Emphasising cost reduction and sustainability, Nvidia founder and CEO Jensen Huang has detailed new semiconductors, software and systems to power data centres, factories, consumer devices, robots and more, with the aim of driving a new industrial revolution.

“Generative AI is reshaping industries and opening new opportunities for innovation and growth,” Huang said in an address ahead of this week’s Computex technology conference in Taipei.

“Today, we’re at the cusp of a major shift in computing. The intersection of AI and accelerated computing is set to redefine the future.

“The future of computing is accelerated,” Huang said. “With our innovations in AI and accelerated computing, we’re pushing the boundaries of what’s possible and driving the next wave of technological advancement.”

Huang revealed a roadmap for new semiconductors. Revealed for the first time, the Rubin platform will succeed the upcoming Blackwell platform, featuring new GPUs, a new Arm-based CPU – Vera – and advanced networking with NVLink 6, CX9 SuperNIC and the X1600 converged InfiniBand/Ethernet switch.

“Our company has a one-year rhythm. Our basic philosophy is very simple: build the entire data centre scale, disaggregate and sell to you parts on a one-year rhythm, and push everything to technology limits,” Huang explained.

Nvidia is driving down the cost of turning data into intelligence, Huang explained.

“Accelerated computing is sustainable computing,” he emphasised, outlining how the combination of GPUs and CPUs can deliver up to a 100x speedup while only increasing power consumption by a factor of three, achieving 25x more performance per Watt over CPUs alone.

“The more you buy, the more you save.”

Computer manufacturers have embraced Nvidia GPUs and networking solutions. The include ASRock Rack, ASUS, Gigabyte, Ingrasys, Inventec, Pegatron, QCT, Supermicro, Wistron and Wiwynn, which are creating cloud, on-premises and edge AI systems.

The Nvidia MGX modular reference design platform now supports Blackwell, including the GB200 NVL2 platform, designed for optimal performance in large language model inference, retrieval-augmented generation and data processing.

AMD and Intel are supporting the MGX architecture with plans to deliver, for the first time, their own CPU host processor module designs. Any server system builder can use these reference designs to save development time while ensuring consistency in design and performance.

In networking, Huang unveiled plans for the annual release of Spectrum-X products to cater to the growing demand for high-performance Ethernet networking for AI.

Nvidia Spectrum-X, the first Ethernet fabric built for AI, enhances network performance by 1,6x more than traditional Ethernet fabrics. It accelerates the processing, analysis and execution of AI workloads and, in turn, the development and deployment of AI solutions.

With Nvidia NIM, the world’s 28-million developers can now easily create generative AI applications. NIM – inference microservices that provide models as optimized containers – can be deployed on clouds, data centres or workstations.

NIM also enables enterprises to maximise their infrastructure investments. For example, running Meta Llama 3-8B in a NIM produces up to 3x more generative AI tokens on accelerated infrastructure than without NIM.

Nearly 200 technology partners – including Cadence, Cloudera, Cohesity, DataStax, NetApp, Scale AI, and Synopsys — are integrating NIM into their platforms to speed generative AI deployments for domain-specific applications, such as copilots, code assistants, digital human avatars and more. Hugging Face is now offering NIM – starting with Meta Llama 3.

“Today we just posted up in Hugging Face the Llama 3 fully optimised, it’s available there for you to try. You can even take it with you,” Huang said. “So you could run it in the cloud, run it in any cloud, download this container, put it into your own data center, and you can host it to make it available for your customers.”

Nvidia’s RTX AI PCs, powered by RTX technologies, will enhance consumer experiences with over 200 RTX AI laptops and more than 500 AI-powered apps and games.

Project G-Assist, an RTX-powered AI assistant technology demo, was also announced, showcasing context-aware assistance for PC games and apps.

Microsoft and Nvidia are collaborating to help developers bring new generative AI capabilities to their Windows native and web apps with easy API access to RTX-accelerated SLMs that enable RAG capabilities that run on-device as part of Windows Copilot Runtime.

According to Huang, Nvidia is spearheading the $50-trillion industrial digitisation shift, with sectors embracing autonomous operations and digital twins – virtual models that enhance efficiency and cut costs. Through its Developer Program, Nvidia offers access to NIM.

Huang showcased Foxconn’s use of Nvidia Omniverse, Isaac and Metropolis to create digital twins, combining vision AI and robot development tools for enhanced robotic facilities.

“The next wave of AI is physical AI. AI that understands the laws of physics, AI that can work among us,” Huang said, emphasising the importance of robotics and AI in future developments.

The Nvidia Isaac platform provides a robust toolkit for developers to build AI robots, including AMRs, industrial arms and humanoids, powered by AI models and supercomputers like Jetson Orin and Thor.

“Robotics is here. Physical AI is here. This is not science fiction, and it’s being used all over Taiwan. It’s just really, really exciting,” Huang added.

Nvidia AI Enterprise on the IGX platform, with partners like ADLINK, Advantech and ONYX, delivers edge AI solutions meeting strict regulatory standards, essential for medical technology and other industries.