AlphaEvolve couples map-elites with LLMs. It's an key step in machine learning, in the vein of DQN for reinforcement learning.
AE brings diversity from the genetic algorithms community to large scale optmized deep learning and RL models.
It is a mandatory step for moving forward. The approach is clean and simple, while generic.
The only caveats is the per optimization problem definition of the map élites dimensions. But surely, this will get tackled somehow over the next few years.
If you don't know about map-elites, go look up Jean-Baptiste Mouret' s work and talks, it's both very interesting and universal.
Most software developers that I know spend only a fraction of time on that, if at all.
Generating diagrams is much more common than generating "images". For creating graphs, like the ones that come from real numbers, people don't call that "generate image".
There is an unimaginably large gulf of distance between an individual thinking about what an author would say about their writing, and a corporate entity selling the "opinion" of an LLM asked to act like someone.