Until now, Artificial Intelligence has largely relied on cloud computing, which offers virtually unlimited computational power: this is advantageous when it comes to training data-heavy AI models in a reasonable amount of time and making inferences with reduced latency.
The AIaaS-Business models also guarantee a maximum cost-effectiveness: all power is only paid according to its specific use. Together with very high availability or minimum downtimes, these characteristics have made the cloud a natural choice for AI services.
Sometimes, however, the cloud cannot be considered as an option. For instance, in cases where data protection considerations prevent the storage of personal data in a central repository, or when latency is crucial, e.g. in medical or transportation or robotics contexts. Furthermore, mobile deployment in areas without a network connection, whether underground, in outer space or in many rural areas even in industrialised countries, is not possible if the solution is completely dependent on a connection to the cloud service.
All these issues can be solved by adopting the Edge AI paradigm: Reply, thanks to its technical expertise, can support companies in exploiting the full potential of this new solution by guiding them in choosing the Edge devices best suited to their needs.
Reply has gained considerable experience and technical expertise in the Edge AI landscape through numerous projects, using Autonomous Mobile Robots and drones in various scenarios. In combination with Computer Vision technology and advanced Machine Learning models, the autonomy enabled or supported by AI on Edge can further promote high precision automation in defect detection, increasingly accurate predictive maintenance scenarios, Warehouse and Facility Management, including revolutionary approaches to Building Information Modeling with LIDAR 3D generated Digital Twins.
In addition, AI can help to improve the user experience by safeguarding personal data, processing them on the device instead of transferring them to a cloud centric service.