Ask HN: Will there ever be a resurgence of interest in symbolic AI?
It&#x27;s really hard to make predictions... especially about the future.[1] But to the extent that I have anything to say about this, I&#x27;ll offer this:<p>1. For all the accomplishments made with Deep Learning and other &quot;more modern&quot; techniques (scare quotes because deep learning is ultimately rooted in ideas that date back to the 1950&#x27;s), one thing they don&#x27;t really do (much of) is what we would call &quot;reasoning&quot;. I think it&#x27;s an open question whether or not &quot;reasoning&quot; (for the sake of argument, let&#x27;s say that I really mean &quot;logical reasoning&quot; here) can be an emergent aspect of the kinds of processes that happen in artificial neural networks. Perhaps if the network is sufficiently wide and deep? After all, it appears that the human brain is &quot;just neurons, synapses, etc.&quot; and we manage to figure out logic. But so far our simulated neural networks are orders of magnitude smaller than a real brain.<p>2. To my mind, it makes sense to try and &quot;shortcut&quot; the development of aspects of intelligence that <i>might</i> emerge from a sufficiently broad&#x2F;deep ANN, by &quot;wiring in&quot; modules that know how to do, for example, first order logic or $OTHER_THING. But we should be able to combine those modules with other techniques, like those based on Deep Learning, Reinforcement Learning, etc. to make hybrid systems that use the best of both worlds.<p>3. The position stated in (2) above is neither baseless speculation &#x2F; crankery, nor is it universally accepted. In a recent interview with Lex Fridman, researcher Ian Goodfellow seemed to express some support for the idea of that kind of &quot;hybrid&quot; approach. Conversely, in an interview in Martin Ford&#x27;s book <i>Architects of Intelligence</i>, Geoffrey Hinton seemed pretty dismissive of the idea. So even some of the leading researchers in the world today are divided on this point.<p>4. My take is that neither &quot;old skool&quot; symbolic AI (GOFAI) nor Deep Learning is sufficient to achieve &quot;real AI&quot; (whatever that means), at least in the short-term. I think there will be a place for a resurgence of interest in symbolic AI, in the context of hybrid systems. See what Goodfellow says in the linked interview, about how linking a &quot;knowledge base&quot; with a neural network could possibly yield interesting results.<p>5. As to whether or not &quot;all of intelligence&quot; including reasoning&#x2F;logic could simply emerge from a sufficiently broad&#x2F;deep ANN... we only just have the computing power available to train&#x2F;run ANN&#x27;s that are many orders of magnitude smaller than actual brains. Given that, I think looking for some kind of &quot;shortcut&quot; makes sense. And if we want a &quot;brain&quot; with the number of neurons and synapses of a human brain, that takes forever to train, we already know how to do that. We just need a man, a woman, and 9 months.<p>[1]: <a href="https:&#x2F;&#x2F;quoteinvestigator.com&#x2F;2013&#x2F;10&#x2F;20&#x2F;no-predict&#x2F;" rel="nofollow">https:&#x2F;&#x2F;quoteinvestigator.com&#x2F;2013&#x2F;10&#x2F;20&#x2F;no-predict&#x2F;</a><p>[2]: <a href="https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=Z6rxFNMGdn0&amp;feature=youtu.be&amp;t=1457" rel="nofollow">https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=Z6rxFNMGdn0&amp;feature=youtu.be...</a><p>[3]: <a href="http:&#x2F;&#x2F;book.mfordfuture.com&#x2F;" rel="nofollow">http:&#x2F;&#x2F;book.mfordfuture.com&#x2F;</a>