In Short:
– Chinese researchers set a world record, accelerating a test vehicle to 700 km/h in two seconds.
– This milestone positions China as a leader in ultra-high-speed maglev technology and future transport developments.

China has set a new world record in magnetic levitation technology after accelerating a ton-class superconducting maglev test vehicle to 700 kilometres per hour in just two seconds. The achievement, reported by state broadcaster CCTV, marks the fastest acceleration ever recorded for an electric maglev system and cements China’s position at the forefront of ultra-high-speed transport innovation.

The test was conducted by researchers at the National University of Defense Technology on a 400-metre track, where footage showed the vehicle flashing across the rail-like structure in a blur, leaving a misty trail behind it. The breakthrough follows more than a decade of research tackling complex challenges such as ultra-high-speed electromagnetic propulsion, electric suspension guidance systems, and high-field superconducting magnets, all of which are critical to stable travel at extreme speeds.

Hyperloop technology

Beyond headline-grabbing velocity, the milestone opens the door to future transport systems, including vacuum-tube maglev networks, commonly referred to as hyperloop technology. Scientists say the same advancements could also be applied to aerospace launch assistance, electromagnetic launch systems, and advanced experimental testing. According to Professor Li Jie from the National University of Defense Technology, the successful trial will significantly accelerate China’s research into frontier technologies, with future work focusing on pipeline-based high-speed transport and aerospace equipment testing.

While China now leads in superconducting maglev acceleration, global competition remains fierce. Japan still holds the record for the fastest manned train, with its L0 Series maglev reaching 603 kilometres per hour during testing in 2015. China, however, operates the world’s only commercial maglev service — the Shanghai Maglev — which currently runs at 300 kilometres per hour after its top speed was reduced from 431 kilometres per hour in 2021.

The December test builds on earlier progress made this year, including a 1.1-ton test sled that reached 650 kilometres per hour in seven seconds over a 600-metre track in June 2025. Together, these developments signal rapid momentum in China’s push toward next-generation transport systems that could redefine how people and payloads move across the planet.

In Short:
– Nvidia has signed a $20 billion deal with AI chip startup Groq to enhance its AI inference capabilities.
– Groq will remain independent while Nvidia acquires technology and talent, excluding Groq’s cloud business.

Nvidia has made waves in the AI world with a complex $20 billion agreement with AI chip startup Groq, marking the chip giant’s largest deal to date. Unlike a traditional acquisition, Nvidia will license Groq’s AI inference technology while hiring key executives, including founder Jonathan Ross and president Sunny Madra, as Groq continues to operate independently. This arrangement highlights a growing Silicon Valley trend in which major tech companies selectively acquire intellectual property and top talent without fully integrating startups.

While CNBC reported the deal’s $20 billion valuation, neither Nvidia nor Groq confirmed financial terms. Nvidia CEO Jensen Huang clarified that the company is “adding talented employees to our ranks and licensing Groq’s IP, but we are not acquiring Groq as a company.” Groq described the transaction as a “non-exclusive licensing agreement” for its inference technology. The startup’s cloud business will remain under the leadership of new CEO Simon Edwards, formerly Groq’s CFO.

Increasing competition

The deal strategically targets AI inference — the process where trained models respond to user queries — a sector where Nvidia faces increasing competition. Groq’s Language Processing Unit reportedly executes large language models ten times faster while consuming one-tenth the energy of traditional GPUs. With Jonathan Ross, who previously helped develop Google’s Tensor Processing Unit, joining Nvidia, the company strengthens its expertise across the AI stack. Huang confirmed plans to integrate Groq’s low-latency processors into Nvidia’s AI factory architecture, expanding its capabilities for real-time AI workloads.

This $20 billion deal eclipses Nvidia’s previous largest acquisition, the $6.9 billion purchase of Mellanox in 2019. Groq itself raised $750 million in September at a $6.9 billion valuation, with investors including BlackRock, Samsung, Cisco, and 1789 Capital. The arrangement also reflects a broader shift in Silicon Valley: companies like Google, Amazon, and Microsoft have increasingly opted for “acqui-hire” deals that license technology and recruit founders while leaving the original companies structurally intact.

With more than $60 billion in cash reserves, Nvidia is clearly doubling down on its aggressive expansion strategy across the AI ecosystem. By combining top-tier talent, breakthrough technology, and strategic IP licensing, Nvidia is positioning itself to dominate the AI inference market and maintain its leadership in the global AI race.

In Short:
– Google Cloud and Palo Alto Networks have partnered on a nearly $10 billion security services deal.
– The multiyear contract will integrate Palo Alto’s security platform with Google Cloud’s AI capabilities.

Alphabet’s Google Cloud and Palo Alto Networks have announced a partnership valued at nearly $10 billion. This agreement marks the largest security services deal for Google Cloud as enterprises increase efforts to protect AI infrastructure amid rising cyber threats.The multiyear contract involves Palo Alto moving key internal workloads to Google Cloud and creating new AI-driven security solutions. While executives refrained from commenting on financial specifics, the deal enhances a relationship formed in 2018.

Research from Palo Alto’s December 2025 State of Cloud Report revealed that 99% of surveyed companies faced at least one attack on their AI infrastructure in the past year. The collaboration aims to integrate Palo Alto’s Prisma AIRS security platform with Google Cloud’s AI capabilities, including Vertex AI and Agent Engine, to enhance protection for AI workloads.

AI Security Demand

Matt Renner, Google Cloud’s chief revenue officer, indicated that the surge in AI has created significant security demand. BJ Jenkins, president at Palo Alto, likened the current threat environment to those seen during the early growth of cloud computing.

The investment will see Palo Alto’s products migrated to Google’s platform, while also funding new AI-focused services. The companies have launched 75 joint integrations, achieving $2 billion in sales via the Google Cloud Marketplace.

The agreement also highlights broader cybersecurity strategies from both firms. Google is pursuing a $32 billion acquisition of Wiz, awaiting regulatory approval. Meanwhile, Palo Alto has plans to acquire observability platform Chronosphere for $3.35 billion.

Renner noted that this collaboration positions Google Cloud advantageously as AI continues to reshape the competitive landscape against rivals like Amazon and Microsoft. Furthermore, Palo Alto CEO Nikesh Arora’s previous experience at Google enhances the partnership’s potential.