Recurrent Relational Networks · HackerPapers discussions

Recurrent Relational Networks — mentioned by selalipop

Thu, 06 Jul 2023 23:55:40 GMT

I didn't say anything about existential risk, and I'm going to assume you meant LLM since training a NN to solve sudoku puzzles has been something you could do as an into to ML project going years back: https://arxiv.org/abs/1711.08028 To me the existential risks are pretty boring and current LLMs are already capable of them: train on some biased data, people embed LLMs in a ton of places, the result is spreading bias in a black box where introspection is significantly harder. In some ways it mirrors the original stochastic parrot warning, except "parrot" is a much significantly less loaded…

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Recurrent Relational Networks — mentioned by Isinlor

Thu, 14 Feb 2019 19:12:27 GMT

Neural Networks seem to be capable of both too. Although I'm just guessing what do you mean precisely by deduction. Would you agree that solving Sudoku requires deduction? "Finally, we show how recurrent relational networks can learn to solve Sudoku puzzles from supervised training data, a challenging task requiring upwards of 64 steps of relational reasoning. We achieve state-of-the-art results amongst comparable methods by solving 96.6% of the hardest Sudoku puzzles." https://arxiv.org/pdf/1711.08028.pdf "We present NeuroSAT, a message passing neural network that learns to solve SAT…

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Recurrent Relational Networks — mentioned by yonkshi

Mon, 24 Dec 2018 02:50:23 GMT

Sure. I don't have any holistic survey to prove my point, but an example of recent progress in terms of sample efficiency is this paper[0]. Derivatives of this paper have been used to solve Sudoku[1], Starcraft II[2] and more [3]. This paper enabled more efficient use of data by creating a probabilistic graphical model between logical sets. [0]https://arxiv.org/abs/1706.01427 [1]https://arxiv.org/abs/1711.08028 [2]https://arxiv.org/abs/1806.01830 [3]https://arxiv.org/abs/1806.01822

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