大丈夫です。

Also bonus because Regal also has a "unique" hairline:

Generative AI, Machine Learning (ML) and Deep Learning (DL).

This is where I find most people confused about. I'm trying to find the simplest way possible to explain it, it may not be as accurate but at least you can get the idea (disclaimer, I have deal with ML but never get too deep into genAI, so apologies if I messed up several technical parts on genAI);

If you give an alphabet, A, B, C, D, E, F, feed into ML it'll only learn from those 6 letters. No matter what prompt you gave it'll only gave answers between those 6. But for genAI, it'll "generate" a "new" answer. It learns that all those 6 letters are alphabets, and used LLM and goes "oh, these are alphabets, and it have 25 letters instead of just 6", hence why it can "generate" answers other than those 6 letters feed into them.

Now what is LLM? It's a transformer architecture and it stands for Large Language Model. Basically include very massive data and parameters. ML also used data and parameters, but not as massive as genAI. (Parameter is the settings you put in the code. I'm not exactly familiar for how the settings work with genAI since I never work with one, but for ML; example is Random Forest, you can set the amount of trees that will effect how the randomization works. If the answer is not accurate then you tweak the numbers until you get the results you wanted. It's very technical but if you're confused don't worry about it, it's not important in this context)

That's one of the main difference between genAI and ML. ML has been around since forever. Even in video games. Easiest example I can think of rn is mmbn4, where fighting Dark Megaman, it copy the same pattern you've used during the whole game. That's ML, it learn from your input throughout the game and does the same. It cannot generate new move.

Now, before I get into genAI, first it's important to know about Deep Learning (DL). To put it simply, it usually used for unstructed data (examples like, all the dataset given are in the form of images or audio, unlike ML that used numbers, tables, or any structured data), but it does not generate new data. So, it's ML but more complex.

If you still keep up with me, thank you lol, but here's a recap:

ML -> DL -> genAI

Every single thing here is AI, it get more complex from left to right

Now, the long awaited, genAI. I don't know much on the technical part about genAI, I know about it theoretically, therefore I wouldn't get too deep here. GenAI "create" something "new". It's just like what I said earlier on, you gave only A, B, C, D as data for it to learn, it can gave, H, I, J as an answers. If you're interested to know about how it acts "human" I recommend reading "Attention is All You Need".

So NOW that you know the difference, here's why genAI is bad. Since it can generate data by itself, it can make shit up. Unlike ML where you yourselves have to manually select features to teach it, and DL where it does have automation but it doesn't use LLM, both ML and DL might give wrong answer but it does NOT create shit up.

Next is intellectual property. ML and DL may take your data for its training, but it didn't create "new" stuff from it. It just used for something like pattern recognition and all that, while genAI can generate something "new", while the original artist can't do anything about it since it's not their art anymore, eventhough genAI clearly copy it.

About the making people dumber issues, THIS! This is the part where "AI is a tool to help people" that so many people got confused!! The "AI" you talk about is ML/DL, not genAI. ML/DL is seen as a tool for a specific job. Like in cybersecurity field where you can used it to detect which IP is considered suspicious and others. Even in medical field too. The AI tools used to spot cancer and other medical issues are primarily DL!!!! NOT genAI!!! GenAI CAN be used as a tool, but it NEEDS to be double check by humans because, again, it can create shit up. Hence why genAI usually used in chatbots.

Okay from this part it's just my personal opinion:

GenAI has a lot of issues and I still can't see how it's useful even as a tool. If I needed certain ideas or have several questions, I can just Google it. For industry? Just use ML and DL. I think GenAI is used more on the creative side instead of technical side because there's no such thing as "wrong" in creativity, while for technical side, you need to double check the answer that genAI gave, which still requires human, hence defeat the whole automation thing.

If you still want to use GenAI, it's all your choices, I can't stop you, but I hope I at least gave a little explanation on how it works.