The industry only cares about one thing: ability to market and sell as a means to make money. Ideally a compiler translates human-understandable code into the fastest possible machine-understandable code. Every tech company is essentially a compiler company because they need people to extract the most performance from their software and hardware.
There are a gazillion AI companies nowadays, they all need training or inference to go faster, they all need compiler people. Lattner [0] knows this, and that's why he started Modular AI [1].
If you want attribute grammars to be involved, you need to make them solve this problem better. That's your task. That's the value you bring.
How do you do this? Here are links to items posted over just the last few weeks on HN. Karpathy spells out neural networks [2], so understand the computational problem. Nvidia describes the difference between CPUs and GPUs [3], so understand the spectrum of computational fabrics. Now figure out how to best solve this computational problem given the different fabrics and their differing trade-offs.
Easy.
[0] https://en.wikipedia.org/wiki/Chris_Lattner