Lisp was ideal for reasoning systems, its homoiconic and meta-programmable nature is perfect for manipulating symbolic structures and logic. But when AI shifted toward numerical learning with neural networks, tensors, and GPU computation, Lisp’s strengths mattered less, and Python became the new glue for C/CUDA libraries like NumPy, PyTorch and TensorFlow.
Still, nothing prevents Lisp from coming back. It would actually fit modern deep learning well if a "LispTorch" with a CUDA FFI existed. We would have macros for dynamic graph generation, functional composition of layers, symbolic inspection, interactive REPL exploration, automatic model rewriting etc.
We almost had it once: Yann LeCun’s SN (the first CNN) was built on a C core with a Lisp interpreter on top to define, develop and inspect the network. It eventually evolved into Lush, essentially "Lisp for neural networks", which in turn inspired Torch and later PyTorch.
https://x.com/ylecun/status/1944504502260003296?lang=en
So Lisp didn't die in AI, it's just waiting for the right people to realize its potential for modern neural networks and bring it back. Jank in particular will probably be a good contender for a LispTorch.