Visit us at MedtecLIVE in Nuremberg from May 23 to 25, 2023.Solectrix lecture at MedConf 2023
Marcus Wawrik will hold a lecture at MedConf in Munich, which takes place from May 23 to 25, 2023.
AI Model Design • Application Development • System Implementation
Solectrix can handle or assist you with all steps of the AI development process. From setting up a prototype AI for smart data acquisition, guiding the machine learning process, to the eventual compilation of the optimized AI model to an FPGA, the creation of a supplementing embedded application or even the entire embedded system – we are here to help you every step of the way!
AI technology is already shaping various markets that we at Solectrix operate in. One example are Advanced Driver Assistance Systems.
In such applications, machine learning methods based on artificial neural networks, known as “Deep Learning”, can be used to train an AI that reliably detects pedestrians, bicycles, cars or road signs in complex traffic situations. Such an AI can be implemented as an edge device in passenger cars or as part of an intersection assistant system in trucks and buses.
The World Seen Through the Eyes of an AI
A digital eye captures a traffic scene and sends the data to an intelligent control unit – the “brain”. The brain processes and interprets the data, then generates a virtual image of the surroundings with classified objects. The resulting knowledge of the surroundings can be used to alert the driver to critical situations or to serve as an information source for the routing decisions of a self-driving car.
How it works: Teaching the AI what to look for in an image
This level of image recognition is achieved through complex neural networks. The machine learning process used to develop such an AI involves databases with millions of tagged images, making the AI model figure out what differentiates a car from a bus, or a child from a dog. Over time, the AI model learns which image characteristics are linked to a dedicated object type, ultimately arriving at the best possible set of transfer functions for the target application’s convolutional neural network.
Implementing AI in an Embedded Project
Our Preferred FPGA Platforms
The heart of our AI-powered systems is usually a powerful System-on-a-Chip (SoC) by Xilinx. These two are our chips of choice:
Both the Zynq-7000 and the UltraScale+ MPSoC series combine ARM CPUs with programmable logic components – they are system cores with an FPGA built-in!
Functions Implemented in FPGA
The FPGA component of the SoC handles the following tasks:
Solectrix can handle or assist you with all steps of the AI development process.
The Solectrix AI Ecosystem is an original development platform for convolutional neural networks, an advanced toolset to train a Deep Learning model. Its main fields are: