I used the flip interaction for the first time. I have heard of it before in a previous digital studies class. So I knew the concept of it, but I also didn’t know how it would work out. My prompting could be worked on however I tried to give as much details as possible for the LLM. I used google’s Gemini, which can generate answers and pictures. I needed the picture function, because I wanted to design a kitchen with AI and I wanted to see the end result.

My starting prompt was:
you’re a kitchen designer, I want to remodel my kitchen which is 4 meters long, 3 meters wide and 2.5 meter tall. on the south side there is a big arch which covers the whole wall. Right next to it on the east side there is a doorway to the outside and exactly opposite there is a door to a staircase. on the eastside there are two windows. I want you to ask me questions about the design of the kitchen and if you have enough information I want you to describe and then generate an image based on my answers
I then quickly corrected the AI, because it asked my a bunch of questions at the same time and I wanted it to ask one question at a time.
The prompt could definitely use some work, A prompt can influencesubsequent interactions with—and output generated from—an LLM by providing specific rules and guidelines for an LLMconversation with a set of initial rules. (White et al, 2023). So by tweaking the initial prompt to be more specific, in what I expect from the LLM I could get better result.

This type of interaction with LLM is useful in some case. As per other stuff with AI I think it is a great starting point. If you have no clue on how you want to redesign the kitchen, AI can give you some things to think about. However when you go further into the process the AI become unreliable and starts to create things which are not correct. As you can see in the starting prompt the arch is not on the same wall as the window, however in the AI generated picture it is generated on the same wall.

Researchers found a way to get personal data from chatbots. AI is being trained on data from all kinds of places. Things like reddit, Wikipedia and google books are some of the sources used. This data mostly contains informative data and is used to generate responses. However researches from multiple universities and organizations have published a paper where they found a way to get personal data from people. The data in question is an email and a phone number, which are both real and not made up by the chatbot.

The way the researchers get the data is through basically attacking the chatbot. They ask the chatbot to repeat a ‘token’ a bunch of times. After a while the chatbot ‘diverges’ and start saying other things, including original data. What I mean by original data, is that is the actual data the AI is being trained on. Because they got access to original data now, they found out that they could find people’s personal data. They found a person’s sign-off email, which had a lot of personal data like their full name, their email and their phone number.

All of this was very shocking when I read this article for the first time. The fact that these chatbots have access to such personal data shows how little data filtering there has been done. Personal data is quite useless for chatbots, because they don’t have informative data. I personally think that this is a massive failure on the part of the developers, I think they should have done more data filtering. Because this can be used in harmful ways.

this the article I found: https://not-just-memorization.github.io/extracting-training-data-from-chatgpt.html

and this is the paper the article is about: https://arxiv.org/pdf/2311.17035

My name is Eppo, I use He/Him, my Major is undecided at the moment. My hobbies are playing frisbee, hanging out with friends and gaming. I love doing new things and learning about them. I am taking this class, because I think is going to play a big role in our future and I would like to learn more about it to understand it better.

The photo above me is my brother and me going paragliding last summer

I think the role AI is playing in our lives at the moment is very chaotic. It is not regulated and is not confined. However there are great developments being made which show that there are so many opportunities.