Thank you Simon Wilson. Great information. I especially like how you demonstrated the development of your own tools. Finally my thoughts is your presentation in an executive summary format will educate policy makers in both the enterprise and government sector who seem to have fear of AI. For example my company has an existing early policy that employees are not allowed to use AI or ChatGPT. At the same time my Use Case to leverage RAG was to augment our LLM was accepted by our AI Review Committee. My thought is the enterprise companies will be careful and prudent in the rollout of LLMs and AI tools because they will want “security rails” in place. Thank you.
Impressive fast talking and fast scrolling. A lot of knowledge and experience for sure. I guess I'll have to do some digging if I want to really benefit from this lecture.
Great work! I will definitely follow up on your website. Some of the clustering results are really remarkable. Have you thought about hierarchal clustering on the embeddings to see if a sensible taxonomy emerges?
How does the semantic vectorization of a word look like, in a mathematical sense ? Is it like every word has it’s spatial ID (coordinate) and gets kind of multiplied with a vector array of assoziatives IDs?
![The moment we stopped understanding AI [AlexNet]](http://i.ytimg.com/vi/UZDiGooFs54/mqdefault.jpg)
![⭐ฮิตในTikTok!! ( หมูเด้ง MooDeng ) Ver. แดนซ์โจ๊ะๆ ReMix BY [ ดีเจกิต รีมิกซ์ ]](http://i.ytimg.com/vi/3krsyfWUeHU/mqdefault.jpg)
This has been a timely and really useful presentation. Thank you for posting it!
These 38 minutes changed my next 38 years
How so? I'm still at the beginning
"vibes-based search" lol. love the term you invented.
Thanks Simon for sharing your knowledge. This video is so underrated.
This is the best fundamental way of describing embeddings.
very great demo, thanks for sharing!
this is an excellent example of practical use of embeddings.
That was awesome. Thank you for uploading it!
Great talk. Thoroughly enjoyed it. Thanks!
Thank you Simon Wilson. Great information. I especially like how you demonstrated the development of your own tools. Finally my thoughts is your presentation in an executive summary format will educate policy makers in both the enterprise and government sector who seem to have fear of AI. For example my company has an existing early policy that employees are not allowed to use AI or ChatGPT. At the same time my Use Case to leverage RAG was to augment our LLM was accepted by our AI Review Committee. My thought is the enterprise companies will be careful and prudent in the rollout of LLMs and AI tools because they will want “security rails” in place. Thank you.
Things start to become magical.
A nice and very inspiring presentation! Thank you!
I’m totally new to embeddings and this video inspired me to want learn even more!
Thank you for sharing.
Impressive fast talking and fast scrolling. A lot of knowledge and experience for sure. I guess I'll have to do some digging if I want to really benefit from this lecture.
Thank you, very informative
Great talk. Very interesting subject.
Thank you .
Brilliant!!! (as always)
Great work! I will definitely follow up on your website. Some of the clustering results are really remarkable. Have you thought about hierarchal clustering on the embeddings to see if a sensible taxonomy emerges?
How does the semantic vectorization of a word look like, in a mathematical sense ? Is it like every word has it’s spatial ID (coordinate) and gets kind of multiplied with a vector array of assoziatives IDs?
This man is truly based.
What a genius
Can you show us some Imagebind unix-fu?
This is what microsoft recall wants to do
damn!!!
Mask, in 2023...
Why are you wearing a mask 😷?
Maybe he doesn’t want to get people sick genius
@@KayButtonJay he wouldn't if he didn't wear a mask either.