Um, no?

    Python 3.11.6 (v3.11.6:8b6ee5ba3b, Oct  2 2023, 11:18:21) [Clang 13.0.0 (clang-1300.0.29.30)] on darwin
    Type "help", "copyright", "credits" or "license" for more information.
    >>> import lisp
    Traceback (most recent call last):
      File "<stdin>", line 1, in <module>
    ModuleNotFoundError: No module named 'lisp'

Here's an essay I wrote 15 years ago about another "unreasonable" puzzle:

https://blog.rongarret.info/2009/12/worst-puzzle-ever.html

I can tell you from personal experience that organizing a "fake" conference is beyond trivial. All you need is a topic that is narrow enough that all of the attendees know and like each other. I was an attendee at several such conferences back when I made my living publishing papers, and I was astonished at how easy it was to publish bullshit as long as it was the right venue, and how borderline impossible it was to publish anything that I considered to have actual value. (In my career I published dozens of conference papers, but only one journal paper and one book chapter.)

In actual practice what I found was that the principle driver of publishing success has absolutely nothing to do with the quality of the work, it has to do with how much your reviewers think that you might some day be in a position to review a paper of theirs. This is the fundamental problem with peer review when: career success is measured by quantity of papers published, the resulting dynamic is governed by game theory, not scientific merit.

You don't even have to change the laws. Just changing the social norms would be enough. At the moment our social norms are that the ends justify the means. If you make money, or produce something that looks like a breakthrough, that is all that matters. How you did it, or whether the thing you did has actual value, matters not at all. As long as you've provided yourself with plausible deniability, that's good enough.

I know this because I've been the beneficiary of this system on multiple occasions, and it makes me sick. This is not the kind of world I want to live in.

> search is a fairly simple control loop

That's like saying that Darwinian evolution is simple. It's not entirely wrong, but it misses the point rather badly. The thing that makes search useful is not the search per se, it's the heuristics that reduce an exponential search space to make it tractable. In the case of evolution (which is a search process) the heuristic is that at every iteration you select the best solution on the search frontier, and you never backtrack. That heuristic produces a certain kind of interesting result (life) but it also has certain drawbacks (it's limited to a single quality metric: reproductive fitness).

> Beam search is an example of TTC in this modern era.

That's an interesting analogy. I'll have to ponder that.

But my knee-jerk reaction is that it's not enough to say "put reactivity and deliberation together". The manner in which you put them together matters, and in particular, it turns out that putting them together with a third component that manages both the deliberation and the search is highly effective. I can't say definitively that it's the best way -- AFAIK no one has ever actually done the research necessary to establish that. But empirically it produced good results with very little computing power (by today's standards).

My gut tells me that the right way to combine LLMs and search is not to have the search manage the LLM, but to provide search as a resource for the LLM to use, kind of like humans use a pocket calculator to help them do arithmetic.

> If LLMs are coming up with effective search formulation for "open-ended" problems, that would be a big deal.

AFAICT, at the moment LLMs aren't "coming up" with anything, they are just a more effective compression algorithm for vast quantities of data. That's not nothing. You can view the scientific method itself as a compression algorithm. But to come up with original ideas you need something else, something analogous to the random variation and selection in Darwinian evolution. Yes, I know that there is a random element in LLM algorithms, and again I don't really understand the details, but the way in which the randomness is deployed just feels wrong to me somehow.

I wish I had more time to think deeply about these things.

But do these characters correspond to sounds?