The satellite has just learned how to find things on its own, and this is what that means

For the first time, an Earth observation satellite found what it was looking for, on its own, without human analysts on the ground. The milestone, which occurred in April, marks the first reported use of a vision language model in orbit, and offers a glimpse into how artificial intelligence could fundamentally change what space sensors are capable of doing — and how valuable they are.

Typically, satellites download large amounts of data to analysts on the ground below, who use machine learning algorithms or their own eyes to figure out what’s going on. But on board the Yam-9 spacecraft, built by the Space Infrastructure Corporation Orbital lofta software package created by NASA’s Jet Propulsion Laboratory, identified areas of interest in response to natural language queries.

Google DeepMind’s Gemma 3 — the vision language model, or VLM, that powers the demo — is specifically designed for edge applications, meaning it’s designed to run on limited hardware far from the data center. VLMs combine the contextual understanding of large language models with the ability to analyze images: researchers asked the model to classify sensor data where the natural environment meets human development, for example, or to identify infrastructure around railway axes – and it did so.

The demonstration is important for two reasons. In the near term, space sensors could be made much more useful by performing preliminary data sorting in orbit, reducing the stream of raw data that analysts currently have to wade through. In the long term, it’s a proof point toward operating large-scale AI infrastructure in space.

“It opens the door to always-on patrol layers in space,” Paul Lasserre, head of AI at LOFT, told TechCrunch. “If you have a VLM, you can have logic — like ‘monitor this border for me, tell me when something is suspicious,’ and interact back and forth with the satellites.”

Loft’s spacecraft are designed as platforms for third-party clients. The business model is closer to infrastructure as a service than traditional satellite manufacturing. One recent deal saw the construction, launch and operation of six new satellites for EarthDaily, which will analyze and commercialize data collected on board the spacecraft. Launched in the fall of 2025 as an explorer for the company’s orbital AI projects, Yam-9 includes the Nvidia Jetson Orrin AGX GPU, one of the leading chips used in space computing.

Juan Delva Victoria, technical lead at NASA’s Jet Propulsion Laboratory’s Artificial Intelligence Group, led the development of NAVI-Orbital, a software package that served as an instrumental tool for the Gemma 3 VLM. While Gemma 3 was ready, software engineers had to simplify the software package to reduce the amount of libraries and memory it would require.

While this is the first reported use of a VLM in orbit, we can expect other companies to follow suit. Planet Labs flies satellites using Jetson Orin processors; Right now, they’re being used for simpler object detection tasks, but a spokesperson says research is underway on other AI applications, including VLMs.

Kepler Communications, which operates The largest collection of GPUS In space, it declined to say whether it has deployed VLM hardware in space due to NDA agreements with partners, but noted there have been “many unannounced use cases for our computing environment” since those spacecraft launched in January.

“Now that we’ve proven the concept, this is really the direction of travel,” Lasser said. The goal is to build the constellation to ensure real-time coverage of anywhere on Earth, which he says will take between 50 and 100 satellites like Yam-9. (Loft currently operates 12 spacecraft in orbit.)

Lessons learned from deploying these smaller models in orbit will inform how companies attempt to deploy large-scale computing infrastructure in space, especially in simple and critical areas such as power and memory management.

They can also pave the way for new scientific tools. The idea for NAVI-Space started with JPL researcher Taran Cyriac John, who was thinking about digital assistants for astronauts exploring the Moon or Mars.

“We’re thinking, ‘Okay, you’ve got astronauts in pressurized suits, and you know they can’t hit a keyboard, everything they want to do is complicated.’ Delva Victoria said. “So, how about we introduce an assistant, like in video games and movies, where you see interactive AI?”

Just don’t call it HAL 9000.