>> These people still exist?
Of course, I just finished reviewing a few papers from ICLP (the International Conference of Logic Programming) 2023. This year there was a substantial machine learning element, most of it in the form of Inductive Logic Programming (i.e. logic programming for learning; ordinary logic programming is for reasoning). But also a few neuro-symbolic ones.
This September I was in the second IJCLR (International Joint Conference of Learning and Reasoning) where I helped run the Neuro-Symbolic part of the conference. Like the first year we had people from IBM, MIT, Stanford, etc etc (to clarify, my work is not in NeuroSymbolic AI, but I was asked to help).
Then in January there was the IBM Neuro-Symoblic workshop, again getting together people from academia and industry.
Yeah, there's interest in combining symbolic and statistical machine learning.
Just two data points about why (well because, why not, but):
a) Machine Learning really started out as symbolic machine learning, back in the '90s when people realised Expert Systems need too many rules to write by hand. A textbook to read about that era of Machine Learning is Tom Mitchell's "Machine Learning" (1997). The work the public at large knows as "machine learning" today was at the time mostly being published under the "Pattern Recognition" rubrik.
b) To the early pioneers in AI having two camps, of "statistical" and "symbolic" AI, or "connectionist" and "logic-based" AI, just wouldn't make any sense at all.
Consider Claude Shannon. Shannon was at the Dartmouth workshop were "Artificial Intelligence" was coined, in 1956. Shannon invented both logic gates (in his Master's thesis... what the fuck did I do in my Master's thesis?) and statistical language processing ("A Mathematical Theory of Communication"; where he also invented Information Theory; btw).
Or, take the first artificial neuron: the Pitts and McCulloch neuron, first described in 1943, by er, by Pitts and McCulloch, as luck would have it. The Pitts & McCulloch neuron was a self-programming logic gate, a propositional logic circuit.
Or, of course, take Turing. Turing described Turing Machines in the language of the first order predicate calculus, a.k.a. First Order Logic (mainly because he was following from Gödel's work) and also described "the child machine", a computer that would learn, like a child.
To be honest, I don't really understand when or why the split happened, between "learning" and "reasoning". Anyone who knows how to fill in the blanks, you're welcome. But it's clear to me that having one without the other is just dumb. If not downright impossible.