The shipment volume of AI smartphones is expected to reach 60 million units in 2024

Japan's Rapidus Begins Test Production of AI Chips

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

Lightmatter's Photonics Technology Boosts AI Chip Data Transfer Speeds

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.

Ambarella Unveils Next-Generation Edge AI at ISC West, Showcasing the Power of Generative AI

Rise of Domestic AI Chips! Ant Group's Training Costs Reportedly Drop 20%, Rivaling Nvidia

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.

OpenAI's Stargate Project: First Data Center to House Up to 400,000 Nvidia Chips

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 Showcases Next-Generation AI Chips, Focusing on Blackwell Series GPUs

Meta Aims to Slash $65 Billion AI Bill with Custom Chips, Seeking to Break Free from Nvidia?

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.

Vivo Restructures, Establishes New AI Department and Shifts Large Model Training to On-Device

OpenAI's Self-Developed AI Chips Pose No Threat to Nvidia's Stock Price

With the rapid development of artificial intelligence technology, tech giants are increasingly investing in new AI chips. Recently, news about OpenAI's self-developed AI chips has attracted widespread attention in the market, but industry experts believe this will not pose a substantial threat to Nvidia's stock price. Source of the image: The image is AI-generated, and the image licensing service provider Midjourney in a recent video report analyzed Nvidia's recent market dynamics and...

Meta Introduces New Framework to Limit the Release of High-Risk AI Systems

Meta has recently launched a new risk policy framework aimed at assessing and mitigating the risks associated with cutting-edge AI models, with the intention to halt development or restrict the release of these systems when necessary. This framework, named 'Cutting-edge AI Framework', outlines how Meta will categorize AI models into high-risk and critical risk categories, and take appropriate measures to reduce risks to an 'acceptable level'. In this framework, critical risks are defined as those uniquely capable of executing specific threat scenarios, while high risk implies