But this does not mean we cannot produce operational models of understanding, for example we have models of propositional/logical semantics and discourse such as Lambda Discourse Representation Theory and others, which can compute a formal representation of the meaning structures for a piece of text. These have been used e.g. for answering question, and working in this space has been a lot of fun, and continues to do so. At the moment people talk a lot about "deep" learning (neural networks with more than one hidden layer), but for such models we need to do a lot more work into explainability, because it is too dangerous to use black boxes in real life.
We still do not understand the human brain function in any substantial way, and it is perhaps a greater mystery of nature than even cosmology, where at least several competing theories have been posed that can explain parts of the evidence.
How are thoughts represented (if that is answerable, it turns out 'Where are thoughts represented?' has proven to be a meaningless question due to the distributed nature of human memory)? What is consciousness? What is a conscience? How do consciousness and intention emerge from materials that are not alive and that have neither consciousness nor intention? How to implement approximate models? (A lot of work to do!)