In 2019, AI meets IoT at the edge computing layer. Most of the models trained in the public cloud will be deployed at the edge.
Industrial IoT is the top use case for artificial intelligence that can perform outlier detection, root cause analysis and predictive maintenance of the equipment.
Advanced ML models based on deep neural networks will be optimized to run at the edge.
They will be capable of dealing with video frames, speech synthesis, time-series data and unstructured data generated by devices such as cameras, microphones, and other sensors.
IoT is all set to become the biggest driver of artificial intelligence in the enterprise.
Edge devices will be equipped with the special AI chips based on FPGAs and ASICs.
Early indicators – Support for ML inferencing at the edge by AWS Greengrass, AI Toolkit for Azure IoT Edge, Google Cloud IoT Edge, FogHorn Lightning Edge Intelligence, andProject Flogo by TIBCO.
