Computer vision is a critical application that benefits from analogue AI accelerators. These accelerators can perform image processing tasks, such as object recognition and event detection, quickly and efficiently. This is useful in applications like security, surveillance, facial recognition, and augmented reality. In many of these applications’ privacy is key, so that edge computing ensures no personal data is transferred.

Autonomous vehicles require real-time processing of large volumes of data from sensors such as cameras, LIDAR, and radars. Analog AI accelerators can process these signals rapidly and with low latency, enabling quick and safe decision-making. This is crucial for navigation, obstacle detection, and autonomous driving.

In industrial and automotive applications, embedded systems require fast and efficient processing. Analog AI accelerators can be integrated into these systems for process control tasks, predictive maintenance, and real-time data analysis. The low latency and robustness of analogue accelerators make them ideal for demanding industrial environments.

In the aerospace and defence sectors, energy efficiency and processing speed are critical. Analog AI accelerators can be used in radar systems, communications, and navigation, providing advanced processing capabilities in energy- and space-constrained environments. It is worth highlighting the case of drones, as they use all kinds of sensors, especially cameras, and their energy constraints are the most significant.

Both industrial and service robots require advanced processing capabilities for navigation, object manipulation, and interaction with the environment. Analog AI accelerators can provide the speed and efficiency needed for these tasks, enhancing the performance and autonomy of robots.

Mobile devices and wearables greatly benefit from analog AI accelerators due to their energy and space constraints. These accelerators can perform tasks such as voice recognition, image processing, and real-time data analysis with minimal energy consumption, extending battery life and improving the user experience.

In healthcare, analogue AI accelerators can be used in portable medical devices for continuous patient monitoring. These devices can analyse biomedical signals, such as electrocardiograms (ECG) and electroencephalograms (EEG), in real time, providing early alerts and improving patient care. Additionally, they can be employed in medical imaging for rapid image analysis and disease detection. Finally, in hospital care applications they can be used to monitor and detect events in patients and devices.

In the energy sector, analogue AI accelerators can be used to analyse power supply signals at various points in transmission and distribution networks. It is also suitable to process information from home energy management systems and local energy communities, especially in systems not connected to the network.

In telecommunications, analogue AI accelerators can optimize spectrum management, signal processing, and network management. They can analyse and process large volumes of data efficiently, improving service quality and network capacity.