Intensive Teaching · September 2026

The most important things

Before: Join the Iliad Discord and check you can see #intensive-september. 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 17:40, 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.

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

Your days

[C.4]Abstractions and Latents Mon 21 Sep, leading 37 responses · energy 3.5/5

Overall -0.94 below expected n = 31

Content -0.81 below expected n = 31

Clarity -0.58 below expected n = 31

Motivation -1.03 below expected n = 31

Exercises -0.30 below expected n = 30

Readings -0.67 below expected n = 21

Other activities -0.54 below expected n = 13

Pace -0.29 too slow n = 31

Difficulty -0.16 about right n = 31

Novelty +1.13 mostly new n = 31

Read what they wrote47

Worked well9

Reading through the notes by myself.
having the time to read and do the exercises at my own pace
Lecturer communicated clearly.
- Reading a section and then doing the exercises straight after - The small group discussion
Speaker was clear.
Aron (?) seemed far better at explaining and communicating.
I think the concepts are very interesting and probably something I'd like to think about more in a couple of days when proposing a project!
Formal distinction between mediation and redundancy.
The structure: lecture->exercise->lunch->lecture->exercise->discussion

Would improve25

Improve the teaching and maybe the material selection
Fewer definitions and theorem proofs, more application of methods and experiment results.
To me, the connection to Alignment was a bit haphazard, contained in only a few bulletpoints at the end of the notes. I would prefer it to be more center stage, perhaps a presentation + discussion, could be very short. As it was, it felt very vague and swept aside. I found it difficult to focus during the lectures, partially because they were slow, but didn't go much beyond the formulas. I think they would be better if more intuition for what things mean (including questions like "what does this entropy tell us?") was explained.
There was no motivation at all on why this matters. I did not like the teaching style. Exercises in the first half just for working with notation and really easy.
The slides seemed completely AI generated and the concepts were not very well motivated and I think there was a shared feeling among participants that we didn't learn anything new.
Since some point of the intensive, I feel like we are manipulating the same concepts, but using different notations. I feel that there is a big overlap among courses but these frictions make it confusing and the short time that we have to familiarize with each topic everyday make it so that we cannot really delve deeper in the different theories.
There was very little content today. Most of the content that was present seemed to be information theory and very few new ideas and connections to AI Safety. It would be better if more new content was included. If there isn't much to be discussed as this is a very new field, it should be scrapped/merged with another similar session.
1. H needs to be defined with a name on the slide for entropy 2. questions were helpful in the lecture to understand the setup better, 3. in the notes label the conditional mutual information 4. add more motivation and ai safety context, how can these be tested/computed
I think this literature (which is very niche) could have been positioned better against the wider literature on latent variable models and latent identifiability in ML.
So many things. This day makes no sense. The research direction is very flimsy, the delivery was not very good and it's just difficult how this fits the alignment and safety direction. Iliad needs to seriously reconsider its curriculum to cover more in-depth established research programs like SLT.
Although the lecturer presented clearly, I think the material was not well motivated. The basic problem we were trying to solve - how two agents can agree on a set of 'beliefs' - should have been more clearly communicated from the very beginning.
- A concrete example of a natural latent early on, before the mediation / redundancy conditions - Pointing to the formal versions during the lecture (e.g. the natural latents paper) for going deeper
I'd like to see a slightly deeper theory + connections to sparse graphical models & linear algebraic algorithms to compute the things the theory cares about. At least for the simple gaussian models to get better intuitions.
The speaker was clear, but overall I think the material was not well motivated today. We should have begun with a clear description of what we were trying to achieve - i.e. how we could model different agents coming to the same set of 'beliefs' - and properly defined how the associated objects (observations, latents) relate to the problem.
I found the material very poorly motivated. The lecture exposition would have benefited greatly from a roadmap. The definition theorem format gave little insight into the 'bigger picture'
This material should be removed from the curriculum. It is absolutely not clear and not motivated why a less wrong blogpost from the last year should be taught for a whole day. Also the teaching needs to be reconsidered.
A bit more of a link to empirical things would have helped cement the information-theoretic foundations into a more practical context.
I didn't quite understand why we were learning this and felt a bit blindsided. I enjoyed the work on a technical level but still have little idea why it was useful for AI safety
I would like to hear about how alignment is done. We're halfway through the intensive and I feel like I've not heard anything about alignment
I think maybe a little more content on the algebra of information theory - the algebraic manipulations are not always very easy and even though I have some prior experience, I was defeated by the two-witness lemma.
The material felt very (nomen omen) abstract; I struggled to see how it could be applied to any more practical settings. There was also not much substance in the material, it felt like giving new names to existing concepts. Also, I think the lecturer was quite jet lagged and it negatively affected the flow of the lecture.
The talks seemed completely unprepared. There was little emphasis and clarity on why this matters. What is the big picture?? How do people use this with deep learning models? And for alignment?
Everything. This felt like an opaque subject that was not properly motivated in the beginning of the lecture. The exercises in the first part were ok to disentangle the difficult language but exercises in the second part were just "proofs left for the reader" which were not very useful to me. It would have made more sense to study real models where latents are concrete and useful. The lectures should include at least one example showing the different tree vs non-tree examples of latents like was presented in the notes. The notes themselves are better than Eisenstat's paper, but still need to be clarified with notation and language that is coherent with the rest of the Iliad curriculum. Working out an example on the white board would slow the pace down and help everyone understand. I did not follow the second part of the lecture at all. No idea what was happening.
More visual diagrams for the condensation framework.
This was too abstract, more examples needed. Not necessarily real life examples (although that is always welcome), but examples to each statement / theorem / computation would be highly beneficial during the lecture. Also, in the very beginning of the lecture we were just submerged into the subject unlubed. Having slides allows one to show the applicability or the empowering example or an impressive result or some gradual real-world examples that help us pick up the thinking so that we can translate it into formulae later. The intro does not need to be long (5-10 mins is completely enough), and I am aware an intro runs a risk of questions arising that drag the intro out into the philosophy (as the Day 1 of SLT has shown). But it has to be there to make the immersion gradual -- some people might have well woken up 15 mins before the lecture, while others, despite traveling there for 1 hour and being for 2 more hours on their feet, do need a gradual context switch. Also, the number of links that was mentioned for exercises was way too big. Like another Iliad website.

