Hands-on sessions / Hands-on session 2 /
This is another example of using LLMs to generate code. We will try to create a simple browser based html game and add some game elements to see how the LLM can help us create the game. The aim of the exercise is not to recreate the same thing as the LLM generates different code on separate interactions and neither to use the LLM in an "efficient" way by following prompt best practices but just to give an overview of what it can understand and do. In this instance we will create a game of Tic Tac Toe and build on top of it but you can try it with other simple games as well. At the end of the page you will find a link with the whole interaction we had with the LLM, all the prompts and resulting code, so you can look at that later as well.
diff --git a/FF2024/exercise_session_2.html b/FF2024/exercise_session_2.html index 904251b..161bcfe 100644 --- a/FF2024/exercise_session_2.html +++ b/FF2024/exercise_session_2.html @@ -49,12 +49,6 @@In this round of hands-on exercises you can choose various use cases/applications of LLMs to try out. We do not expect you to try out more than one of these in such a short time. Select one LLM use case that you think is most fun below.
-Hands-on sessions / Hands-on session 2 /
-One use of LLMs that has become popular is image generation. The version of Microsoft Copilot available via the universities can create images. The free version of ChatGPT does not offer full image generation capability but you can try and see what it gives you 😀.