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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.

Nvidia's stock fell over 6% on Tuesday, a decline that occurred the day after the company announced its next-generation AI chips, following a record high in stock price. This drop is partly attributed to a broader sell-off of tech stocks due to soaring U.S. Treasury yields. Nevertheless, Nvidia continues to be recognized as the strongest performer among the so-called 'Super Seven Giants', with a stock price increase of 185% over the past year and more than 900% over the past two years. As artificial intelligence continues to thrive, Nvidia has become the biggest beneficiary.

At the recent CES conference, NVIDIA CEO Jensen Huang stated that the performance improvement speed of the company's AI chips has surpassed the historical standards set by Moore's Law. Moore's Law, proposed by Intel co-founder Gordon Moore in 1965, predicted that the number of transistors on a computer chip would approximately double every year, consequently doubling chip performance as well. However, in recent years, the pace of progress of Moore's Law has significantly slowed. Image source note: The image was generated by AI, image licensed by Midjourney.

In 2024, NVIDIA significantly increased its efforts in venture capital, investing as much as $1 billion across 50 different funding rounds and several corporate acquisitions. This figure marks a substantial rise from $872 million and 39 funding rounds in 2023. After profiting $9 billion from AI chip sales, NVIDIA is concentrating resources on 'core AI' companies that require substantial computing power, many of which are also NVIDIA's clients. The investment list for 2024 includes some well-known companies.

The Beijing Academy of Artificial Intelligence (BAAI) recently announced that it has collaborated with ecological partners to build and open source the Heterogeneous Unified Communication Library FlagCX, aiming to address the challenges faced by communication libraries in the era of diverse computing power and fill the significant gap in the open source software stack for diverse computing power. This initiative responds to the special action organized by relevant national departments for the governance of typical issues in 'Clear and Bright: Algorithmic Problems of Online Platforms', reflecting the important principles of correct algorithm orientation, fairness and justice, and transparency.