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Solving the Jane Street reverse engineering challenge

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Re: Solving the Jane Street reverse engineering challenge

#61

Post by strken »

skinfaxi wrote: post #55
Emma_Goldman wrote: post #43

Earlier quoted context omitted.

The strong affinity between autism and intelligence seems strongest in technical fields, and engineering and computer science in particular. Autism does not seem to be over-represented to anywhere near the same degree in many other domains that are full of intelligent people.

Is this just from your direct experience or do you have data to back that up? Are you talking about credentialed engineering like mechanical or civil engineering or just software developers?

https://pmc.ncbi.nlm.nih.gov/articles/PMC9058071/ (if "strong affinity" means "bimodal distribution and I ignore the lower pole")

https://pubmed.ncbi.nlm.nih.gov/38497251/ (if "engineering and computer science" means "IT")

I don't know if it's actually true but the idea is interesting.

Re: Solving the Jane Street reverse engineering challenge

#62

Post by mdritch »

I love z3. I used it for the first time for Jane Street's puzzle last year involving a hashing alg disguised as a neural network. I use a lot of MCMC at work and I have made a few small investigations into MCMC model formal verification via z3, but nothing real yet. This has inspired me to pick that back up.

Re: Solving the Jane Street reverse engineering challenge

#64

Post by nostrebored »

thisisauserid wrote: post #57

I know nothing about z3 but it's from Microsoft. Would Google's OR-Tools component CP-SAT also be useful for something like this?

z3 is also just so thoroughly optimized that even if your formulation of the constraints is inefficient it is faster. it is a great library that lets you solve pretty complicated DP problems with a few dozen lines of code.

Re: Solving the Jane Street reverse engineering challenge

#65

Post by Emma_Goldman »

skinfaxi wrote: post #55
Emma_Goldman wrote: post #43

Earlier quoted context omitted.

The strong affinity between autism and intelligence seems strongest in technical fields, and engineering and computer science in particular. Autism does not seem to be over-represented to anywhere near the same degree in many other domains that are full of intelligent people.

Is this just from your direct experience or do you have data to back that up? Are you talking about credentialed engineering like mechanical or civil engineering or just software developers?

There's plenty of data on the clustering of high-functioning autistic workers in engineering and computer science, and the massively disproportionate share of autistic children with fathers and grandfathers in those fields. I work across technical and non-technical academic fields and the difference is quite obvious. It also follows naturally from some of the common presentations of autism, e.g., the high co-occurrence of dyslexia.

Re: Solving the Jane Street reverse engineering challenge

#67

Post by darksaints »

ctippett wrote: post #46

> I ended up using a tool called ‘z3’. It’s kind of magical? Every time it finds a solution I get a surge of joy. This resonates so much. I had a similar feeling after going to my very first operations research lecture. Solving seemingly incomprehensibly complex problems by framing them as a bunch of simple constraints and getting a solution seemed like such magic.

Yeah this was my experience too. I have an undergrad business degree, but got nerd sniped by an optimization problem, found a solution with constraint programming, and ended up going down a 15 year operations research rabbit hole with it.

Many people say that the way to tackle a hard problem is to break it down into smaller problems. I disagree. The best way to tackle a hard problem is to break it down into a defined search space and as many seemingly-redundant constraints as you can possibly list, then dump it all into a solver, go take a nap for a few hours or possibly a month, then come back to the problem solved for you.

Re: Solving the Jane Street reverse engineering challenge

#68

Post by josu »

I gave the problem to chatGPT 5.6 Sol Pro and this was the result:

> Worked for 12m 36s

> Solved

https://chatgpt.com/s/t_6a9aed0b09988191b0f2850dee056b48

Edit: It didn't independently solve it.

> 1. Used the public reconstruction to obtain the recovered RTL/constraint structure, including the 11×11 region map and the fact that it is a two-stars-per-row/column/region, non-touching puzzle.

> 2. Then independently wrote and ran my own exhaustive solver against that recovered constraint system.

Re: Solving the Jane Street reverse engineering challenge

#69

Post by ambicapter »

skinfaxi wrote: post #55
Emma_Goldman wrote: post #43

Earlier quoted context omitted.

The strong affinity between autism and intelligence seems strongest in technical fields, and engineering and computer science in particular. Autism does not seem to be over-represented to anywhere near the same degree in many other domains that are full of intelligent people.

Is this just from your direct experience or do you have data to back that up? Are you talking about credentialed engineering like mechanical or civil engineering or just software developers?

There's this trend on the internet to attribute success at any remotely technically challenging problem to the glorious power of autism.

Re: Solving the Jane Street reverse engineering challenge

#70

Post by kachnuv_ocasek »

mdritch wrote: post #62

I love z3. I used it for the first time for Jane Street's puzzle last year involving a hashing alg disguised as a neural network. I use a lot of MCMC at work and I have made a few small investigations into MCMC model formal verification via z3, but nothing real yet. This has inspired me to pick that back up.

Can you share more about the connection between MCMC and SAT/SMT? That's a crossover I never thought I'd see.
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