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American chipmaker Nvidia recently announced it would collaborate with Humain, an AI startup owned by the Saudi Arabian sovereign wealth fund, to provide 18,000 cutting-edge AI chips to Saudi Arabia. This announcement was made during the visit of a US delegation to Saudi Arabia, Qatar and the UAE, marking an important step for Saudi Arabia in artificial intelligence and cloud computing infrastructure. Nvidia founder Jensen Huang expressed this at the Saudi-US Investment Forum.

Shanghai is actively promoting innovation and upgrading within its automotive industry, focusing on the application of advanced technologies including high-performance computing chips and intelligent driving large models. This initiative aims to enhance the competitiveness and technological advancement of the city's automotive sector.

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...

Google integriert derzeit aktiv seinen neuesten KI-Assistenten Gemini in den Chrome-Browser, um Nutzern ein intelligenteres und komfortableres Surferlebnis zu bieten. Diese Funktion ähnelt dem Copilot im Microsoft Edge Browser, wurde aber von Google einzigartig gestaltet. Laut Analysen des Browser-Forschers Leopeva64 ist der Gemini AI-Assistent bereits in Chrome Canary (der experimentellen Version von Google Chrome) verfügbar.

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.