10+ years ago, "AI" would likely refer to work in RL, evolutionary/genetic algorithms, etc.

Nowadays most of the spotlight seems centered on LLMs, CNNs, and other methods that are either human-labeled or at least reliant on human-created data, and have a static separation between "learning" and "inference".

I know that there are still non-LLM, non-CNN, non-anthropocentric topics of AI development currently, in RL and in other areas. Which would you say are the most prominent or promising today, or likeliest to come to fruition?

In order of nicheness

- Singular learning theory

- Vector-symbolic architectures

- Homomorphic learning

BTW, on the topic of the fading of genetic algorithms, here is an interesting recent take: https://statmodeling.stat.columbia.edu/2025/04/17/what-happe...