In theory, Gamalon’s approach could make it a lot easier for someone to build and refine a machine-learning model, too. Perfecting a deep-learning algorithm requires a great deal of mathematical and machine-learning expertise. “There’s a black art to setting these systems up,” Vigoda says. With Gamalon’s approach, a programmer could train a model by feeding in significant examples.
Source: AI Software Juggles Probabilities to Learn from Less Data
