by pkkkzip | 2025-05-31 06:09:54+00:00
I think biochemistry might be the biggest beneficiary of "good enough" AI. Much of the expensive and slow parts of discovery (like creating new drug or making sense of some crazy complicated protein structure) are already speedrunning and while I'm on the conservative side of estimates, with mathematical certainty will see groundbreaking new drugs, discoveries from biochemistry field and not in the distant future but in a few years.

For the other stuff like automating white collar jobs, good enough might not suffice due to the intricate dependencies and implicit contracts formed naturally out of human groups.

Creative jobs will be the most impacted by "good enough" depending on the number of features. For 2d art it was almost certainly over (unless you add text feature to it like manga). You can see with increasing features, like starting with general photography, stock photography and now product photography are overnight made redundant. ex) with the latest Flux image editor negates a need to hire a photo editor, photographer, camera equipment, lighting, product artist. Veo3 not quite there but handles speech features in video generation that other models did not and getting closer to replacing videographers. I think 3d model is the next frontier here following the trend but is still quite difficult as it involves mesh generation/texture/rigging/animation/physics that also must come with shaders and interaction with other 3d models.

Software engineering falls somewhat in the creative field but also shares the complexity from white collar jobs for the same reason that will prevent it from being completed automatable with "good enough".

The hallucination issue is less of an issue and an old trope. The truly challenging enemy of AI of "good enough" is due to "not enough context" and "poor context compression and recall". The problems I listed in white collar and software engineering jobs is context problem. The compression of contexts cannot be stable as the former isn't solved. The fast efficient recall of contexts then cannot take place due to poor compression and so on.

This is just my observation of seeing how things are progressing. I do feel that we will see something different from LLM altogether that could solve some of the context issues but a major misalignment of incentives is what I think would prevent an AGI know-all-see-all type of deal. ex) you might not have any incentive to share all the essential context with the AI because you might become irrelevant and want it to stay in the dark. you might have a union or some social organization to legislate monopoly of human knowledge/skill workers in a field.

but perhaps THE most difficult problem even after we solve the context problem is the inability for the God AGI to be awake or conscious which is absolutely critical in many real world applications.

I like to focus more on the very near impact of what AI is currently doing in the labs and its impact on humans than worrying about who and when all of the other problems are going to be addressed.

Whether we get a UBI-first socialist world order or a continuation of technological feudalism with the poors still using GPTs while the rich sell the energy and chips (software would almost be worthless on its own by then) is the least of my concern.

I'm an optimist and I'm very excited for the very-near and immediate impact of our currently available AI tools doing the "good enough" in very positive ways.