GPT-4 - How does it work, and how do I build apps with it? - CS50 Tech Talk

The session begins at 13:40

That's why these are some of the best universities in the world . no wonder why so many students wants to enroll in there The immediately include recent development in practical world instead of teaching you 20 year old syllabus

This lecture is going to be initial reference for so many people who are going to build things on top of GPT.

I've been working on ~2000 token long conversational prompts with response formatting and decision making even with data structures in the context and it just keeps on giving, spent hours tweaking my prompts and they keep on giving, amazing tech!

Starts at 13:40

I've been using GPT for quite a while and am glad I got to build up my own knowledge of what I thought it was capable of to then watch this and realize it can do SO much more!

Like always CS50 never fails to amaze.😍

Love to see how quickly people can adapt to new tech and start building

Loved the framework approach for each application!

My team is currently using GPT3.5 to build Tammy AI:face-blue-smiling:. GPT4 just dont make sense for a cost perspective now.

Pretty damn cool. Thanks for the chat. If we ask GPT how many times PIZZA was mentioned it will probably return 'too many times' :) Now let's go build an app and force the AI into a loop.

This is so basic but is so necessary, really good to be able to watch this. Thank you.

I thoroughly appreciate this talk, I feel it did a great job to inspire me further into this particular field of development, even if only in small ways that are relevant to my particular work, or even to just try things as he said by hitting things with this new hammer!

This was great lecture. Thanks for sharing this.

thank you for sharing and for opening doors to the field

I read that one of the reasons for the chatgpt inaccuracies is it's linear generation method. As mentioned it is trying to do it's best to predict the next logical word in a sequence. Unfortunately once it's made it's choice it is unable to correct the “stream of prediction”. This is apparently why, when you “prompt” it that there is an error it is able to re-read it's output and correct the error. I have heard that methods like “chain of thought” might help with this issue. This method allows the generation to backtrack up the tree to effectively undo a path it may have previously gone down and start down a different path. Much, much more computationally expensive though.

An excellent talk. Thank you for sharing.

Very good explainations! I would see these systems as a simulated intelligence or a way to do knowledge discovery from a learned model. But since it does not have real life experiences, needs, emotions and cannot "do" anything by itself, it seems to cover only part of what makes up a human or even animal. But certainly a great tool that can be used for many purposes.

What a time to be alive, between open-source human-led courses like this, and GPT-enabled tutors of today (not just tomorrow y'all, TODAY) we can empower the next generation with a quality education, refinement of critical thinking skills and curiosity!

This lecure is really inspiring, thank you very very much!!!