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chaisan

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Autoresearch for Integer Factorization

github.com
4 points·by chaisan·3 months ago·0 comments

[untitled]

1 points·by chaisan·4 months ago·0 comments

[untitled]

1 points·by chaisan·4 months ago·0 comments

[untitled]

1 points·by chaisan·4 months ago·0 comments

Autoresearch for SAT Solvers

github.com
167 points·by chaisan·4 months ago·32 comments

Autoresearch for SAT Solvers

github.com
3 points·by chaisan·4 months ago·1 comments

Monitor your world with one daily report

monitorish.com
1 points·by chaisan·5 months ago·1 comments

comments

chaisan
·3 months ago·discuss
we moved our whole org off Vercel after that selfie Rauch put out. rotten company, overpriced product for what it is, sneaky practices. never looked back.
chaisan
·4 months ago·discuss
have examples?
chaisan
·4 months ago·discuss
nice. for which problem?
chaisan
·4 months ago·discuss
yess. loads of space for further exploration here. there is an attempt to keep things as general as possible in the expert.md file, but hard to mitigate overfitting fully. however, changing the seed will not get you much further with all else in the solver constant. unless you try a number of seed that exponentially scales with the size of the problem
chaisan
·4 months ago·discuss
sure. in the limit, everything is parameter tuning. with large enough NP-hard problems, the complexity of the search space is big enough that its infeasible to get to a better state by just tuning params in any reasonable amount of time.
chaisan
·4 months ago·discuss
wrt. token usage?
chaisan
·4 months ago·discuss
somewhat
chaisan
·4 months ago·discuss
and it would take an algo change to the solver to jump to the next local optimum
chaisan
·4 months ago·discuss
yeh. ofc. but on any problem larger than 40 variables, the gains from random restarts or initializations will quickly plateau
chaisan
·4 months ago·discuss
the sum of the weights of the unsatistied clauses. we want to reduce this number
chaisan
·4 months ago·discuss
as its from 2024 (MaxSAT was not held in 2025), its quite likely all the solvers are in the training data. so the interesting part here is the instances for which we actually got better costs that what is currently known (in the best-cost.csv) file.
chaisan
·4 months ago·discuss
its just comparing the cost of the best solution found to the best known cost we had before. O(N). why optimistic?
chaisan
·4 months ago·discuss
nice. EDA indeed one of the top applications of SAT
chaisan
·4 months ago·discuss
An autonomous AI agent that teaches itself to become the world's top expert on MaxSAT. Given weighted MaxSAT instances, it learns novel strategies, finds better solutions and iteratively refines its toolbox. No human guidance.
chaisan
·5 years ago·discuss
Ntropy | https://ntropy.network/ | ML & Backend engineers | SF Bay Area / London, UK / Remote | Full-time

Ntropy is building a data layer to combine financial transactions from across organizations in a scalable and privacy-preserving way.

You will be one of the first hires joining the team of 6 (2 founders + 4 engineers). We are well funded and will be scaling up to 10-12 people over the next 4 months.

See https://jobs.ntropy.network

stack: Python / Rust / lots of GPUs