Geoffrey Hinton and Demis Hassabis: AGI is nowhere close to being a reality

That's just a sampling of artificial intelligent (AI) systems' achievements in 2018, and evidence of how rapidly the field is advancing. At the current pace of change, analysts at the McKinsey Global Institute predict that, in the U.S. alone, AI will help to capture 20-25 percent in net economic benefits (equating to $13 trillion globally) in the next 12 years. Some of the most impressive work has arisen from the study of deep neural networks (DNNs), a category of machine learning architecture based on data representations. They're loosely modeled on the brain: DNNs comprise artificial neurons (i.e., mathematical functions) connected with synapses that transmit signals to other neurons. Said neurons are arranged in layers, and those signals -- the product of data, or inputs, fed into the DNN -- travel from layer to layer and slowly "tune" the DNN by adjusting the synaptic strength -- weights -- of each neural connection. Over time, after hundreds or even millions of cycles, the network extracts features from the dataset and identifies trends across samples, eventually learning to make novel predictions.