I did the same for the FDA drug label database and 100% believe that this the future for search. Semantic search layer for context then the large language layer for human answers.

Tip - you don’t actually need GPT-3 level embedding for a decent semantic search. Sentence transformers paired with one of their models is good enough.

I like this: https://huggingface.co/sentence-transformers/multi-qa-MiniLM... - since it’s very light.

Also, perhaps I am an idiot but I just used Postgres array field to store my embeddings array to keep things simple and free.

It was less than $2 to embed all 100+ episodes with the new OpenAI embeddings and was as easy as just making a bunch of API calls. Pretty hard to beat that experience.

Did you use the sentence-transformers model as-is or did you need to fine-tune it for medical data?

As is.. all it’s doing is pulling relevant context to the question. GPT-3 is doing all the heavy natural language lifting.

Holy f**ing s**t, this is amazing!

The UX is gorgeous, simple and snappy. I remember a few of Huberman's podcasts so I typed a few questions and the answers were spot on.

I'll be following you and your work, Riley.

Thanks a lot. It's nice when people appreciate the stuff I build for fun.

The UI is my own design system that I will open source at some point. The app is Remix with a Redis cache to keep things snappy.

This is an amazing piece of work and as others have said, the site and the UI are perfect.

On a side note, Huberman Labs bothers me. I was an avid listener to the early episodes. As I have ADHD, some of his explanations of the brain chemistry involved in attention and motivation were fascinating. But in one of the early-ish episodes he said some completely ridiculous about acupuncture (that it worked) that makes me think he has no real critical thinking skills.

I hope anyone out there listening to him and thinking about applying any of the approaches he talks about just takes the time to see whether any other sources say they have real-world effects.

To the credit of the author, this tool highlights the exact thing I'm talking about. Try searching for...

"How does acupuncture work?"

"Acupuncture involves taking needles and sometimes electricity and or heat as well and stimulating particular locations on the body. Through these maps of stimulation that have been developed over thousands of years, mostly in Asia, acupuncture can reduce inflammation in the body by stimulating the body in particular ways at particular sites on the body, liberating certain cells and molecules that enhance the function of the immune system and potentially can be used to combat different types of infection."

+1 to this. Huberman has the bad habit of constructing grand narratives that match his beliefs about health and reality, and packaging them as podcast episodes based on science. The only problem is that "based on science" might mean a single low-powered study, which Huberman cites and over-generalizes as if it was rock-solid fact. See this[0] discussion on Huberman's subreddit for more context.

Another example is his episode with Matthew Walker[1] (author of Why We Sleep), and his other episodes where he gives sleep advice citing Walker as an authority. The problem is that Walker's work is not good[2][3] (riddled with errors at best, fraudulent at worst).

To be clear: I'm sure a lot (if not the majority) of what Huberman says is correct, or at least matches our current scientific understanding. The problem is that some things are incorrect, and the layman has no way of knowing which is which (especially since all the content is presented with the same high-certainty "science-based tools" tone)

[0] https://old.reddit.com/r/andrewhuberman/comments/smnnb0/crit...

[1] https://www.youtube.com/watch?v=gbQFSMayJxk

[2] https://guzey.com/books/why-we-sleep/

[3] https://news.ycombinator.com/item?id=21546850

+1

Do you claim that acupuncture, a practice with significant use for thousands of years and supporting scientific studies, is invalid because it goes counter to your belief? [1][2]

Prof Huberman is an expert and he reads up on relevant studies before talking about something. Even though he may occasionally make mistakes (who doesn't?), your evidence to the contrary, if any, should be at least as strong as his.

Moreover, accusing that an accomplished scientist lacks critical thinking skills should require substantial evidence.

[1] https://www.nccih.nih.gov/health/acupuncture-what-you-need-t...

[2] https://www.hopkinsmedicine.org/health/wellness-and-preventi...

and there are many other links one can easily find.

You are right and everyone makes mistakes and I'm sure much of the Huberman Lab content is great. I don't claim that acupuncture is invalid because it goes against my belief. I claim that it does not work because there are no credible studies that show that it does. The links you have provided are not to studies, they are to organisations that promote/sell acupuncture. [Edited to correct a typo]

Thanks for your explanation of the rationale.

The links I provided are to trustworthy organizations in healthcare who usually practice evidence-based medicine.

There are many studies referenced here: https://www.evidencebasedacupuncture.org/acupuncture-scienti...

This one is published in Cell: https://www.cell.com/neuron/fulltext/S0896-6273(20)30532-8

But of course, one can always find faults in most single studies. It's the accumulative amount of evidence that supports the claim that acupuncture often work for certain types of syndromes. Note that in medicine, few things have irrefutable proof as in math or even engineering.

This is excellent! I have only recently begun listening to Huberman Lab and my biggest issue has been that I usually don't have an opportunity to write down most of the suggestions while I'm listening.

I've only done a single search with the tool so far, but it immediately returned the details that I was hoping for, along with context and other relevant mentions of the search terms.

Thank you kindly for making and sharing this.

You're welcome :)

> What are the parts of the brain that become de-synchronized in the ADHD brain?

>> The default mode network and the task networks become de-synchronized in the ADHD brain.

> What are the three parts of the brain that become de-synchronized in the ADHD brain?

