Can Robots Make Decisions in Real Time? The Era of Physical AI Opened by 'InstinctFlash'

Imagine a robotic arm assembling complex parts in a factory. Suddenly, a person steps in front of it, or a part unexpectedly rolls off. What would happen if the robot couldn’t grasp the situation and stop or dodge within 0.1 seconds? Until now, many robots have operated only according to pre-set commands. But now, an era is approaching where AI acts as the ‘brain’ of the robot, enabling it to see situations and act immediately on its own.

‘InstinctFlash’, recently introduced in the developer community Hacker News, is a core technology for realizing this real-time intelligence for robots. Source: ShowHN:InstinctFlash–Run5Bworld-actionmodelsinrealtime…

Why is this important?

Until now, robots have had long “thinking times.” The process of capturing video with a camera, analyzing it to judge the situation, calculating the corresponding movement, and then delivering it was too slow. In particular, running a massive model with over 5 billion (5B) parameters—the figure that determines the intelligence of an AI model—on a small computer (edge hardware) inside a robot body was nearly impossible.

However, InstinctFlash helps robot AI models make immediate decisions in the field. This means that a robot’s ability to safely collaborate with people in real time or find its way autonomously in complex environments can be significantly improved. Its application range is extremely broad, from manufacturing and logistics to, in the long term, humanoid robots in our daily lives.

Easy to understand: The ‘Smart Little Chef’ Analogy

Let’s use an analogy. Suppose there is a ‘genius little chef’ who is very smart but reads books slowly. If they had to finish reading a thick book of recipes (the giant AI model) before starting to cook, the guests would all go hungry.

InstinctFlash is a system that provides a ‘speed cooking guide’ to this little chef.

1. Native Optimization: Summarizes the book’s contents in advance to help them read faster.
2. Few-step distillation: Compresses the recipes themselves so that results are produced after going through only a few steps by leaving only the core of the recipe. Source: GitHub - General-Instinct/InstinctFlash: High-Performance Serving…

As a result, the little chef can immediately serve warm dishes to guests using just the core summary they just read, without having to read the whole book. In this way, InstinctFlash plays the role of optimizing and executing massive AI models in real time according to the robot’s hardware situation. Source: GitHub - n26modi/InstinctFlash: High-Performance Serving Runtime for Robotics Models · GitHub

Current Situation: The Robot’s New Brain, Jetson Thor

Developers can use InstinctFlash on this powerful hardware to declare models, set up optimization plans, enter commands directly, or run models via Python code. Source: GitHub - General-Instinct/InstinctFlash: High-Performance Serving… It also supports FP8 (8-bit floating-point) arithmetic, balancing performance and efficiency. Source: GitHub - LH-and-FPGA/InstinctFlash · GitHub

How far will it develop?

In the future, robots will become smaller and lighter while getting smarter. In the past, robots needed to be connected to large external computers to perform complex calculations, but once high-performance runtimes like InstinctFlash become widespread, they will be reborn as ‘independent intelligent machines’ that can make all decisions by themselves. Source: Release InstinctFlash: complete Thor pipeline · General-Instinct/InstinctFlash

We can look forward to seeing the era of ‘true physical AI,’ where robots go beyond being machines that simply do what they are told, to understanding their surroundings and acting autonomously according to the situation.

References

1. ShowHN: InstinctFlash – Run 5B world-action models in real time on Jetson Thor - https://news.ycombinator.com/item?id=49802789
2. GitHub - General-Instinct/InstinctFlash: High-Performance Serving… - https://github.com/General-Instinct/InstinctFlash
3. GitHub - n26modi/InstinctFlash: High-Performance Serving Runtime for Robotics Models - https://github.com/n26modi/InstinctFlash
4. GitHub - LH-and-FPGA/InstinctFlash - https://github.com/LH-and-FPGA/InstinctFlash
5. Release InstinctFlash: complete Thor pipeline · General-Instinct/InstinctFlash - https://github.com/General-Instinct/InstinctFlash/releases/tag/thor-2026-09-15

6. Jetson Thor

   Advanced AI for Physical Robotics

   NVIDIA - https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/jetson-thor/