Connectionist Approaches

Today’s AI technology, Machine Learning, is radically different from the old days.

ML applications are ubiquitous and already credited with changing the way we live in many ways. Clearly it is here to stay. Machine Learning’s successes have been so widely publicized that the term has become nearly synonymous with Artificial Intelligence.  But “learning” here does not mean acquiring knowledge but rather “training” huge networks of interconnected “artificial neurons” to recognize patterns in vast databases.  These approaches are called connectionist AI.

Even its most ardent practitioners freely admit that connectionist approaches cannot understand our language and lack general intelligence.

None of the AI techniques we have can build representations of the world, whether through structure or through learning, that are anywhere near what we observe in animals and humans…The crucial piece of science and technology we don’t have is how we get machines to build models of the world…The step beyond that is common sense, when machines have the same background knowledge as a person.

Yann LeCun, Director of AI at Facebook

Ultimately, the real challenge is human language understanding – that still doesn’t exist. We are not even close to it…

Satya Nadella, Microsoft CEO

I think we need to consider the hard challenges of AI and not be satisfied with short-term, incremental advances. I’m not saying I want to forget deep learning. On the contrary, I want to build on it. But we need to be able to extend it to do things like reasoning, learning causality, and exploring the world in order to learn and acquire information.

Yoshua Bengio, deep learning pioneer

I’ll be honest with you, I believe that solving language is equivalent to solving general artificial intelligence. I don’t think one goes without the other.

Manuel Mogenet, Head of Google Research Europe

Despite all of the problems I have sketched, I don’t think that we need to abandon deep learning. Rather, we need to reconceptualize it: not as a universal solvent, but simply as one tool among many, a power screwdriver in a world in which we also need hammers, wrenches, and pliers, not to mention chisels and drills, voltmeters, logic probes, and oscilloscopes.

Gary Marcus, Former head of AI at Uber