The Monthly Wrap

Catastrophic interference, also known as catastrophic forgetting, is the tendency of an  artificial neural network  to completely and abruptly forget previously learned information upon learning new information. Neural networks are an important part of the  network approach and connectionist approach  to  cognitive science . With these networks, human capabilities such as memory and learning can be modeled using computer simulations. Catastrophic interference is an important issue to consider when creating connectionist models of memory. It was originally brought to the attention of the scientific community by research from McCloskey and Cohen (1989), and Ratcliff (1990). It is a radical manifestation of the 'sensitivity-stability' dilemma or the 'stability-plasticity' dilemma. Specifically, these problems refer to the challenge of making an artificial neural network that is sensitive to, but not disrupted by, new information(see the diagram).  Lookup tables  and connec

There are already more linked devices than people in the world, and this number is growing. According to IDC, there will be 41.6 billion connected IoT devices, or "things," in the world by 2025.It also says that industrial and automotive equipment provide the largest possibility for connected "things," but that smart home and wearable gadgets will see rapid adoption in the near future.  According to Gartner, the enterprise and automotive industries will account for 5.8 billion devices this year, up nearly a quarter from last year.Because of the ongoing installation of smart metres, utilities will be the largest users of IoT. The second most common usage of IoT devices will be security devices such as intrusion detection and web cameras.The fastest-growing area will be building automation, which includes linked lighting, followed by automotive (connected autos) and healthcare (monitoring of chronic conditions).  Figure 1: IoT Market scale by 2021 Industry-specific of