Can't agree more. Lisp was discovered/invented for the purpose of AI research. Of course, modern neural nets and transformers is a big departure from McCarthy's vision of AI - logical, interpretable, symbolic. However, if the current wave of AI hits a wall - and many serious researchers think it will, or already has at the margins - there's growing interest in neurosymbolic approaches that combine neural nets with symbolic reasoning. That's closer to McCarthy's original vision, and Lisps are genuinely well-suited for it.
Let's be honest: Lisp probably won't ever get bigger than Python, unless Python for whatever reason starts dying on its own. But if AI ever gets serious about interpretability, formal reasoning, program synthesis - all the stuff Lisp was built for - it just might quietly become relevant again in research contexts, without ever reclaiming mainstream status.
Scicloj has been building out a serious ML stack in Clojure - noj, metamorph.ml, scicloj.ml.tribuo, libpython-clj for Python interop. Beside that, people been proving that 'code is data' is exactly what makes it a better target for LLMs. Clojure is most token efficient PL - it's been proven. There are some recent interesting clj projects in relevance:
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Can't agree more. Lisp was discovered/invented for the purpose of AI research. Of course, modern neural nets and transformers is a big departure from McCarthy's vision of AI - logical, interpretable, symbolic. However, if the current wave of AI hits a wall - and many serious researchers think it will, or already has at the margins - there's growing interest in neurosymbolic approaches that combine neural nets with symbolic reasoning. That's closer to McCarthy's original vision, and Lisps are genuinely well-suited for it.
Let's be honest: Lisp probably won't ever get bigger than Python, unless Python for whatever reason starts dying on its own. But if AI ever gets serious about interpretability, formal reasoning, program synthesis - all the stuff Lisp was built for - it just might quietly become relevant again in research contexts, without ever reclaiming mainstream status.
Scicloj has been building out a serious ML stack in Clojure - noj, metamorph.ml, scicloj.ml.tribuo, libpython-clj for Python interop. Beside that, people been proving that 'code is data' is exactly what makes it a better target for LLMs. Clojure is most token efficient PL - it's been proven. There are some recent interesting clj projects in relevance:
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https://github.com/realgenekim/clj-surgeon
https://clojure.getpando.ai
https://github.com/yogthos/chiasmus