>> The default mode network, the task networks, and the dopamine circuits.

From https://youtu.be/hFL6qRIJZ_Y?t=1714:

> An area called the dorsolateral prefrontal cortex ... the posterior cingulate cortex, and ... the lateral parietal lobe ... these are three brain areas that normally are synchronized in their activities ... that's how it is in a typical person. In a person with ADHD ... these brain areas are not playing well with each other.

I wonder if part of the problem might be the usage of text to speech. Did you consider scraping the transcriptions instead? e.g. with https://github.com/jdepoix/youtube-transcript-api

It uses Whisper for transcripts, which I believe are better than the YouTube generated ones.

My guess is that there are more relevant results from the semantic search than I'm including in the context (to reduce costs) and that exact snippet isn't being given to the answering model as context.

As I wrote here: https://news.ycombinator.com/item?id=34035123, I also wrote a tool to access them. I'm pretty sure there are English transcripts which are manually generated, not just the YouTube generated ones. I've always found them to be high quality, enough to make a book out of.

For Huberman Podcast I imagine he pays someone to do the annotations manually, so they're accurate. But on most videos I've found Whisper's annotations to be more accurate than YouTube's default annotations - not to bash YouTube's, they're still great but occasionally you get some weird annotations

I was just thinking the other day how I'd LOVE to have a way to get a summary of all of the experts' opinions Huberman has had opine on a given supplement. This goes beyond my expectations. Great work!

This is great. Since I also found the discoverability of podcasts annoying, I wrote a tool to download the Huberman Lab transcripts and convert them to an ebook: https://github.com/cmf/huberman. They still take a while to read though!

this is amazing, thank you for building this, i was literally in the process of doing this with the same stack but as a chat bot.

would you be open sourcing soon? totally understand if you want to keep it private but if you are open sourcing there’s a few other podcasts i’m interested in running this on for myself, like some parenting ones.

This is pretty amazing. Is this approach documented or explained anywhere?

I have some ideas of my own that I would love to implement similarly to this and it would help to know how to get started.

I imagine it is something similar to the following.

Preprocessing

1. Transcribe the dataset

2. Chunk the transcription into paragraphs.

3. Store the embedding of each paragraph into a vector database.

Querrying

1. Convert the user's query into an embedding

2. Query the vector database for the top N closest embeddings and fetch the paragraphs that correspond to them. To be robust against queries which you don't have results for you should limit how far away results can be from the user's query.

3. Using those paragraphs craft a propmt that you will give to a LLM.

4. Do any final filtering on the what you got back from the LLM.

I built something similar using a variety of YouTube channels focused on NLP, AI, etc. The app is here https://huggingface.co/spaces/jamescalam/ask-youtube - you can ask things like "what is a transformer model?" or "what is semantic search?"

The way I built it is documented here: https://www.pinecone.io/learn/openai-whisper/

Afaik it's the same approach as Riley, that is:

- Scrape audio of YouTube videos

- Transcribe to text with OpenAI's Whisper

- Use sentence transformer to create embeddings of text

- Index embeddings (with transcribed text, timestamps, and video URL attached) in Pinecone's vector database

- Wrap up the querying functionality in a nice UI

(this is for the search functionality)

If wanting to replicate the Q&A part, I also built something similar and wrote about it (https://youtu.be/coaaSxys5so) - it's essentially the same process but we return text snippets to GPT-3 along with the original question and it generates an answer

I should add, Riley used the ada embedding model (rather than sentence transformers). Performance wise they should be similar (in ability to encode meaning accurately) but the ada model can encode a much larger chunk of text. I don't know exact numbers but something like 1-2 pages of text in a typical corporate PDF. Whereas sentence transformers are typically limited to around a paragraph of text.

Typically you'd split the text in paragraph sized chunks to handle this requirement of sentence transformers, with GPT-3 embeddings you naturally have more flexibility there

Thank you :)

Sorry for the ignorant question, but who is Huberman Lab and why should we care? What drove you to make an AI interface for it?

This is so well done, thank you for your contribution. An open-source of the whole approach would be greatly appreciated as well!

Big fan of Huberman Labs. Excited to try this out!

Just a heads up that the styling and the JS doesn't work on Firefox.

Old version? Works on latest for me, but the CSS uses @layer which doesn't have great support with older browsers.

Ah, right, I'm still on Firefox 91 ESR.

Congratulations on launching! Can you please share your OpenAI API costs?

The embeddings cost less than $2 for all 100+ episodes. The cost for the answering calls to davinci are around $30 so far.

Can one generate the answers using text-embedding-ada-002 as well?

you can return the chunks of text containing the answers, but not generate answers as that isn't what text-embedding-ada-002 is for. For that you need generation model (davinci in this case)

It's not fine tuned. You literally just add something like "if the answer to the question isn't in the context, say 'I don't know'" It's wild.

So do you have the entire Huberman podcast transcript in the context of the prompt?

How did you do that?

He just told you? The prompt is a combination of the top 5 search results, the phrase to say it doesn't know if it does not have context, and the question the user is actually asking. That is sent to OpenAI and the response is shown along with the search results as the references.

What do you mean by embedding?

This is the process of mapping documents to vectors representing their semantic meaning. Here's a reasonable high-level overview:

https://en.wikipedia.org/wiki/Sentence_embedding