5. OpenAI Embeddings API - Searching Financial Documents

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In this video, we build the backend for a simple semantic search engine using OpenAI Word Embeddings.

[parttimelarry]

Like the video? Support my content by checking out Interactive Brokers using the link below:

[SwingingInTheHood]

Not being an AI guy, I've been trying to understand embeddings and search vectors for the past two weeks. This is the first video I have found that explains it so that even I now get it. Whew! Thank you Brother!

[davidw]

Your recent video quality again has come in higher than expected - despite high priors, sir😁 damn good teaching and funny. Thanks man!

[Guy-Scott]

I appreciate the work you have put into this series. I like how you start small, with a few examples and build from there. Great job.

[private_]

Amazing video! Loving the series so far. Thank you for doing it!

[carlhlazo]

Awesome tutorial. Using familiar concepts made it easy to follow. I was finally able to understand much better what these concepts are and how they all relate.

[psychurch]

Thanks man, super clear explanations! Subscribed and excited to see what you’ve got coming up for music and ai ❤

[alanfeng]

Extremely well presented of how embeddings work!! I "kind of" knowing how it works, but after watching this video, I can say I "know" how it works! Thanks.

[blender_wiki]

Your contents are surpassing the simple high economic value and make the world a better place. 🙏🏾🙏🏽🙏🏼🙏🏻🙏🙏🏿

[rengavasan]

This is the best explanation Ive come across about embeddings anywhere on the internet. Great work Larry. Subscribed :)

[iamaguest]

very much appreciated for the simple introduction. Very good at explaination of something that is not easy to understand, great job

[shanthu]

Happy New Year! Great content learning a lot from you. Thank you so much for detailed explanations step by step guidance. Wish you all the best!

[robertcormia]

This is outstanding, his clarity and enthusiasm is amazing, real passion for this topic!

[Jberv]

Man! I just watched your video like its 5 minute length, very detailed. It took me so long to find this kind of sample/explaination. Thanks

[kenchang]

Thanks, Larry for a great video and explanation. Being an old former developer I am so fascinated with these LLMs, and your explanation has helped me organize how I will do a POC. I really appreciate you sharing your knowledge and enthusiasm.

[soesevenonesix]

Another great Video Larry! Thanks for sharing!

[karansajnani]

This is by far, the best video explaining embeddings! Thank you

[bakari]

Great Video ! Super interesting how this transformations works words to vectors ! I'm wondering how the architecture of the classifications works ! Thank you for the great quality of the video and the super interesting topic !! Don't stop !! 🥰

[seandiamond]

Bro you're the fkn man. I would have never known about this. I just created a search field in my Django website and it will be getting a massive upgrade now lol thanks again bro.

[mariusirgens]

The espresso-milk -> latte example blew my mind 😄