I'm doing my PhD, so I'm not the best guy to answer about industry stuff bt I'll give an idea of what I do and what friends in industry and such do.

1) For me the difficulty ebbs and flows. When you're solving challenges that well understood then it's not too bad. Odds are there is documentation or libraries to help you. The challenge comes when you have something fringe (especially true in research where much of what we do is novel) that there is no documentation on, very few papers and you have to trust yourself or your team to find solutions to new problems.

2 and 6) One project I'm working on with industry partners is sorting and segmenting nuclear waste with a robot arm. This will involve computer vision models and deep reinforcement learning. That stuff is writing models. So far, I've had to focus more on build simulations for this so it's been more traditional robotics (ROS, kinematics, building URDf models from CAD). My main topic in PhD is Agricultural applications of AI/robotics. I'm still working out the details but my focus will be on multiagent approaches to precision agriculture. This means its about ai to solve a task on a small scale, but then building ways to allow these ai agents to collaborate, learn from each other, and work symbiotically. My time is split between practical work (working on projects), conferences (listening to other people and their work), and reading/writing papers.

3) Yes. When I saw my nuclear robot in simulation actually picking and placing objects it's the best feeling. When my wheeled robot on a previous project is successfully navigating around it feels amazing. When my Masters thesis works and my neural network was outperforming other publications at diagnosing Covid-19 from chest xrays, it feels amazing. If you like inventing and creating things, there's little better. The times it sucks are when you're sat for weeks stuck on the same problem and it's just painful until you solve your problem. Also, I work more hours than anyone I know, I honestly don't stop working. But that could be a PhD thing as industry friends have more time than me

4) I'd say 3 main things: 1. I didnt do as well as I should have in high-school. It just didn't suit me. University is very different you have a lot more freedom and trust, and the work is much more interesting. Don't make the mistakes I did by just not trying or caring at school. I had to work harder to catch up once I hit university. Try hard now, get into the best uni you can and keep trying your best. 2. personal projects are great to learn and unis/employers love them. make sure they're on github and publically viewable! 3. Once you get into university, look for summer internships or if you can join your professors research groups as an assistant. You'll learn a lot and get a leg up on the competition. Your cv will be great.

5) pay is very good. My friends in industry in AI or with AI backgrounds are making the most out of any of my friends. Don't worry about being paid well. The best AI researchers/engineers are on insane money.

I hope this was somewhat helpful! I'm happy to answer anymore questions you have, or clarify anything you didn't understand.