To be fair to the creators of “half baked” libraries, you’re comparing our work to frameworks with several years head start with the backing of trillion dollar organizations (excluding polars). To have convinced ANYBODY to successfully make the switch is, to me, both somewhat of a miracle and an indication that there is a legitimate market for this work. I think it also dispels the hobby claim
As for your issues with Explorer, perhaps it is not the library, but your knowledge of Elixir that was a little too half baked? ;)
Telling someone they’re ignorant probably doesn’t get them to use your tech. Not the person you’re replying to; I use elixir everyday at work.
The biggest barrier to adoption of these libraries I can see is that there is not a wealth of resources to solve the actual problem the person is experiencing.
Googling “dyplr verbs in python” there’s a towards data science post that’s the 6th result. It has step by step code examples to get you started with what I guess the person is looking for.
Googling “dyplr verbs in elixir”, you get the explorer library’s GitHub page and docs as results. I see there’s an example on the first page, but docs present as a high barrier to entry. For better or worse, hand-holding helps get people using the thing, and there’s a SEO-fueled ton of python hand-holding resources out there.
I’m sure you’re aware of these things as the author of the book mentioned, but buying a book is a step for someone who’s already sold on learning the language/framework. Having google-able content is much more useful to get people in the door and in the day-to-day work looking something up.
Until something “cool” and well-known is made with Nx/Axon and friends, they’re gonna be seen as second-class to most people who aren’t elixir diehards. Somehow everyone in elixir-land recs these, but never has anything they actually use them for.
There’s also the switching cost. Most Python ML compute is actually done in C/off-loaded to gpu, so its speed is ok and not greatly constrained by the language choice. Python does have multiprocessing stuff which, while annoying in my experience, makes parallelizing stuff possible. Again, thinking from an outsider’s perspective, there doesn’t seem to be a “must have” reason to use elixir when they’ve already been working in python.
I appreciate your response. I should not have replied in the manner that I did. I think there are many ways to make the argument against using these libraries, and all of the maintainers would agree it doesn't make sense in many situations. I am fine with these arguments, but I don't think it warrants referring to the work we've done as half-baked or hobby projects. Even if not the intention, I think it implies a lack of effort and professionalism which comes across as more disparaging than simply pointing out the gaps.
Sean Moriarity, please use your elixir knowledge to write a user defined function or a plugin in explorer. It's easy to attack other people and assume they are ignorant.
It has always been possible to do custom transformations via Series.transform. And here is a PR adding it to dataframes: https://github.com/elixir-explorer/explorer/pull/912 - the PR uses existing APIs, it was possible before, it just makes it more convenient. I am sure more will be added later
Yeah the latency in my demo is definitely worse. There also seem to be some issues where it picks up it’s own audio and keyboard/mouse clicks and tries to transcribe them which leads to derailed convos.
The unnatural voices happen I think because for some reason the way I stream audio to the browser breaks up the audio from ElevenLabs, so you get almost this “start/stop” sound that makes it sound worse than usual.
There’s a lot of minor details to get right, but it’s a fun problem to try to solve. I wish Retell the best :)
Yes, we have an open issue to leverage that in a future release. The issue is that MPS misses many operations, so we will see how challenging it will be.
It should not be too hard! From what I saw Whisper is similar to Bart, and we have Bart. The missing piece is a library for audio processing to tensors.
No need to convert the format! Bumblebee supports loading parameters directly from PyTorch. You can just specify `{:local, path/to/checkpoint}` in `Bumblebee.load_model`
It’s a pleasant surprise to see this shared here, I am the author of this piece. Honestly I wrote this post for myself more than anything else. I also find that my knowledge in a lot of areas is very “surface level.” It’s really easy to regurgitate definitions, but it’s definitely harder to get to the core of those ideas. I hope you enjoyed!
As for your issues with Explorer, perhaps it is not the library, but your knowledge of Elixir that was a little too half baked? ;)