October 28, 2025 · 24-Hour AI Briefing: Qualcomm Challenges Nvidia, AMD Builds Supercomputers, Amazon’s Mass Layoffs, and China’s Robotaxi IPOs
In the past 24 hours, the global AI landscape has once again shifted. From chipmakers expanding into new frontiers to tech giants reshaping their organizations and China’s autonomous driving leaders going public — AI remains the driving force behind every major technological transformation.
1. Qualcomm Launches AI200 and AI250 Chips, Entering the AI Data Center Market
Qualcomm has unveiled two new AI chips — the AI200 and AI250 — marking its official entry into the AI data center sector to challenge Nvidia’s dominance. Both chips are powered by Qualcomm’s Hexagon NPU architecture and are expected to begin commercial rollout in 2026 and 2027 respectively. Following the announcement, Qualcomm’s stock surged over 11%, peaking at $205.
Comment:
Qualcomm’s transition from a mobile chip giant to a data center AI player signals a direct challenge to Nvidia and AMD in the high-performance AI computing space. The stock market’s reaction shows investors’ optimism toward this strategic pivot.
However, Qualcomm’s ecosystem remains weak compared to its competitors, and the verification cycle for enterprise-level AI products is long. Strong performance alone may not be enough — without a solid developer ecosystem and client trust, market adoption remains uncertain.
2. AMD and the U.S. Department of Energy Invest $1 Billion in Two Supercomputers
AMD has partnered with the U.S. Department of Energy to invest $1 billion in the development of two next-generation supercomputers at Oak Ridge National Laboratory (ORNL), named “Lux” and “Discovery.”
The project also involves Hewlett Packard Enterprise (HPE) and Oracle Cloud Infrastructure (OCI) as key collaborators.
Comment:
This is the U.S.’s first “AI factory-level” scientific supercomputing project, jointly developed by ORNL, AMD, HPE, and OCI. Powered by AMD’s Instinct MI355X GPUs, EPYC CPUs, and Pensando networking technologies, the systems will deliver roughly three times the AI capacity of current supercomputers.
The initiative strengthens AMD’s leadership in HPC and AI research infrastructure, providing advanced capabilities for energy research, materials science, medicine, and manufacturing.
Scientific AI is not just about computing power — it’s a reflection of national competitiveness. As the U.S. takes the lead, it remains to be seen whether Europe, China, and Japan will respond with their own “AI super-factories.”
3. Amazon Announces Its Largest Layoffs in History, Refocusing on AI Strategy
Amazon plans to cut up to 30,000 jobs across multiple business divisions — its largest workforce reduction to date. The goal is to streamline operations, conserve cash, and reallocate resources toward artificial intelligence, which the company considers its next strategic growth pillar.
Comment:
The layoffs will undoubtedly cause internal turbulence, especially across non-technical departments. But in a global market increasingly dominated by AI and automation, cost optimization has become the new corporate mantra.
Amazon expects to save billions through AI-driven operational efficiency and reinvest in its AI infrastructure initiatives.
Still, the key question remains — can Amazon truly differentiate itself in the AI race? With Microsoft Azure and Google Cloud accelerating their AI offerings, AWS faces both competitive and innovation pressure.
4. Pony.ai and WeRide to Go Public on Hong Kong Stock Exchange on November 6
China’s leading autonomous driving companies — Pony.ai and WeRide — have confirmed plans to go public on the Hong Kong Stock Exchange on November 6. Pony.ai aims to issue about 41.96 million shares with a maximum price of HK$180 per share, while WeRide plans to offer 88.25 million shares at up to HK$35 per share.
Comment:
The near-simultaneous listings mark a new milestone for China’s autonomous driving sector, signaling maturity in capital market recognition. Both companies are already listed in the U.S., and their Hong Kong IPOs further strengthen their dual-market presence.
However, the road to profitability remains long. The industry is fiercely competitive — domestically, Pony.ai and WeRide face Baidu’s Apollo; internationally, they go up against Waymo, Tesla, and Cruise.
As capital pours into the sector, the real race isn’t just for technology — it’s for sustainable business models. Only those who achieve large-scale deployment and cost efficiency will emerge as true winners.
From the rise of new AI chips to billion-dollar supercomputers, from massive corporate restructuring to autonomous driving IPOs, the global AI race continues to accelerate.
This is no longer just a competition in algorithms — it’s a full-spectrum contest across nations, enterprises, and capital.
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