With all of the exciting directions knowledge management has been moving in lately, it's disheartening to see that Notion's product vision is already so uninspired.

Particular in the corporate space, the problem of finding relevant knowledge (and keeping that knowledge up to date) is a really hard problem. I think competitors like Mem are going to eat Notion's lunch here (categorization and perhaps tagging of stale content is a much more reasonable application of ML than this).

... further, Notion's performance is so absolutely awful that my very small company had to stop using it. Latency is incredibly relevant to note taking and writing apps.

The marketing page example is also so contrived: "Write a blog post introducing Notion's new AI feature." How would the AI even know what that feature even is? Where's the context? It seems like this just proposes static solutions to dynamic problems.

>Particular in the corporate space, the problem of finding relevant knowledge

I'm eagerly waiting for the day that I don't get frustrated with Notion's search. I'm not sure if I actually even bother with the search that much these days. I just try to drill down the page structure to find what looks relevant.

They could have used HuggingFace models to embed texts, put them in a vector search engine and serve results.

- models here: https://sbert.net/docs/pretrained_models.html

- fast vector search here: annoy, faiss, Milvus, Elastic, Pinecone

It's like the hello world of current day NLP.