As a newcomer to this, this was incredibly enlightening! My take-way is that yes, with some proper prompts for complex solutions, you get very close to "I might as well have done the whole thing myself". The point is the scaling: you go through these steps, because you then have a "prompt model" that you can use over and over for similar tasks.
@@LatentAI Cool! Yes, I totally think such a stream would be nice. Also a collection / dataset of high quality prompts would be nice. Let me know if you know of any. I am thinking of building an app around this to make it fun to learn.
Jonathan, thank you so much for this. I have been at quest where I have been studying many different techniques when it comes to extraction of data in form of products from a database we have. I have now developed a technique, but the hardest part that I have worked with several months is making the llm to update it's chunks from the database as it is a cost/performance balance that we are trying to achieve. We are very close, and we have seen that how we structure our data is as important as the base prompt. We are using retrieval augmented generation also. Can you please comment on this or make a video. I think this will be benifitial to many in the future. Thank you again, very good content.
Your tutorial is superb. If you may, do you have a PDF copy of prompting examples as shown in this video? It would greatly help so we'll just copy and paste to test and actually play with those prompting examples for more interactive learning.
As a newcomer to this, this was incredibly enlightening! My take-way is that yes, with some proper prompts for complex solutions, you get very close to "I might as well have done the whole thing myself". The point is the scaling: you go through these steps, because you then have a "prompt model" that you can use over and over for similar tasks.
Best video I've seen on Prompt Engineering, thanks.
Behazlaha!
Brilliantly clear and covered heaps! Legend
Wow ! That was useful. Many thanks Jonathan !
Thanks for your content it is great!
Thanks a lot, I benefited a lot from this seminar.
This was amazing. I'ld love to see more content on prompt engineering from you!
Thanks. That is on the roadmap.
Amazing video! I wonder if there any puzzles / challenges for learning prompts? Would be a fun way to learn!
There are! Check out the colab in the description. I wonder if a weekly stream of me prompt engineering hard prompts would be interesting.
@@LatentAI Cool! Yes, I totally think such a stream would be nice. Also a collection / dataset of high quality prompts would be nice. Let me know if you know of any. I am thinking of building an app around this to make it fun to learn.
Jonathan, thank you so much for this. I have been at quest where I have been studying many different techniques when it comes to extraction of data in form of products from a database we have. I have now developed a technique, but the hardest part that I have worked with several months is making the llm to update it's chunks from the database as it is a cost/performance balance that we are trying to achieve. We are very close, and we have seen that how we structure our data is as important as the base prompt.
We are using retrieval augmented generation also. Can you please comment on this or make a video. I think this will be benifitial to many in the future. Thank you again, very good content.
Your tutorial is superb. If you may, do you have a PDF copy of prompting examples as shown in this video? It would greatly help so we'll just copy and paste to test and actually play with those prompting examples for more interactive learning.
super straightforward, thx for the video 😁👍
Great session! Keep these coming
thank you for tips how to prompt:)
About the guarding post problem: posts, gate, Hasam . . . 3 different words for the same thing. Seems like a rookie misstake to me.
I can't access to colab file can somebody help me about it?
What is the name of the platform mentioned at 50:38? I can't understand it enough to catch the name, thanks.
Thank you so much.
Excellent.
Thanks but the colab file is not accessible. Kindly check