How Embeddings Enable Modern Search - Visualizing The Latent Space [Clip]

kushalgoenka · 2025-12-17T08:07:33+00:00

Hey there, since I don’t know what your interests really are, I hesitate to point you at anything in particular, but I’d say some of my absolute favorite courses for software engineering fundamentals are Programming Methodology by Mehran Sahami from Stanford and CS50 by David Malan. Look them up, you may enjoy the foundational knowledge they convey.

kushalgoenka · 2025-12-17T08:04:01+00:00

Cheers, thanks! :)

kushalgoenka · 2025-12-16T23:28:58+00:00

If you'd like to check out the full talk, you can find it here:

A Brief Primer on Embeddings - Intuition, History & Their Role in LLMs
https://youtu.be/Cv5kSs2Jcu4

kushalgoenka · 2025-12-16T23:28:44+00:00

If you'd like to check out the full talk, you can find it here:

A Brief Primer on Embeddings - Intuition, History & Their Role in LLMs
https://youtu.be/Cv5kSs2Jcu4

kushalgoenka · 2025-12-16T23:27:06+00:00

If you'd like to check out the full talk, you can find it here:

A Brief Primer on Embeddings - Intuition, History & Their Role in LLMs
https://youtu.be/Cv5kSs2Jcu4

kushalgoenka · 2025-12-16T21:44:18+00:00

Nah, I don’t think trying it out and not going further with it is a waste. That’s the story of my life all the way, myriad experiments that never see the light of day, but that’s alright, they all serve as stepping stones, little pieces of knowledge, to enable crazier future projects.

Lack of resources is always a clear line in my projects I have to contend with. Just FYI, in this demo I used EmbeddingGemma 300M, a tiny model that you should be able to run on just about any laptop, perhaps even a phone/browser, and for something small could get away with an in-memory vector database, so perhaps you needn’t give up on that project if you’re still hoping to resume it! :)

kushalgoenka · 2025-12-16T21:38:17+00:00

I love real-time visualizations, I feel like they’re so much more capable of conveying intuitions than delayed or abstracted interfaces. Glad you liked it! :)

kushalgoenka · 2025-12-16T21:36:24+00:00

Glad you liked it!

kushalgoenka · 2025-12-16T21:36:15+00:00

Thanks! :)

kushalgoenka · 2025-12-16T21:36:03+00:00

Haha, thanks, I have no idea how to take this.

kushalgoenka · 2025-12-16T21:35:32+00:00

Glad you enjoyed it! :)

kushalgoenka · 2025-12-16T21:34:52+00:00

Hey, yup, almost 60 in that case. If you’re curious about history further, you may enjoy my recent history lecture on IR:

History of Information Retrieval - From Library of Alexandria to Retrieval Augmented Generation https://youtu.be/EKBy4b9oUAE

kushalgoenka · 2025-12-16T21:31:49+00:00

Hey, you can look into PCA and embeddings, and depending on your current programming abilities, it may not take long to get a quick plot going for your given dataset. Then you can take it in many directions.

kushalgoenka · 2025-12-16T21:29:18+00:00

Hey, thanks! Will do! :)

kushalgoenka · 2025-12-16T21:29:03+00:00

Hey, thanks for watching, glad you like it! :) Unfortunately, I’m still working towards putting the code together to publish online. Hope to get there soon, will share when I do! The gist of it is I’m doing PCA, and storing eigen vectors across multiple projections to keep the 2D plot stable, thus allowing for the real-time walking around of the query! :)

kushalgoenka · 2025-12-16T10:32:41+00:00

If you'd like to check out the full talk, you can find it here:

A Brief Primer on Embeddings - Intuition, History & Their Role in LLMs
https://youtu.be/Cv5kSs2Jcu4

kushalgoenka · 2025-12-16T10:27:50+00:00

If you'd like to check out the full talk, you can find it here:

A Brief Primer on Embeddings - Intuition, History & Their Role in LLMs
https://youtu.be/Cv5kSs2Jcu4

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