Why not just "ML-ware"?

It's not specific to neural networks, corresponds closely to what most people would refer to as "AI" today, but explicitly excludes handcrafted algorithms. The resemblance to "malware" is serendipitous.

Brainware.

Brains seem like the closest metaphor one could have for these. Lizards, insects, goldfish, and humans all have brains. We don't know how they work. They can be intelligent, but are not necessarily so. They have opaque convoluted processes inside which are not random, but often have unexpected results. They are not built, they are grown.

They're often quite effective at accomplishing something that would be difficult to do any other way. Their structure is based around neurons of some sort. Input, mystery processes, output. They're "mushy" and don't have clear lines, so much of their insides blur together.

AI companies are growing brainware in larger and larger scales, raising more powerful brainware. Want to understand why the chatbot did something? Try some new techniques for probing its brainware.

This term might make the topic feel more mysterious/magical to some than it otherwise would, which is usually something to avoid when developing terminology, but in this case, people have been treating something mysterious as not mysterious.

"tensorware" sprang to mind

because the goal here is to have a word that people skeptical of the "lifeyness" or "brainyness" of ai will accept to understand that it's not normal software, I really like "moldware" and will be using it until something sticks better. it nicely describes the general nature of function approximators without getting into the weeds of why or how, or claiming function approximators have inherent lifeyness. it also feels like the right amount of decrease in "firmness" after software.

more candidates to reject from, a few favorite picks from asking an llm to dump many suggestions: fit-; contour-; match-; mirror-; conform-; mimic-; map-; cast-; imprint-;

Groware/grownware? (Because it’s “grown”, as it’s now popular to describe)

Oozeware?

• Gradientware? Seems verbose and isn't robust to other ML approaches to fit data.
• Datagenicware? Captures the core of what makes them like that, but it's a mouthful.
• Modelware? I don't love it
• Puttyware? Aims to capture the "takes the shape of its surroundings" aspect, might be too abstract though. Also implies that it will take the shape of its current surroundings, rather than the ones it was built with
• Resinware - maybe more evocative of the "was fit very closely to its particular surroundings", but still doesn't seem to capture quite what I want

I don't really like any of those ideas. I think it's really interesting that aware is so related though. I think the best bet would be based on software. So something like deepsoftware, nextsoftware, nextgenerationsoftware, enhancedsoftware, etc.

I like "evolveware" myself.