> I have discussed in this article three reasons that proves Machine Learning and Data-Driven approaches are not even relevant to NLU This is a pretty hard-lin

> I have discussed in this article three reasons that proves Machine Learning and Data-Driven approaches are not even relevant to NLU This is a pretty hard-line position to take, and given the authors credentials I'm inclined to believe this is somehow poorly worded and not reflective of the thesis he intended with this article. > Languages are the external artifacts that we use to encode the infinite number of thoughts that we might have. > in building larger and larger language models, Machine Learning and Data-Driven approaches are trying to chase infinity in futile attempt at trying to find something that is not even ‘there’ in the data > Ordinary spoken language, we must realize, is not just linguistic data I would be curious to know what the author thinks of multimodal representation learning - which is conceptually promising in that it opens the door for machine learning models to learn relationships that span text, images, video, etc. For example OpenAI's CLIP [1], and other models like it. [1] https://arxiv.org/abs/2103.00020 https://arxiv.org/abs/2103.00020