U.S. Air Force Plans to Invest $6 Billion to Build 2,000 AI Drones


The US Department of Defense plans to invest hundreds of millions to expand its fleet of drones and autonomous systems. The initiative aims to incorporate more artificial intelligence technology to enhance military capabilities. This includes developing 'small, intelligent, and cost-effective' AI systems, strengthening surveillance equipment and networks to provide real-time information. This has sparked discussions about the ethical and security implications of applying artificial intelligence in the military sector.
Sunrise, an AI inference GPU chip startup, raised nearly 3 billion yuan within a year, setting a record for early-stage funding in China's AI chip sector. Backed by industrial capital, top VCs/PEs, and national funds, this investment reflects strong market confidence in its technology and domestic substitution potential. Investors like Huaxu Fund from Sany Group highlight strategic synergy between high-end manufacturing and AI chips.....
Ant Tech collaborates with Tongfang Global Life Insurance, using AI technology as the core to deepen cooperation in all areas of insurance. The goal is to reshape business processes through technological empowerment, enhancing operational efficiency and risk control. AI technology has become a crucial engine for high-quality development in the insurance industry, with leading insurers increasingly prioritizing it as a strategic focus.
Baidu officially launched ERNIE Bot 5.0, featuring 2.4 trillion parameters, achieving a transition from multimodal fusion to native full-modal. It adopts native full-modal unified modeling technology, jointly training text, images, videos, and audio within a unified architecture, differing from the industry's common post-hoc integration approach.
As AI becomes an essential tool for enterprises, building dedicated computing infrastructure has become a trend. More and more companies are choosing to build their own local AI workstations instead of relying on cloud-based APIs, mainly due to considerations of data security, cost control, and business stability. The initial investment in self-built hardware can typically be recouped within 1.5 to 2.5 years, showing significant economic advantages. Enterprises need to match different scales of computing solutions based on the complexity of their tasks.