We combine the power of AI with the flexibility of edge computing to build smarter, more efficient technologies and devices.
AI models can be trained to do all kinds of smart things. The Cloud offers huge processing power for model training, but edge computing pushes the boundaries of what’s possible even further.
On the edge, the AI capability is combined with the physical device or hardware itself - no more sending information elsewhere. Using super low-cost solutions like the powerful but compact NVIDIA Jetson Nano, edge computing works upon data in the same location where it’s gathered. It means no time lags, no outages, no bandwidth limitations, but still all the powerful processing benefits you’d expect from the Cloud.
The applications are obvious in sectors like healthcare. Image classification, real-time object detection, speech and pressure monitoring – you name it. If you can imagine it, it’s likely that edge AI can make it work better.
We’re working with new generation hardware through our partnership with AI accelerators NVIDIA, deploying AI models to edge and IoT devices in innovative ways. Sensors, wearables, trackers, microcontrollers and more – edge computing makes it all faster, more reliable and much more secure.
We work with tiny hardware units (like Arduino) which can easily be embedded in portable AI enabled devices. In medical technology, wearables, and smart vehicles this is a game changer – new generation edge devices don’t rely on cumbersome fixed monitoring systems, or lots of battery power. Imagine an AI sensor working just as well on the move as within a fixed infrastructure like a hospital – that’s the power of the edge.[Read more about mobile AI devices]
When data doesn’t have to be sent over the internet to analyse and act upon it you get faster results, consistently, and regardless of connectivity. Edge computing allows a device itself to react instantaneously to real-time events. There’s no latency. It’s more efficient. This means that end user experiences are ultimately improved. Imagine the possibilities when every second counts - no lag between monitoring and medicine, or being able to get instant image classification by smarter security cameras. It’s all possible on the edge.[Read more about AI for healthcare]
Using the cloud for AI processing requires transmitting potentially sensitive data over the internet. Edge computing can remove overheads for the often huge privacy and security infrastructure this requires. Whether it’s patient medical records, or simply the facial recognition image used to unlock your phone, edge computing stores and acts upon this data locally. The analytical power is still there, but privacy is never compromised.[Read more about managing data with AI]
The hardware Fuzzy Labs work with is surprisingly low cost. We combine our hardware and innovation expertise with years of experience in advanced AI modelling, developing IoT and edge devices for every conceivable sector and location. Edge computing widens the marketplace for smarter tech. It’s small, but extremely powerful. And with our know-how? It’s accessible to all.[Read more about how we work]
Through our partnership with Nvidia, Fuzzy Labs are working right at the cutting edge of AI for edge computing. This accelerator programme means we understand innately what, how, and where edge computing can bring real benefits when speed, reliability, scale and mobility of processing really matter. Not only that, we have the skills to bring these exciting new ideas to life.
From the kernel of an idea, through to seeing it transform people’s lives, a custom approach is what we’re all about. The opportunities for progress through AI and edge computing are huge. What would that look like for your industry?