8 precision models on non-Nvidia Hopper architecture GPUs and various domestic chips.

Social media giant Meta is facing unprecedented AI infrastructure costs, with projected AI-related spending soaring to a staggering $65 billion, potentially contributing to a total annual expenditure of $119 billion! Faced with this astronomical bill, the tech giant has decided to develop its own AI chips, and has already made significant progress. Recent reports indicate that Meta is about to begin a small-scale deployment of its custom chips, signaling a gradual move away from Nvidia and its reliance on their GPUs.

With the rapid development of artificial intelligence technology, tech giants are increasingly investing in new AI chips. Recently, news about OpenAI's self-developed AI chips has attracted widespread attention in the market, but industry experts believe this will not pose a substantial threat to Nvidia's stock price. Source of the image: The image is AI-generated, and the image licensing service provider Midjourney in a recent video report analyzed Nvidia's recent market dynamics and...

On February 11, 2025, at the World Governments Summit held in Dubai, UAE, Baidu founder Li Yanhong engaged in an in-depth dialogue with UAE AI Minister Omar Sultan Al Olama to explore future development trends in AI infrastructure. During the discussion, Al Olama mentioned the recent global attention towards DeepSeek, which caused significant fluctuations in the stock prices of several major chip manufacturers and exchanges, and asked Li Yanhong for his views on the future of data centers and AI infrastructure.

In today's development of artificial intelligence (AI), the speed of data transmission has become a significant bottleneck hindering its progress. To break through this barrier, a research team led by the University of Michigan (U-M) is developing a brand new chip connection system that uses optical waves instead of traditional cables for data transmission. This innovation is expected to address the 'memory wall' problem that limits computational speed and promote further growth of AI models. The project has received a $2 million grant from the National Science Foundation's Future Semiconductor program, with participation from the University of Washington and Penn State.

With the rapid development of artificial intelligence, the investment boom in AI chip manufacturers has gradually intensified. Among them, Blaize has attracted wide attention in the market. Founded by a former Intel engineer, the company announced its plan to go public on NASDAQ through a SPAC (Special Purpose Acquisition Company) on January 14, 2025. Blaize was established in 2011 and is headquartered in El Dorado Hills, California. To date, it has raised $335 million in investments, primarily from Samsung and Mercedes.