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nsypteras

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投稿

You Go Next (Standup Tool)

yougonext.com
1 ポイント·投稿者 nsypteras·2 か月前·0 コメント

Can GPT-5 Beat My Favorite Daily Puzzle Game?

nicksypteras.com
10 ポイント·投稿者 nsypteras·8 か月前·4 コメント

コメント

nsypteras
·6 か月前·議論
https://nicksypteras.com
nsypteras
·7 か月前·議論
Analyzing frontier LLM performance on my favorite daily puzzle game (https://www.nicksypteras.com/blog/cbs-benchmark.html) Next step is to assess how well the LLMs can create their own new, logically satisfiable puzzles in the same style. Then I'll have them battle it out, with one model creating a puzzle and the other attempting to solve it!
nsypteras
·8 か月前·議論
Congrats on launching! One immediate thought is that people will always be wary of running LLM-generated code on their machines even if it's sandboxed. Is one of the future business cases for this to host a remote execution environment that pctx can call out to rather than running the code locally?
nsypteras
·8 か月前·議論
Ya interesting thought - would be fascinating if generating games w/solutions is part of the training data pipeline. There's been previous work done on on testing LLMs on logic puzzles[1][2][3] so they could possibly be building off those ideas to improve performance.

[1] https://huggingface.co/papers/2504.00043 [2] https://huggingface.co/blog/yuchenlin/zebra-logic [3] https://arxiv.org/pdf/2403.12094
nsypteras
·8 か月前·議論
I'm impressed it recommended so many books i've already read and liked! I have a big reading backlog but once it's whittled down I will likely come back to this. One feature request would be to also show a "why this is recommended" for each recommendation so I can further narrow down the list for what I'm looking for
nsypteras
·昨年·議論
So much nostalgia for my Pebble. Got it right as I was seriously getting into programming. I still remember how magical it felt writing the C code to build my first watch face and how proud I was to show people. Amazing news <3