In there is a note that Wolfram is working on, or at least thinking about, the big unsolved problem - useful robots. Robot manipulation in unstructured situations is still very poor. But maybe someone will figure out a way to apply newer machine learning techniques to that. Google had a research group working on that, but they haven't been heard from in years.
The approach of the large language model, where you have a huge training set of general purpose info and a small prompt for the current task, might possibly work.
Yesterday I tried to get ChatGPT to tabulate some general information and sort it. It failed in many ways (grouping, sorting, inconsistency in field nomenclature, failure to cite sources, etc.). If it can't tabulate data correctly, I'm sure as hell not putting it in charge of motion systems. It'll get there, but not soon.
I think that with few exceptions to make truly useful and cost effective robots we have to design them from scratch for specific applications. In order to do that we need to have a viable highly documented supply chain, well understood fabrication processes and the capacity to assemble the results. And in order to do that at any scale across society we probably need a service provider to deliver "robot-on-demand" - probably flatpacked, with assembly instructions, and open source maintenance and design documentation. This is non-trivial, not in the least because people can't articulate their requirements. Same as software. ChatGPT can help there, but it needs guidance.
The approach of the large language model, where you have a huge training set of general purpose info and a small prompt for the current task, might possibly work.