‘Tis the season to ponder what to get that someone in your life who has everything. If you haven’t finished your Christmas shopping and have $249 to spend for a piece of technology about four inches wide, three-and-a-half inches high, and 1.3 inches thick, then Nvidia Corp. has the perfect gift.

The tech giant introduced the Jetson Orin Nano Super Developer Kit this week. Though that’s a big name for such a small product, don’t be fooled. The latest innovation from Nvidia packs a big wallop in its little package.

The Jetson Orin Nano Super Developer Kit is a small but mighty artificial intelligence computer that the company says “redefines AI for small edge devices.” And by mighty, the new product delivers up to 67 tera operations per second of AI performance. That’s a 1.7-times increase over its predecessor, the Jetson Orin Nano.

But if you already bought the original model, which sold for $499 and debuted just 18 months ago, don’t worry. The team at Nvidia isn’t pulling a Grinch move. A free software upgrade for all original Jetson Orin owners turns those devices into the new Super version.

What’s in the box?

The developer kit comprises an 8-gigabyte Jetson Orin Nano module and a reference carrier that accommodates all Orin Nano and Nvidia Orin NX modules. The company says this kit is “the ideal platform for prototyping your next-gen edge-AI product.”

The 8GB module boasts an Ampere architecture graphics processing unit and a six-core Arm central processing unit, which enables multiple concurrent AI application pipelines. The platform runs Nvidia AI software stack and includes application frameworks for multiple use cases, including robotics, vision AI and sensor processing.

Built for agentic AI

Deepu Talla, Nvidia’s vice president and general manager of robotics and edge computing, briefed industry analysts before the Dec. 17 announcement. He called the new Jetson Orin Nano Super Developer Kit “the most affordable and powerful supercomputer we build.” Talla said the past two years saw generative AI “take the world by storm.” Now, he said, we’re witnessing the birth of agentic AI.

“With agentic AI, most agents are in the digital world. And the same technology now can be applied to the physical world, and that’s what robotics is about,” he said. “We’re taking the Orin Nano Developer Kit and putting a cape on it to make it a superhero.”

And what superpowers will the Jetson Orin Nano Super Developer Kit have? In addition to increasing performance from 40 to 67 TOPS, the new kit will have much more memory bandwidth — from 68 to 102 gigabytes per second, a 70% increase.

“This is the moment we’ve been waiting for,” said Talla. Nvidia is increasing performance significantly on the same hardware platform by supercharging the software. “We designed [the original Orin Nano system] to be field upgradeable. As generative AI became popular and we did all the different testing, we can support all the old systems in the field without changing the hardware, just through software updates.”

On the call, Talla mentioned that the total available market for robots, also known as physical AI, is about half the world’s gross domestic product, or about $50 trillion. Is it that big? It’s hard to quantify, but I do believe the opportunity is massive. Robots represent the next frontier in agentic AI because they combine a physical form factor with advanced decision-making capabilities, bridging the gap between virtual intelligence and the real world.

Unlike purely virtual AI systems, robots can interact with their environment, perform tasks and adapt to dynamic situations, making them critical for solving complex real-world problems. Their ability to act autonomously while continuously learning from their surroundings allows them to tackle challenges that are difficult for traditional software and sometimes people.

In fields such as healthcare, logistics, retail and manufacturing, robots are already demonstrating their potential by automating repetitive tasks, improving precision and enhancing efficiency. As advancements in machine learning, computer vision, and natural language processing continue, robots will become more capable of understanding and responding to human needs with nuance. They can assist the elderly, manage warehouses or even conduct surgeries accurately and consistently, surpassing human capabilities.

Additionally, as robots gain greater autonomy, they will increasingly function as agentic AI — intelligent agents capable of making decisions, setting goals and pursuing actions without constant human oversight. This shift will unlock new possibilities in sectors such as exploration, disaster response and personal assistance, transforming robots into valuable partners for human endeavors. The convergence of AI, robotics, and automation is poised to redefine industries and everyday life.

One of the biggest challenges and expenses with robots is to train them. Creating all the possible scenarios to test a physical robot can take years. For example, teaching a robot to walk requires stairs, gravel roads, side hills and other scenarios. They can fall, get damaged, overheat or experience other events slowing training. Nvidia takes a “full stack” approach to physical AI, where training can be done virtually using synthetic data. When the training is complete, upload the information so the robot can do the tasks.

Planned rejuvenation

Many products that hit the market have been designed with planned obsolescence in mind, whether by design or just due to rapidly evolving technologies and components. Nvidia is doing the opposite. Call it “planned rejuvenation.”

Talla said this is possible because Nvidia designed the Jetson architecture to support faster performance. “We are increasing the frequency of the memory,” he said. “We are increasing the frequency of the GPU. In fact, we are also slightly increasing the frequency of the CPUs. And the power consumption will go up to 25 watts. But the hardware has been designed to support that already.” Jetson runs Nvidia AI software, including Nvidia Isaac for robotics, Nvidia Metropolis for vision AI, and Nvidia Holoscan for sensor processing.

These preconfigured kits are also part of why Nvidia has become the runaway leader in AI. Packaging up all the hardware and software required for a developer to get started significantly reduces development time. Nvidia’s peers offer many of the same building blocks, but the developer must put them together.

The new Jetson Orin Nano Super Developer Kit and software upgrades for owners of the original Jetson Orin Nano Developer Kit are available at nvidia.com.

Zeus Kerravala is a principal analyst at ZK Research, a division of Kerravala Consulting. He wrote this article for SiliconANGLE.

Photo: Nvidia