Amazon recently announced a $110 million investment in AI research to support the development of its own designed Trainium chips. This move aims to reduce Amazon's reliance on Nvidia and promote technological advancements in its cloud computing platform AWS. Note: Image generated by AI, image licensed from service provider Midjourney. Trainium is a machine learning chip tailored for deep learning training and inference tasks. Through this investment, Amazon hopes to encourage academic research.

Recently, AMD announced it will lay off approximately 1,000 employees, which is about 4% of its global workforce. The layoffs primarily affect sales and marketing positions in the gaming and consumer PC departments, marking the chip giant's full transition towards the artificial intelligence chip sector. In the thriving AI chip market, NVIDIA currently holds a dominant 80% market share. Analysts predict that by 2028, the AI chip market will reach a scale of $500 billion. AMD's resource restructuring aims to capture a larger share in this rapidly growing market.

Recently, Amazon announced a significant investment of $110 million for artificial intelligence (AI) research aimed at reducing reliance on Nvidia and advancing the development of its own chips. The funding will support generative AI research at universities under the project name 'Build on Trainium.' The project will provide researchers with the opportunity to use Trainium chips to develop new AI architectures, machine learning libraries, and solutions for large-scale distributed AWS Train.

In a recent Reddit Q&A, OpenAI CEO Sam Altman admitted that insufficient computing power is one of the main reasons the company is unable to frequently launch new products. He stated that the current AI models are becoming increasingly complex, and OpenAI faces many constraints and difficult decisions on how to allocate computing resources to implement numerous excellent ideas. Reports suggest that OpenAI has encountered difficulties in obtaining sufficient computing infrastructure.

This week, Apple unveiled its latest M4 series chips at a launch event, marking a strong performance in the personal computer market. Apple claims that devices equipped with M4Pro and M4Max significantly surpass competing AI PC chips, particularly in handling artificial intelligence tasks. The M4Pro chip offers up to 14 CPU cores, including 10 high-performance cores and 4 efficient cores, along with 20 GPU cores. Apple stated that the M4Pro excels in AI computing.

OpenAI officially announces its entry into the AI chip sector through collaboration with chip giant Broadcom, planning to develop its first custom AI inference chip. This strategic move not only marks a significant step towards supply chain autonomy for OpenAI but also targets NVIDIA's current dominance in the AI chip market. According to Reuters, OpenAI has assembled a specialized R&D team of about 20 members, including the chief engineer who participated in the development of Google's Tensor processors. The project will be led by Broadcom for chip design and TSMC for manufacturing.

Nvidia has recently engaged in a series of collaborations with local businesses in India to promote its artificial intelligence chips and technologies. The CEO of the American chip design company, Jensen Huang, announced at an AI summit in Mumbai that Nvidia has partnered with one of India's most valuable companies, Reliance Industries, to co-establish the infrastructure for AI applications. Additionally, tech company Tech Mahindra will use Nvidia's chips and software to develop a Hindi AI model called "Indus2.0."

Against the backdrop of rising global chip demand, semiconductor manufacturing company TSMC announced its financial results for the third quarter of 2024, which were impressive. The company reported a net profit of NT$352.3 billion (approximately $10.1 billion), an increase of 54% compared to the same period last year. This achievement surpassed market analysts' expectations, with Reuters previously estimating a net profit of NT$300.2 billion. Image source: The image was generated by AI, provided by the image licensing service Midjourney. TSMC is a global leader in advanced chips.

This Monday, chip manufacturing giant Nvidia once again set a new historical high in the stock market, closing at $138.07 per share. This increase has investors eagerly anticipating as major companies like Microsoft, Meta, Google, and Amazon are about to release their earnings reports, creating excitement over their investments in AI infrastructure. Year-to-date, Nvidia's stock price has surged nearly 180%, leaving many in astonishment. Even more surprising is Nvidia's dominance in the AI chip market.

Recently, Lidwave announced the successful acquisition of $10 million in funding aimed at enhancing machine vision capabilities, particularly in key applications such as pedestrian detection in busy environments. Lidwave's CEO Yehuda Vidal stated in an interview that their innovative 4D LiDAR technology integrates complex Lidar sensors into a single chip, marking not only a technological revolution but also helping to reduce costs and expand the market. Note: Image from Lidwave's official website. This round of funding was backed by Jump.

Recently, TSMC announced that it expects a significant profit increase of 40% in its upcoming Q3 earnings report. This surge is primarily attributed to the booming demand for artificial intelligence (AI) chips. As the world's largest contract chip manufacturer, TSMC's clients include renowned companies such as Apple and Nvidia, which are actively advancing AI technology. According to LSEG's smart estimate, analysts predict that TSMC's net profit for the third quarter ending September 30 will reach NT$298.2 billion (approximately US$9.27 billion).

Recently, Intel officially launched the new Xeon 6 processor and Gaudi 3 AI accelerator, both designed to enhance the company's competitiveness in the fields of artificial intelligence (AI) and high-performance computing (HPC). With the rapid development of AI technology, the demand for efficient and cost-effective infrastructure has become increasingly urgent, and Intel has responded proactively. The Xeon 6 processor is equipped with performance cores (P-cores) that can double the performance of AI vision processing, while the Gaudi 3 accelerator's

Recently, foreign media reported that ByteDance is accelerating its efforts to self-develop and manufacture AI chips to reduce dependence on expensive chips from NVIDIA. The report claims that ByteDance plans to collaborate with TSMC and expects to mass-produce two self-developed AI chips by 2026, having already reserved the production of hundreds of thousands of chips. More notably, the report pointed out that ByteDance aims for its self-developed chip clusters to achieve four times the computing performance of a single H100 chip at a similar cost. In response, ByteDance quickly addressed this report.

Recently, the foreign media outlet The Information reported that ByteDance is accelerating the development of its own AI chips and plans to collaborate with TSMC, aiming for mass production by 2026. The report also stated that this move by ByteDance is intended to reduce dependence on NVIDIA chips and lower the costs of developing and operating AI models. Source note: The image is generated by AI and provided by the image licensing service Midjourney, according to reports from the Sci-tech Innovation Board Daily regarding today's media coverage of ByteDance's plans to collaborate with TSMC on AI chips.

Recently, AI chip company Groq, based in California, has reached a partnership agreement with Saudi Arabia's oil giant Aramco to establish a large data center in Saudi Arabia. The aim of this data center is to enhance Saudi Arabia's capabilities in the field of artificial intelligence and further promote the diversification of the country's economy. Groq's CEO, Jonathan Ross, stated that the data center is expected to be operational by the end of the year, initially equipped with 19,000 Language Processing Units (LPUs). Image source note: Picture

Recently, at the launch event for the new EX90 electric SUV, Volvo announced its continued collaboration with NVIDIA, stating that future models will be equipped with NVIDIA's chips. The EX90 is Volvo's first software-defined vehicle, featuring the NVIDIA Orin system-on-chip, which boasts computation capabilities exceeding 250 trillion operations per second. This SUV's core computing architecture not only supports deep learning functions but also provides robust support for its AI-driven active safety and driving assistance systems. Furthermore, Volvo plans for future enhancements.