Recently, Chengdu Huayi revealed on its interactive platform that it has successfully developed a specialized AI chip for the edge computing field. This chip boasts an AI computing power of up to 16 Tops and is currently undergoing limited trial use among several clients in specific industries. The new chip not only offers robust computing power but also demonstrates excellent performance in video encoding and decoding, supporting video processing capabilities of up to 8K resolution. This represents a significant technological advancement for applications such as video surveillance and smart homes.

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.

Recently, researchers from the Department of Engineering at Princeton University and the Indian Institute of Technology achieved breakthroughs in the design of wireless microchips using artificial intelligence (AI), significantly reducing design time and costs while discovering new functions. The results of this research were published in the journal Nature Communications, marking the dawn of a new era in microchip design. Image source note: The image was generated by AI, image licensed by Midjourney. Microchips play a vital role in modern technologies such as wireless communication. They consist of traditional electronic circuits and complex electromagnetic structures.

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 event, NVIDIA CEO Jensen Huang pointed out that Samsung Electronics is facing some difficulties in the production of new AI memory chips. These new memory chips, known as High Bandwidth Memory (HBM), are crucial for the next generation of AI systems powered by NVIDIA chips. Huang mentioned at the press conference that Samsung's production speed for HBM is slower compared to its competitor SK Hynix.

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.

At the 2025 International Consumer Electronics Show (CES2025), Qualcomm showcased its next-generation AI technology and collaborative achievements across PCs, cars, smart homes, and enterprise sectors. The event took place in Las Vegas, where Qualcomm demonstrated how AI capabilities in its chips are transforming user experiences across various devices, presenting the future of smart technology. Qualcomm also introduced the Snapdragon X platform for the first time, marking the fourth platform in its high-performance PC product lineup.

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 latest collaboration between Aliyun and Hezhima Intelligent has sparked a new wave in the domestic smart car sector. Aliyun announced that its Tongyi Qianwen models with 1.5 billion and 3 billion parameters have been successfully ported to the Hezhima Intelligent Wudang C1200 series automotive-grade chip, marking a significant breakthrough for domestic large models in vehicular scenarios. In practical applications, this integrated solution supports multi-turn natural dialogue in offline environments, providing users with a smooth human-computer interaction experience. This technological breakthrough not only demonstrates the R&D capabilities of domestic AI chips but also injects new momentum into the development of smart cars.

In today's rapidly evolving technological landscape, Large Language Models (LLMs) play a crucial role across various industries, aiding in task automation and enhancing decision-making efficiency. However, in specialized fields like chip design, these models face unique challenges. NVIDIA's recently launched ChipAlign is specifically designed to address these challenges, aiming to combine the strengths of general-purpose LLMs with those of chip-specific LLMs. ChipAlign employs a new model merging strategy that...

Chip giant Nvidia is expanding its territory once again. Recently, Nvidia officially announced the acquisition of Israeli artificial intelligence startup Run:ai for $700 million. This deal has passed through the stringent scrutiny of regulatory bodies in Europe and the US, paving the way for Nvidia to further cement its dominance in the AI field. As the absolute leader in the GPU market, Nvidia currently holds about 80% of the market share. This strong position has attracted the attention of regulators. The European Commission raised concerns about the acquisition in October, fearing it could harm the market.

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.

Doug LeFevre, CEO of Advantest, the world's largest chip testing equipment supplier, stated that if investment in data centers slows down, the demand for AI smartphones may help certain areas of the semiconductor industry avoid a 'vicious' recession. LeFevre indicated that he is closely monitoring whether spending by large U.S. tech companies in the AI sector is slowing down. Meta, Google, and Microsoft have been major investors in data centers that provide significant computational power. LeFevre stated that the construction of data centers...