NVIDIA CEO Jensen Huang: If Europe Wants to Reap the AI Dividend, Every Industry Should Embrace AI

Related topics top start Related topics top end Futures promotion begin Futures promotion end Miaopai begin Miaopai end Video player start Video player end Market chart begin Market chart end

"If Europe wants to benefit from the AI dividend and truly build an AI ecosystem and AI economy, it must get AI into every end industry," Jensen Huang said Wednesday at Nvidia's GTC conference in Berlin. Citing automobiles, finance and healthcare as examples, he said: "Every industry must transform into an AI enterprise."

This launch event was one stop on Huang's European trip. He has been signing agreements with local companies one after another while making the case for AI safety to European political and business leaders. The trip comes at a sensitive moment for the industry: over the past two weeks, AI sector stocks have been under sustained pressure, and the closely watched Philadelphia Semiconductor Index has posted its longest losing streak since 2008.

Huang and his executive team hold GTC conferences in many places around the world, showcasing the latest AI advances while opening up business opportunities for an ever-expanding product lineup.

The new products include the DSX Pod, a containerized mini data center that helps enterprises quickly complete computing hardware deployment. Nvidia says each container comes with servers, cables and supporting piping pre-installed and pre-commissioned; once it arrives, the customer only needs to connect power and link it with other units of the same model to put it into service.

Built by Nvidia partners including Dell, the solution shortens the hardware deployment cycle from six months to 14 days.

The container product is suited to small and medium-sized computing deployments of less than 1 gigawatt. Data center projects typically use power consumption as their core metric, and power supply is a key constraint on computing infrastructure.

Nvidia says several European customers have already adopted the DSX AI data center solution and the latest Vera Rubin processors, including Nscale, a data center developer in which Nvidia has invested.

Nvidia is the world's most valuable listed company, and supply chain capacity bottlenecks have long constrained its growth. To address this, Ibiden, Samsung Electro-Mechanics and Unimicron will increase their supply of packaging substrates; Amkor plans to quadruple its chip packaging capacity by the end of 2028; and King Yuan Electronics is expanding chip testing capacity. Nvidia is also advancing in-package optical interconnect technology to speed up data communication between chips.

As the market grows increasingly concerned that AI is slipping beyond human control, Nvidia is developing supporting software to constrain AI agents (intelligent agents that orchestrate multiple large models and programs) so that they operate within defined boundaries. Nvidia offers a hardware and software reference solution that prevents agents from accessing data beyond their authority or obtaining operational permissions the designers did not authorize.

In embodied intelligence (the robotics sector), Nvidia says progress has been rapid. In the first half of this year, revenue in this segment grew by up to 30% year on year, to about $11 billion.

Nvidia says R&D in this sector is highly complex and capital-intensive, and currently only well-funded companies can take part.

To lower the R&D barrier, Nvidia has partnered with Agile Robots to build an open-source robot development platform for researchers; the platform's accompanying hardware is the Agile ONE SN humanoid robot powered by Jetson Thor.

In the automotive sector, Volvo is using Nvidia chips to develop autonomous vehicles; Volkswagen's commercial vehicle business uses Nvidia solutions; and Bolt Technology OU is developing robotaxis based on Nvidia hardware and software. news_keyword_pub,usstock,DELL&SIEGY Account opening QR code start

Account opening QR code end iframe below article body iframe below article body General statement General statement QR code at end of article start QR code at end of article start

QR code at end of article start QR code at end of article start Editor name and work code

Editor name and work code