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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.

Reports suggest that Nvidia, the global semiconductor giant, is nearing a deal to acquire the startup Lepton AI for potentially hundreds of millions of dollars. Founded two years ago, Lepton AI focuses on leasing servers equipped with Nvidia AI chips to other businesses. According to The Information, the deal is progressing rapidly, although Nvidia has yet to officially comment.

Former Intel CEO Pat Gelsinger recently criticized Nvidia's pricing strategy for its AI GPUs on the Acquired podcast during Nvidia's 2025 GPU Technology Conference, arguing that the high cost makes them unsuitable for large-scale AI inference tasks. Gelsinger highlighted that inference is crucial for deploying AI models and that the industry should focus more on inference, a domain where Nvidia's technology falls short in terms of cost-effectiveness. Image source omitted.

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.

South Korean media reports that FuriosaAI, a startup specializing in AI application chips, recently rejected an $800 million acquisition offer from tech giant Meta. FuriosaAI stated it will continue focusing on independent R&D and production of its AI chips. The report indicates that the breakdown of acquisition talks stemmed from disagreements on business strategy and organizational structure, not the acquisition price itself. Similar to many tech companies building large language models (LLMs), Meta...

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.

Nvidia has introduced Dynamo, a new software designed to significantly accelerate the performance of its DeepSeek AI technology, promising a 30-fold speed increase.

Nvidia has unveiled its next-generation AI chip, Rubin, promising a performance leap of up to 900 times that of its current flagship Hopper architecture. This significant advancement points towards a new era in AI processing capabilities.

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.

Nvidia recently announced that its next-generation AI chip will be named after renowned astronomer Vera Rubin. Born in Philadelphia in 1928, Vera Rubin's exceptional achievements and profound impact on the scientific community serve as the inspiration behind this name.

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.

Meta is reportedly testing a self-designed chip for training AI systems, a move to lessen its reliance on hardware vendors like Nvidia. According to Reuters, the chip, manufactured in collaboration with Taiwan Semiconductor Manufacturing Company (TSMC), is specifically designed for AI workloads. Currently undergoing small-scale testing, Meta plans to expand production if the tests are successful. Image caption.

Taiwan Semiconductor Manufacturing Company (TSMC), the world's largest semiconductor manufacturer, announced plans to invest at least $100 billion in the United States over the next four years to build multiple new chip fabrication facilities. The announcement was made at a press conference with former US President Trump. TSMC CEO C.C. Wei stated that the investment would primarily focus on expanding its Arizona facilities. Wei added, "We will produce many AI chips to support the progress of Artificial Intelligence." This new commitment builds upon TSMC's previous pledge of a $65 billion US investment.