The files can take up to three seconds to load at times, and seemingly caches nothing on my phone so when I want to look at my notes on the tube, I can't load it.
The filters and relations are so powerful and I really love the flexibility: example, “show only tasks linked to projects with an active status.” But when they keep disappearing and redrawing, I just feel slowed down in the app lately.
But there is no feature at all that could excite me about Notion now unless they fixed the performance first.
I stopped using it due to performance also.
This really is incredibly hard. A large fortune 500 company I worked for this summer had a whopping 35000 confluence pages. There is no navigating a knowledge base that vast. You couldn't even clean it up, because there was no way to know if someone would need some piece of fringe information on a rarely visited page any time in the future.
I wish we had a librarian on staff on my team to just keep data organized
that's what it looks like to me at least, I don't see anything here that 50 other generic GPT-3 tools don't already do. It's just embedded in Notion
In some cases that can work, but generally you want to massage the inputs and outputs a lot more than that.
Doesn't have to be revolutionary. It helps to be "in just 1 place"
The whole feature is kinda cynical in that it already kind of implies that because nobody will read it, you shouldn't put too much effort into writing it either.
This is EXACTLY what people in the corporate space need! AI to help them generate nonsense corporate-speak so they can get back to work!
On the other hand, Notion wouldn't have full control anymore, usage stats might be hard to get when some users are offline, and so on, so unlikely Notion would do such a thing. Certainly their investors wouldn't like it either.
> Writing goes first into your local storage, then gets send to your remote storage
We do this already; writes are queued in SQLite or IndexedDB first and then asynchronously batched and streamed to the server. Our apps (Mac/Windows/iOS/Android) cache pages locally, and all platforms search a subset of documents locally in addition to server-side search. We’re actively improving this area as well.
Maybe ask the Google Docs team? They seem to have low latency online-first doc management figured out.
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.
- 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.
Almost any self-hosted ANN library will do if you're dealing with <1M vectors, but the indexes at these note-based applications tend to balloon very quickly into the hundreds of millions and billions. That's where rolling your own gets painful and where Pinecone shines.[1]
[1] https://www.pinecone.io - Disclosure: I work there.
- strip off all attachments --- these are archived on a central server w/ version control and links are passed around
- all e-mails are converted into threaded discussions in an hierarchical organization
Then, use an expert system to review and tag all messages and facilitate finding the correct forum thread/file.
"10 ways async communication is more productive" - alright, so you have an AI answering a leading question. Are you going to take the output as given and publish it as-is or spend time verifying and tweaking it? If you do the latter, how much productivity have you gained from rewriting a generated post compared to writing your own draft?
For automatic summarising and translating, okay cool, that really could be handy but this is almost commodity tech at this point.
I don't like my negative, pessimistic response here but I don't need tools that make it easier to write or create, I need them to keep things organised and up to date as you've mentioned. I need a better search that can help me find something that already exists, or actually point me to that article if I'm writing something that starts to look like a duplicate.
Can the AI say "this 'setting up the environment' post looks really similar to [some other setting up the environment post] which was written 6 months ago; is that what you're looking for/do you want to edit that?"
In my experience, AI providing the activation energy to get a first draft is highly valuable.
But more fundamentally, it sounds like you just don't believe the product works, which is fair, just not a very helpful comment. "How would the AI even know what that feature even is?" by learning about how its documented in the rest of Notion.
Fundamentally though, your comment has serious "Uber? No way that's going to work! Why would I get into a stranger's car?" vibes.
IMO, the most useful rejects were:
- Subscribe to a search query. Get an RSS-like digest of Slack messages, external document updates, CRM interactions, etc.
- Auto-responder I called "escal.ai," named after Slack's internal naming convention for help/support channels. These channels were prefixed with #escal-<subject>. I built a variation of https://arxiv.org/pdf/1901.05415.pdf to handle asymmetric retrieval tasks, where the answer to a question was typically a Slack post in another channel.
My gut says that every engineer they hired in the name of growth is trying to get their own little feature in to show impact. They prematurely scaled the company and it shows in the loss of focus.
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.