No Code Movement Hits the Embedded World
Thanks to the ever evolving AI landscape, you can now use model zoos to accelerate product developement
You probably already know what the no-code movement is, how it’s reshaping software development, and how platforms like Bubble have turned anyone with an idea into an app creator— drag, drop, click, and you’ve got yourself an app. It’s no longer a trend but a full-blown revolution. The stats back it up: a survey from Gartner indicated that about 60% of custom apps are built using no-code or low-code tools.
However, this shift isn’t limited to only software development anymore. The same philosophy that powered the no-code movement is now creeping into the embedded world.
With Model Zoos, the world of embedded AI is about to be cracked wide open. In the near future, edge AI devices won’t be the exclusive specialized domain it is now. Just like no-code platforms, Model Zoos are making AI models more plug-and-play and accessible.
What Are Model Zoos?
Model Zoos are libraries filled with pre-trained AI models, blueprints and datasets that simplify the process of building AI applications. Rather than building AI models from scratch, developers can select from a collection of models that have already been trained on large, diverse datasets. These pre-trained models can handle tasks like image recognition, speech analysis, or natural language processing, allowing developers to skip the heavy lifting of model training.
It is easy to run advanced AI models in the cloud, since they operate on standardized platforms with vast computing resources. However, deploying them to edge devices—like smart cameras, sensors, or wearable tech is a different story. Edge devices are constrained by limited processing power, specialized hardware, and the need for power efficiency. So, while developers won’t build the models from the ground up, they will almost always need to fine-tune them to suit the specific limitations of the hardware.
Although this requires some technical input, it’s nowhere near the level of expertise needed to build the model from scratch. Therefore, Model Zoos are to AI what no-code platforms are to software development—bringing the technology within reach for more innovators. Fine-tuning on edge devices feels more like tweaking the settings than deep programming. So, it still keeps the “plug-and-play” philosophy alive.
The Potential of Model Zoos for Edge AI
Model Zoos, which are collections of pre-trained AI models, offer a glimpse into a future where developing AI on edge devices could become faster and more efficient. At present, the available models and support for all hardware platforms are limited, and only a few edge devices are fully compatible with these pre-built solutions.
Looking ahead, the goal is to expand the range of supported platforms and streamline the process so that developers can easily mix and match AI models with different hardware. As more companies invest in this space and as the technology evolves, the flexibility and ease of use of this technology will likely become the norm.
In the near future, we can expect a shift where not just developers but the community at large—including enthusiasts from the TinyML movement—will play a key role in contributing models, frameworks, blueprints and datasets to Model Zoos.
This collaborative effort will be vital to expanding the reach and effectiveness of edge AI. Much like how Original Design Manufacturers (ODMs) create basic hardware designs that other companies customize and enhance, Model Zoos will provide foundational AI models and reference designs that businesses can modify to suit their own specific needs and add value on top of a standard base.
Security Concerns in Embedded Edge AI Development
As powerful as Model Zoos are in simplifying AI deployment, they also bring unique challenges, especially around security. Embedding AI into devices means these devices will be processing real-world data at the edge, often in less secure environments compared to centralized cloud systems. While this opens up exciting possibilities for faster and more efficient data processing, it also introduces potential vulnerabilities.
One common security risk is model poisoning, where attackers could potentially manipulate pre-trained AI models. As more businesses rely on AI for decision-making and handling sensitive data, ensuring the integrity of these models will become increasingly critical. In the future, we can expect more rigorous testing and encryption to protect the AI models within Model Zoos.
Another concern is the way data is handled at the edge. Unlike cloud-based AI, edge AI processes data locally, which reduces reliance on sending information over networks but places more responsibility on device-level security. Encrypting data and securing firmware updates will be essential as these devices grow in use.
Why Businesses Should Act Now
The no-code revolution in software development has shown us how simplifying complex processes can spark innovation on a large scale. In the embedded systems world, Model Zoos are doing the same for AI development. Although not yet fully realized, emerging platforms like ModelNova from embedUR are setting the stage for businesses to accelerate their AI development without needing to build models from scratch.
With edge AI becoming a defining factor for the next generation of smart devices, businesses that adopt these tools now will be able to innovate faster and bring their products to the market faster, and get an edge on less agile competitors.
Moreover, silicon vendors working on AI-native hardware also stand to gain when they collaborate with solutions like ModelNova. By having their latest AI chips optimized for ModelNova’s library of AI models, they ensure that their hardware is ready for rapid AI deployment and make their products more attractive to businesses eager to dive into the edge AI space.
Now that speed and efficiency dictate success, the question isn’t whether businesses should embrace Model Zoos—it’s when. And with ModelNova, that moment is now. Partner with embedUR today to unlock the full potential of edge AI and drive your products to market at lightning speed. Read more on how Model Zoos are set to simplify Edge AI App developement.
