&gt;&gt; The ressurgence of AI is just as hyped as expert systems and logic computers in the 1980.<p>Yep, for instance see how recent results are advertised as showing that machine
learning algorithms are &quot;better than humans&quot; in various tasks (image
recognition, primarily).<p>The thing to keep in mind is that all that old tech did not &quot;fail&quot; as is often
assumed. Expert systems worked perfectly fine, as did a host of other GOFAI
techniques. It&#x27;s all waiting for us just as the researchers left it when they
jumped overboard to fields that still had funding, kind of like a Mary Celeste
of science.<p>My hope is that rather than going through another AI winter we can find a way to
pick it all up where the 80&#x27;s and the 90&#x27;s left it and advance the science
further, absolutely so while keeping the best bits of the current machine
learning explosion. Machine learning is not a new thing anyway- it too goes back
in the early days of AI. We have more data and more computational power today,
but there&#x27;s practically no really new approaches - Deep learning, SVMs, Decision
Trees... those are not really &quot;new&quot; as such, it&#x27;s just their popularity that is
a new thing.<p>So we&#x27;re at a point where we need to learn our history, before we end up
repeating it unwittingly. And we can- we have theoretical foundation, we have
practical approaches, we can put the two together and win.