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transitive-bullshit
yt-semantic-search
TypeScript2022–2023
transitive-bullshit / yt-semantic-search

yt-semantic-search

OpenAI-powered semantic search for any YouTube playlist – featuring the All-In Podcast. 💪

2Distinct people
5Mentions
0Explicit recommenders
544GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

OpenAI-powered semantic search for any YouTube playlist – featuring the All-In Podcast. 💪

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by week5 dated mentions

Observed mentions: 2022-12-21 12:04:40 UTC to 2023-02-09 16:36:15 UTC. Weeks start Monday, UTC.

0122022-12-19 00:00:00 UTC to 2022-12-26 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 commentsDec 192022-12-26 00:00:00 UTC to 2023-01-02 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2023-01-02 00:00:00 UTC to 2023-01-09 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2023-01-09 00:00:00 UTC to 2023-01-16 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsJan 92023-01-16 00:00:00 UTC to 2023-01-23 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-01-23 00:00:00 UTC to 2023-01-30 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-01-30 00:00:00 UTC to 2023-02-06 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-02-06 00:00:00 UTC to 2023-02-13 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 commentsFeb 6

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Dec 192022-12-19 00:00:00 UTC2022-12-26 00:00:00 UTC110
Dec 262022-12-26 00:00:00 UTC2023-01-02 00:00:00 UTC110
Jan 22023-01-02 00:00:00 UTC2023-01-09 00:00:00 UTC202
Jan 92023-01-09 00:00:00 UTC2023-01-16 00:00:00 UTC000
Jan 162023-01-16 00:00:00 UTC2023-01-23 00:00:00 UTC000
Jan 232023-01-23 00:00:00 UTC2023-01-30 00:00:00 UTC000
Jan 302023-01-30 00:00:00 UTC2023-02-06 00:00:00 UTC000
Feb 62023-02-06 00:00:00 UTC2023-02-13 00:00:00 UTC110

What Hacker News says

5 sources
tikkun·Feb 9, 2023Submission

Dev LLM stack, production LLM stack, example projects, & things you'll discover

The dev LLM stack - OpenAI + Pinecone + GPT-Index or Langchain - Perhaps also dust.tt for playing around with prompts, kinda like a more advanced gpt playground -- <https://docs.dust.tt/quickstart> The production LLM stack - The dev stack - OpenAI + Pinecone + GPT-Index or Langchain - arXiv for finding new research to build on - Prompt platforms such as Humanloop - ML frameworks such as PyTorch, Keras, Tensorflow - MLOps tools such as MLflow, Kubeflow, Metaflow, Airflow, Seldon Core, TFServing Example OpenAI Projects - <https://github.com/openai/openai-cookbook> - <https://gpt-index.readthedocs.io/en/latest/gallery/app_showcase.html> - <https://langchain.readthedocs.io/en/latest/gallery.html> - <https://gkogan.notion.site/gkogan/The-OP-Stack-aafcab0005e3445a8ad8491aac80446c> - <https://github.com/transitive-bulls
Read the rest
hit/yt-semantic-search> What OpenAI/MSFT should do - Fund "AI white mirror" -- a tv show that has beautiful visions a future where intelligence costs ~0 Things you'll probably discover - Embeddings work ok, but not great, from a user perspective. As a developer they're great to work with. As a user, the results aren't ranked quite right. Embeddings use cases will be better with GPT-4 or GPT-4.5. - All of the obvious gpt apps will be built. We'll get hundreds of basic gpt wrapper apps (and some of them will be big businesses!), hundreds of basic embeddings search apps. If someone can think of the idea and make it without needing specific relationships, credibility, or experience, then it'll probably exist by Summer 2023. - The developer energy in this space is intense. Adults are going to hackathons to build ai apps. This is awesome. - Devs using gpt will soon be a large enough market that startups will exist and succeed just by selling to developers that are using gpt-3 in production. We already saw it a little bit, but we'll get many more startups here. - How could AI not be better than me at all computer based things within 10 years? - AI is kinda like a kid. When they're young, they're not that smart. Then all of a sudden, they've gotten enough training data, and their brain (compute!) has grown, and they're doing useful stuff. This is related to why people will say that building models can feel frustrating because it doesn't work well for ages and then all of a sudden it works (CEO of Oasis said this, CTO of OpenAI said this, and Instagram co-founder said this). Would love input and feedback on this. I have similar things that I'm going to submit, covering what builders and engineers should do, what vector database to use, why no one else made ChatGPT before OpenAI, things holding ai powered apps back, and some other stuff like that. If you want a preview and are happy to give feedback, then email is in my profile.
10 points · Open discussion

Show HN: OpenAI-powered semantic search for the All-In Podcast

My favorite podcast is the All-In Pod, but search and discovery is tough for podcasts. So I built a semantic search index that lets you search across every episode of the pod with Google-level accuracy. It uses OpenAI's latest ada-2 embedding model and Pinecone to index the embeddings + k-NN search. Wrapped up in a Next.js + Vercel webapp. The project is designed to work with any YouTube channel / playlist. I'm just using All-In as a demo. Would love to hear feedback & suggestions. Open source here: https://github.com/transitive-bullshit/yt-semantic-search Note that the source is designed to work with any YouTube playlist / channel. I'm just using the All-In Podcast as a demo because it's my favorite.
4 points · Open discussion

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