Artificial Intelligence and inference are approaching a point of mass implementation in every day devices, from hearing aids and medical devices, to cars and sensors. Read insights in conversation with the visionaries on a mission to enable the conversion of raw data into actionable knowledge and wisdom within smart-devices at the network’s edge.
“Computation does not require energy, only the movement of data” – In Conversation with Alexandra Pinto, CEO, Hoursec
Energy efficiency is all anyone talks about these days: rightfully so. As we squeeze as much juice as we can extract from this planet, to thrive on our survival, we must then find sustainable solutions that can satiate a global regime based on growth. Now, to begin this article I should explain the titled quote…
Realising the vision for enabling adaptive learning at the edge: In conversation with Gordon Wilson, CEO, Rain Neuromorphics
Among one of the bottlenecks to enabling ever-increasing intelligence at the edge of the network, is the cost of enabling machine-learning capabilities. For a number of reasons (ranging from size of the algorithmic learning models, software, the available hardware, the network bandwidth transmitting data between cloud and edge, and training challenges at the edge), enabling…
Intelligence at the Edge Explained: In Conversation with Altaf Khan, CEO, Infxl
In the foundational conversation kicking off the “Intelligence at the Edge” series, I sat down with Chief Executive Officer of Infxl, Altaf Khan, whose company develops hardware-agnostic, ultra-low-power, ultra-low-latency machine learning (ML) solutions for the edge. What this means is he’s achieved a way of mechanically reaching a conclusion from a shed load of digital information a…
Digital Anthroconomy 