Changed my mind7

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I thought the concept was very interesting and I can almost see how it ties into other topics. I would have appreciated a more holistic view on things though.
I feel a bit frustrated and want to know more about the purpose and direction of research, and would rather engage with that kind of material. These questions are fun but it feels like a poor use of time. It's hard to choose a research direction when you don't see why you're doing it. I feel this sentiment is shared, If the situation is so urgent, we should be engaging more with actual research and what is the state of the field.
Understanding condensation does not seem like something useful because we have no proof that LLMs understand concepts that same was humans do. Isn't that the whole point that superintelligent AI could be an existential risk? An example is neuralese!
Natural abstractions can be mathematically formalized.
That I probably have no wish to do dry abstract math

Other thoughts6

Have chats in person with some of us for ideas to improve the intensive. I genuinely think that its a great initiative but there has to be some structural changes to the program.
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I was sick so I only attended the first half of the day
Solid foundational theory.
I will leave after lunch tomorrow because I have an onsite interview. That's why I can't make it to the London tour, sorry -- thank you for organizing btw! Must be very nice for non-locals.

The day

10:00 Lecture starts

12:30 Lunch at LISA

13:30 Afternoon session

17:40 Feedback form

18:00 Day ends. Dinner at LISA

When	Where
Mon 7 Sep	LISA, 25 Holywell Row, London EC2A 4XE
Tue 8 – Mon 14 Sep	23 Curtain Road, London EC2A 3LT
From Tue 15 Sep	69 Wilson Street, Moorgate, London EC2A 2BB

Resources

Elsewhere