37 karma · joined May 24, 2015
We believe that solving autonomous coding will enable superintelligence more broadly.
Traditional OCRs are good at transcribing typed notes (e.g. pdfs) to editable docs, but do poorly with handwriting. The best OCRs I've seen can make a handwritten note searchable (e.g. Evernote) but still don't transcribe it editable form.
A lot of academic work on transcribing images of handwritten notes into text has surfaced over the last couple of years (mostly regarding using neural networks), and we decided to apply it
I was at LensCrafters the other day and had to fill out a paper form that someone input into a computer by hand, so definitely see the need there.
Our goal is to get a high enough accuracy for handwriting OCR to work in enterprise settings. 90% may be good for consumers, but I wouldn't want to put anyone's health on the line due to a transcription error
Definitely didn’t mean for it to put a damper on the tech - sorry for the mistake.
It handles that kind of script pretty well, mainly because we had a good amount of training examples from college student handwriting
Currently, it's a combination of the two, mainly because people often take notes hastily so word-based recognition coupled with spell check allow you to fix things on the fly. However, this also results in bizarre outputs sometimes so we're still figuring out what an optimal output looks like.
Adding digital handwriting support is a great idea. I actually think other companies do it pretty well, which is why we didn't go down that route. The reason is that they use a different type of algorithm that learns, in part, from the handwriting velocity, and gives you edit access on the go, which is not possible if you've taken the notes in a normal notebook.
We decided to start with plain notebook text mainly because it seemed like no one else had solved this problem to our satisfaction yet.
We staged the google doc bc there is still a 10-30 sec lag time in sending the note out, we'll fix it up. Thank you for the call out!
ML / NN have been around for a while, but there are a few reasons Scribble is only possible now:
1) Although classifying MNIST digits is the "hello world" of ML, doing the same with notes is substantially more difficult. The algorithm has to figure out sentence structure, punctuation, paragraph breaks, lists, and tons of other features that are hard to train. This problem is still a major research topic academically.
2) As a corollary to (1), while OCR has been around for a while, handwriting OCR has never worked due to (1).
3) Computing power has never been so cheap, training the algorithm would have been very expensive before AWS / Azure / etc abstracted hardware and made it inexpensive
I used to be a physics student and always had to draw plots / equations by hand, so it's definitely a feature I would love to see as well
We don't have a developer facing API at the moment but it's in the roadmap. Once our algorithm is accurate enough that it "just works" in an enterprise setting, we may open up an API so developers can build applications for their businesses.
Scribble currently only supports English, so it does poorly with other languages, but is pretty robust to poor handwriting in English (such as my own).
It gets about 85% of my handwriting correct (my handwriting is abysmal), so there's definitely room for improvement.
We don't have a developer facing API at the moment but it's in the roadmap. Once our algorithm is accurate enough that it "just works" in an enterprise setting, we may open up an API so developers can build applications for their businesses.
It currently happens in the cloud (purely a software design decision), but we could probably do it locally as well since the NN is already trained.
We were thinking of having similar TOS as normal note editing software (Evernote, Dropbox Paper) to mitigate security concerns. What do you think?
It's currently not perfect but handles a surprising amount of bizarre handwriting styles (cursive / messy notes). Looking forward to hearing your thoughts as we onboard to the beta,
Agreed re: Evernote. I actually really like that feature, because it makes handwritten notes searchable but found the same problem you identified with the lack of transcription.
My hope is we can integrate with players like Evernote / OneNote who already do a great job at centralizing notes.
The algorithm works on a large variety of handwriting (currently only support English).
It's a NN that was trained on ~100k different handwriting examples, and it's pretty robust to cursive / sloppy handwriting. Haven't tried European vs American numbers yet but I'll definitely give it a try now that you've piqued my curiosity