David Quarel Not you?

Iliad Intensive

October 2026

The most important things

Before
Join the Iliad Discord and check you can see #intensive-october. That is where you post any material you need to share with participants. If you can't see it, tell Leonard (@leonardbereska on Discord).
During
At 17:10, make sure everyone fills out the feedback form.
After
Fill out the end-of-day log: rate the day and tell us anything that went wrong.
Fill out Who stood out: name anyone who made a positive impression.
  • Questions about pay, travel, logistics or materials: see the FAQ.

66 project proposals are open for review. Stars, a sentence, or both. Read them.

Your days

[D.1]Decision Theory and RL Fri 9 Oct, leading 42 responses · energy 4.0/5
Overall +0.46 better than expected n = 41
Content +0.51 better than expected n = 41
Clarity +0.32 better than expected n = 41
Motivation +0.12 as expected n = 41
Exercises +0.37 better than expected n = 41
Readings +0.29 better than expected n = 35
Other activities +0.06 as expected n = 32
Pace +0.54 too fast n = 41
Difficulty +0.22 about right n = 41
Novelty +0.66 mostly new n = 41
Read what they wrote55
Worked well17
  • The answers ti questions by the lecturer.
  • The notes introducing Solomonoff induction and AIXI were very well-written and good for internalizing the more difficult conceptual material
  • The Notebook in Colab. And the sarcastic approach of the teacher also worked well, although it sometimes made him slightly difficult to approach (somewhat afraid to ask stupid questions).
  • Got my first exposure to RL through the well designed Notebook.
  • I think the material and discussions with the lecturer were very useful.
  • The exercises were so well curated and detailed.
  • Loud voice, good preparation
  • The material touched on the core concepts of RL that are relevant to understand what is still being used/practiced today. So, after getting the basics I hope to read more and familiarize with the concepts more. Good foundation.
  • Building around the central objects of expected value.
  • The mathematically rigorous presentation helped me, and several of my colleagues, latch onto the ideas and formatively develop intuition. Most of the exercises were well-considered and helpful for advancing intuition.
  • interesting material, amazing energy and knowledge from the speaker
  • The topic and formalisms were new and different from those covered on previous days. I really enjoyed it, and even when the material was difficult, David was very good at explaining it again and answering questions.
  • I liked the rigour and the teaching style. Often was too fast, but having time to go through the material helped, and I believe with this much content you cannot go any slower. So no complaints.
  • The lectures were the best part, but I wish they'd been slower.
  • The materials is well organized and great for me.
  • mix of examples and theory and coding
  • The derivation exercises were helpful.
Would improve27
  • I think the most helpful improvement for both learning about AIXI and Reinforcement learning is: immediately after giving the definition of either of these, give a specific example. For example, it wasn't clear that, when talking about reinforcement learning, that the action one can take only has probabilistic distribution on what actually happens after, and I think this would have been cleared up if the two examples were moved first. Also, it seemed like these slides were originally made when reinforcement learning and AIXI were covered for a longer time; it might be good for the slides to be adjusted rather than to try to cover as much as possible.
  • Great
  • I liked it
  • Reduce the amount of material
  • Slower pace
  • More time explaining relevance of Solomonoff and AIXI results, especially in practice. Less time on mechanical exercises
  • Begin the day with the notebook exercises to motivate the mathematical content. Next, I would reduce the volume of the material covered, and focus on getting the main point across, rather than rushing through multiple large topics in a single day. Of course, this is all specific to my background, and probably doesn't make sense for everyone.
  • I think a lot of stuff was poorly motivated. I wish we would have talked about what was mentioned in the calendar.
  • I think today was great.
  • It was a bit much different stuff crammed into one day, maybe remove the last part, and focus on AIXI so one has more time to read through the later parts
  • Went a bit fast but I honestly given how short the program is this is better than prioritizing real-time understanding. I think I like the speed-run style much better as long as we're given the foundational exercises to work on in our own time to cover our bases.
  • It was great! Although I don't know how much of the first part of section D we really studied (which was interesting to me i.e. the more economics of rationality section)
  • Encourage the audience to filter the questions.
  • Too many materials covered in a short time. The math materials could be covered at a high level (focusing on intuition and proof sketches) instead of going too deep. The colab tutorial at the end is nice and deserves more time.
  • Make the instruction a bit slower.
  • I would welcome more time on this material could -- it seemed interesting, but rushed and cool stuff skipped. Introducing the example from the very end at the beginning could help ground the abstraction through the day.
  • maybe a bit fast at points
  • It felt a bit rushed, but it was okay as I knew most of it beforehand.
  • today was way too packed, with the subjects seemingly weakly related to each other.
  • It was really good and interesting content, and great teacher with great understanding of the content / field. Only issue on my side maybe was that the content links are sometimes a bit messy, as in some links in intensive-october.pages.dev, some in iliad-intensive.org, some in discord. It gets hard to follow. Would be nice to have a simple and compact way to get to all lecture resources. Applies to previous days as well.
  • I could not download one of the packages for the Google Colab.
  • This was probably too much material to fit in one day. I would have preferred to go through some of the theorems slowly in class, rather than going through them on my own afterwards. The notes had a lot of notation, which made it difficult to keep track. Lecturer was clearly very knowledgeable and good at presenting, but it was impossible to get through all the material comfortably within the time frame. The parts that I could follow were great.
  • I feel like, at times, I was struggling to to see the connection bewteen the specifics of decision theory, AIXI, and how it relates to AI safety and existential risk. One question I had going into this particular section was learning what the load bearing assumptions (inside of decision theory) are for existential risk due to AI. I do think I was told these assumptions... I just am not sure what they were. I mean, I feel like I got a sense that the needle is in the haystack of info today but I'm not sure where though. I am excited to look back at the info and learn from it.
  • nothing
  • This is best lecture day this week
  • Very good - personally, I would remove some of the quantity / amount of detail to be tracked. Not in a manner to dilute any one individual topic, but in a manner that - in principle - the material could have been presented at a black board - stripped down to its essentials. I emphasize that this is a personal take, constituting an improvement on an already good program.
  • The pacing was a bit fast, but perhpas the only way to fix that would be to assign pre readings or split this across 2 days.
Changed my mind9
  • I'm better able to understand how to study and bound AI behavior in general rather than just specific models
  • I wasn't aware that there is such deep theory behind RL
  • N/A
  • The importance of RL in the AI world.
  • AIXI seems very interesting!
  • Kolmogorov complexity is a very cool concept and seeing its use to formalize the often-cited 'occam's razor' concept was very interesting.
  • I am very interested in the AIXI/Solomonoff Induction research agenda.
  • I didn't think this topic was important/interesting before, and my mind has been changed.
  • I do think that I underestimated how much the AI community understood mis-generalization and I am curious to learn more about how they think about it.
Other thoughts2
  • N/A
  • The material was bit too dense for me. I knew about RL before in different context, not the theoretical basis of it. So, having everything on the same day felt like a lot. The theory session itself could have been a full day. The coding session, where we were given a code to play with was too short to really understand what is happening. Spending more time on that would have been more useful for someone like me who has more coding background than the math.

The day

10:00 Lecture starts
12:30 Lunch at Mox
13:30 Afternoon session
17:10 Feedback form
17:30 Day ends. Dinner

Resources

Elsewhere