Intel Labs has developed one of the architectures in the field the Loihi neuromorphic chip

Scientists have tapped neuromorphic computing to keep robots learning about new objects after they've been deployed. It specifically targets future applications like robotic assistants that interact with unconstrained environments, including in logistics, healthcare, or elderly care. Intel Labs has developed one of the most notable architectures in the field the Loihi neuromorphic chip. Intel Labs, in collaboration with the Italian Institute of Technology and the Technical University of Munich, has introduced a new approach to neural network-based object learning.

Intel Loihi Neuromorphic Chip:

Loihi is comprised of around 130,000 artificial neurons, which send information to each other across a "spiking" neural network (SNN). The SNN representation is learned or updated. Lohi chip is based on Intel's 14nm technology and will house a core mesh that supports a wide range of neural network topologies. Further, it is up to 1,000 times more energy-efficient than general-purpose computing required for typical training systems. Loihi chips are particularly good at rapidly spotting sensory input like gestures, sounds, and even smells.

The chips had already powered a range of systems, from smart artificial skin to an electronic "nose" that recognizes scents emitted from explosives. The method targets systems that interact with unconstrained environments, such as future robotic assistants for healthcare and manufacturing. Using these new models, Intel and its collaborators successfully demonstrated continual interactive learning on Intel's neuromorphic research chip.

The researchers first implemented an SNN on Loihi. This architecture localizes learning to a single layer of plastic synapses. Their goal is to apply similar capabilities to future robots that work in interactive settings, enabling them to adapt to the unforeseen and work more naturally alongside humans. Intel believes that neuromorphic computing offers a way to provide exascale performance in a construct inspired by how the brain works.