Deploying Artificial Intelligence At The Edge

Rapid advances in artificial intelligence (AI) have made this technology important for many industries, including finance, energy, healthcare, and microelectronics. AI is driving a multi-trillion-dollar global market while helping to solve some tough societal problems such as tracking the current pandemic and predicting the severity of climate-driven events like hurricanes and wildfires. Today, AI algorithms are primarily run at large data centers, that is in the cloud. For this intelligence to be used at the edge, data must be transmitted to the cloud, analyzed there, and the results transmitted back to the edge – a device in the field of operation, whether it is a sensor tracking the strength of a bridge, a mobile phone, a medical implant, or an autonomous vehicle. The problem with the current approach of using AI primarily in the cloud is that it consumes much energy and can introduce data transmission delays and security vulnerabilities.