A new AI model replaces months of simulation with near-instant predictions, changing how spacecraft operations are prepared
Updated
April 24, 2026 10:53 AM
Northrop Grumman Stargaze serves as the mother ship for the Pegasus, an air-launched orbital rocket. PHOTO: UNSPLASH
Flexcompute, a startup that builds software to simulate real-world physics, is working with Northrop Grumman to change how space missions are prepared. Together, they have developed an AI-based system that can predict how spacecraft respond during critical manoeuvres such as docking—when one spacecraft moves in and connects with another in orbit. These steps have traditionally taken months of preparation.
At the centre of this work is a long-standing problem in space operations. When a spacecraft fires its thrusters, the exhaust plume interacts with nearby surfaces. These interactions can affect movement, temperature and stability. Because these effects are difficult to test in real conditions, engineers have relied on large volumes of computer simulations to estimate outcomes before a mission. That process is slow and resource-intensive.
The new system replaces much of that workflow with a trained AI model. Instead of running millions of simulations, the model learns patterns from physics-based data and can make predictions in seconds. It also provides a measure of uncertainty, which helps engineers understand how reliable those predictions are when making decisions.
"At Northrop Grumman, we're pioneering physics AI to accelerate design and solve complex simulation and modelling problems like plume impingement—critical for station keeping, rendezvous and space robotics. Simply put: we're pushing the boundaries of advanced space operations", said Fahad Khan, Director of AI Foundations at Northrop Grumman. "Partnering with Flexcompute and NVIDIA, we're accelerating innovation and mission timelines to deliver superior space capabilities for customers at the speed they need".
The system is built using technology from NVIDIA, which provides the computing framework behind the model. Flexcompute has adapted it to handle the specific challenges of spaceflight, including how gases expand and interact in a vacuum. The result is a tool that can simulate complex scenarios much faster while maintaining the level of accuracy needed for mission planning.
By shortening preparation time, the model changes how engineers approach spacecraft design and operations. Faster predictions mean teams can test more scenarios and adjust plans more quickly. It also helps improve fuel use and extend the lifespan of spacecraft.
"Northrop Grumman's confidence reflects what sets Flexcompute apart", said Vera Yang, President and Co-Founder of Flexcompute. "We are able to take the most accurate and scalable physics foundations and evolve them into highly trained, customized Physics AI solutions that engineers can rely on. This work shows how we are transforming the role of simulation, not just speeding it up, but expanding what engineers can confidently solve and how quickly they can act".
The collaboration points to a broader shift in how engineering problems are being handled. Instead of relying only on detailed simulations that take time to run, companies are beginning to use AI systems that can approximate those results quickly while still reflecting the underlying physics.
"The industry's most ambitious space missions now demand a level of speed and precision that traditional engineering cycles can no longer sustain", said Tim Costa, vice president and general manager of computational engineering at NVIDIA. "By integrating NVIDIA PhysicsNeMo, Northrop Grumman and Flexcompute are transforming complex simulations like plume impingement from days of compute into seconds of insight, drastically accelerating the path from mission concept to orbit".
What emerges from this work is a shift in how missions are prepared. When prediction cycles move from months to seconds, testing and decision-making can happen faster. For space operations, where timing and precision are closely linked, that change could reshape how systems are built and run.
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From plush figures to digital pets, a new class of AI toys is emerging — built not around screens or sensors, but around memory, language and emotional awareness
Updated
March 17, 2026 1:02 AM
Spielwarenmesse toy fair. PHOTO: SPIELWARENMESSE
Spielwarenmesse in Nuremberg is the global meeting point for the toy industry, where brands and designers preview what will shape how children play and learn next. At this year’s fair, one message stood out clearly: toys are no longer built just to entertain, but to listen, respond and grow with children. Tuya Smart, a global AI cloud platform company, used the event to show how AI-powered toys are turning familiar formats into interactive companions that can talk, react emotionally and adapt over time.
The company’s central argument was simple but far-reaching. The next generation of artificial intelligence toys will not be defined by motors, sensors or screens alone, but by how well they understand human behavior. Instead of being single-function objects, smart toys for children are becoming systems that combine language models, emotion recognition and memory to support ongoing interaction.
One of the most talked-about examples was Tuya Smart’s Nebula Plush AI Toy. At first glance, it looks like a soft, expressive plush figure. Inside, it uses emotional recognition to change its LED facial expressions in real time. If a child sounds sad or excited, the toy’s eyes respond visually. It supports natural conversation, reacts to hugs and touch and combines storytelling, news-style updates and interactive games. Over time, it builds memory, allowing it to behave less like a gadget and more like an interactive AI toy that recalls past interactions.
Another example was Walulu, also developed using Tuya’s AI toy platform. Walulu is an AI pet built around personalization. It can detect up to 19 emotional states and speak more than 60 languages. It connects to major large language models such as ChatGPT, Gemini, DeepSeek, Qwen and Doubao. Through simple app-based controls, users choose traits like cheerful, quiet, curious or thoughtful. Those choices shape how Walulu talks and reacts. Instead of repeating scripts, it adjusts its tone and behavior over time. The result is not a novelty item, but an emotionally responsive AI toy that feels consistent in daily use.
Tuya also showed how educational AI toys can extend into learning and exploration. Its AI Learning Camera blends computer vision with interactive content. When it recognizes an object, it links it to cultural and learning material. If a child points it at a foreign word, it offers real-time pronunciation and translation. It can also turn drawings into digital artwork, encouraging active creativity rather than passive screen time. In this sense, AI toys for kids are becoming tools for learning as much as play.
These products point to a larger strategy. Tuya is not just making toys — it is building the AI toy development platform behind them. Through its AI Toy Solution, developers can design a toy’s personality, memory logic and behavior without training models from scratch. The system integrates with leading AI models and supports multi-turn conversation and emotional feedback, turning standard hardware into responsive AI companions.
The platform supports multiple development paths. Brands can use ready-to-market OEM solutions, add AI to existing products or build custom toys around their own characters. Plush toys, robots, educational tools and wearables can all become AI-powered toys without changing their physical design.
Because these products are made for children and families, safety is built in. Tuya’s system includes parental controls, conversation history review and content management. It supports standards such as GDPR and CCPA with encryption and data localization.
From a business standpoint, Tuya’s pitch is speed and scale. The company says its AI toy infrastructure can cut development time by more than half and reduce R&D costs by up to 50 percent. Its AIoT network spans over 200 countries and supports more than 60 languages, making global deployment of AI toys easier.
What emerged at Spielwarenmesse 2026 was not just a lineup of smart gadgets, but a clear shift in the category. AI toys are evolving into emotionally aware systems that talk, listen, remember and adapt. Their value lies not in sounding clever, but in fitting naturally into everyday life.
The fair did not present AI toys as a distant future. It showed them as products already entering the mainstream. The real question now is not whether toys will use AI, but how carefully that intelligence is designed for children.