I would have agreed with this a few months ago, but something Ive learned is that the ability to verify an LLMs output is paramount to its value. In software, you can review its output, add tests, on top of other adversarial techniques to verify the output immediately after generation.

With most other knowledge work, I don't think that is the case. Maybe actuarial or accounting work, but most knowledge work exists at a cross section of function and taste, and the latter isn't an automatically verifiable output.

"Given the state of robotics" reminds me a lot of what was said about llms and image/video models over the past 3 years. Considering how much llms improved, how long can robotics be in this state?

I have to think 3 years from now we will be having the same conversation about robots doing real physical labor.

"This is the worst they will ever be" feels more apt.

That’s the deep irony of technology IMHO, that innovation follows Conway's law on a meta layer: White collar workers inevitably shaped high technology after themselves, and instead of finally ridding humanity of hard physical labour—as was the promise of the Industrial Revolution—we imitate artists, scientists, and knowledge workers.

We can now use natural language to instruct computers generate stock photos and illustrations that would take a professional artist a few years ago, discover new molecule shapes, beat the best Go players, build the code for entire applications, or write documents of various shapes and lengths—but painting a wall? An unsurmountable task that requires a human to execute reliably, not even talking about economics.

> If we can successfully get rid of most software engineers, we can get rid of most knowledge work

Software, by its nature, is practically comprehensively digitized, both in its code history as well as requirements.