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On the evening of June 11, XPeng Motor officially released its latest model - XPeng G7. This car is known as the world's first AI car with L3-level computing power. Its biggest highlight lies in the installation of XPeng’s self-developed Turing AI chip, which has a computational capability equivalent to three Orin-X chips, showcasing XPeng's technical advantages in the intelligent vehicle field. The XPeng G7 is equipped with a powerful 40-core processor that can run up to 30B simulation parameters and features two self-developed neural network processors.

According to Reuters, citing three sources familiar with the matter, Nvidia will launch a new AI chip designed specifically for the Chinese market in June. The pricing is expected to be between $6,500 and $8,000, which is significantly lower than the current H20 series priced around $10,000 to $12,000. The new chip is based on the latest Blackwell architecture and adopts the RTX Pro6000D design framework. To bypass US export restrictions on advanced chips to China, this GPU deliberately avoids TSMC's advanced packaging processes and instead uses standard GDDR7.

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.

During his recent Middle East visit this week, U.S. President Donald Trump focused on artificial intelligence (AI) chips as a key topic of discussion. According to the latest report from The New York Times, Gulf countries such as Saudi Arabia and the UAE hope to obtain advanced AI chips from American companies, and the Trump administration appears open to facilitating relevant transactions. Image source note: Images generated by AI, licensed through Midjourney service provider. This shift contrasts sharply with the restrictive policies of the Biden administration. During the Biden administration, the U.S. restricted AI chip exports to Saudi Arabia.

XPeng Motors announced that its self-developed Turing AI chip, designed to support Level 4 autonomous driving capabilities, is slated for mass production in 2025.

Xiaopeng Motors chairman He Xiaopeng recently announced that the company's fully self-developed Turing AI chip will be mass-produced and launched in the second quarter of this year. This progress comes as the automotive industry accelerates the application of end-to-end intelligent driving technology and the scale of AI large models continues to expand. Xiaopeng Motors is building its strongest AI brain by simultaneously developing a world base model with 35 times the parameters of mainstream VLA models, and a self-developed chip with computing power equivalent to three Nvidia Orin Xs, which is about to be mass-produced.

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.

AI chip giant Nvidia announced it will partner with manufacturing collaborators to design and build its first AI supercomputer on US soil, marking a significant step in its supply chain strategy. Nvidia has commissioned over one million square feet of manufacturing space for production and testing of its latest Blackwell AI chips in Arizona, and for the manufacturing and testing of the AI supercomputer in Texas. Nvidia's ecosystem partners are expected to invest $500 million to support the construction of this AI infrastructure. While the...

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.

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...