It helps to comprehend research papers (and not only papers - any document on any language) faster.
The tool is free to use, because we have credits from GCP. I guess at some point we'll need to introduce some level of subscription fee to keep it alive and useful, as it uses LLMs and vector search quite a bit.
Leo Boytsov, my guest on the Vector Podcast, made an honest and an eye-opening claim about vector search being intellectually rewarding, but professionally undervalued. What picked my attention was how he gives credit to people who actually deserve it, and how he speaks modestly about his own achievements. When professionally as a researcher, he accumulated over 1800 citations by now and helped to create the famous HNSW vector search algorithm.
I'm working on the tool, that includes AI. My original target is to test it on my https://www.youtube.com/c/VectorPodcast by offering something that Lex Fridman does for his episodes.
Current features:
1. Download from YT
2. Transcribe using Vosk (output has time codes included)
3. Speaker diarization using pyannote - this isn't perfect and needs a bit more ironing out.
What needs to be done:
4. Store the transcription in a search engine (can include vectors)
5. Implement a webapp
If anyone here is interested to join forces, let me know.
It helps to comprehend research papers (and not only papers - any document on any language) faster.
The tool is free to use, because we have credits from GCP. I guess at some point we'll need to introduce some level of subscription fee to keep it alive and useful, as it uses LLMs and vector search quite a bit.
Feedback is welcome!