This sounds like the periodic resurgance of interest in neural nets that has been going on for decades. While our brains do well with neural nets, they use a lot of neurons and a lot of synapses to figure out patterns. Once the pattern is understood: "IF the temperature rises quickly THEN ring the fire alarm", it can be programmed on a trivially simple logic gate. I think that neural nets often are used to address problems which are not well understood and the programming of the neural nets is not well understood either. Knowing what we want and finding an efficient way to get to the intended destination is more likely to lead to programming success.
It's great to see experimentaiton in architectures. However these usually come at the cost of needing a whole new programming approach which means outside of the chip devekopers, no one knows how to write software for this beast yet.
Drones are, in essence, flying autonomous vehicles. Pros and cons surrounding drones today might well foreshadow the debate over the development of self-driving cars. In the context of a strongly regulated aviation industry, "self-flying" drones pose a fresh challenge. How safe is it to fly drones in different environments? Should drones be required for visual line of sight – as are piloted airplanes? Join EE Times' Junko Yoshida as she moderates a panel of drone experts.