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If you’ve ever tried to hold a conversation with a chatbot like Clever Bot, you know how quickly the conversation turns to nonsense, no matter how hard you try to keep it together.But now, a research team led by Bruno Golosio, assistant professor of applied physics at Università di Sassari in Italy, has taken a significant step toward improving human-to-computer conversation.Golosio and colleagues built an artificial neural network, called ANNABELL, that aims to emulate the large-scale structure of human working memory in the brain — and its ability to hold a conversation is eerily human-like.

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The field is known as natural language processing (NLP), and although amateurs and professionals enter their best NLP programs into competitions every year, the past seven decades still haven’t produced a single NLP program that allows computers to consistently fool questioners into thinking they’re human.

NLP has attracted a wide variety of approaches over the years, and linguists, computer scientists and cognitive scientists have focused on designing so-called symbolic architectures, or software programs that store units of speech as symbols.

It’s an approach that requires a lot of top-down management.

Another school of thought, the “connectionist approach,” holds that it’s more effective to process language via artificial neural networks (ANNs).

These computerized systems begin as blank slates, and then they learn to associate certain speech patterns with clusters of interconnected processing units.

This open-ended structure enables ANNs to build connections on the fly, with very little direct supervision — in much the same way a human brain does.

The crucial distinction between the two approaches is that symbolic architectures require specific rules in order to make decisions, while ANNs aren’t as beholden to rigid structures.

Instead of checking whether an answer is right or wrong, ANNs choose the answer that’s Inspired the successes of earlier ANNs, Golosio and his team engineered a brand-new type of ANN known as ANNABELL (Artificial Neural Network with Adaptive Behavior Exploited for Language Learning).

The team designed ANNABELL to be able to pick up language by building a system of interconnected associations from scratch, in the same way a human infant does.

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