By Dr. Sakyasingha Dasgupta.
Edge computing will grow exponentially in the next few years, as more and more devices and applications demand low-latency, high-performance, and privacy-preserving computation at the edge of the network.
However, one of the biggest challenges facing edge computing is handling the increasing complexity and diversity of data sources and modalities, such as images, videos, audio, text, speech, and sensors. This challenge is where multimodal generative artificial intelligence (AI) comes into play.
Read the full blog here
By Dr. Sakyasingha Dasgupta.
Edge computing will grow exponentially in the next few years, as more and more devices and applications demand low-latency, high-performance, and privacy-preserving computation at the edge of the network.
However, one of the biggest challenges facing edge computing is handling the increasing complexity and diversity of data sources and modalities, such as images, videos, audio, text, speech, and sensors. This challenge is where multimodal generative artificial intelligence (AI) comes into play.
Read the full blog here